Dear Reader,
Fifty years ago, the first slimline pocket calculator to be mass-produced was introduced to the world. In the five decades that followed rapid developments in the field of Electronic Engineering meant that the Global dependence on digital technology became increasingly more significant. From dawn to dusk our brains constantly interact with some form of Artificial Intelligence. Technology, in its various forms, serves us from birth to death; it helps us learn, prosper, and sometimes survive. In addition, as with any dutiful servant, it responds to our every wish, need and command at the press of a button. However, are technological innovations an unceasing list of magical creations of the human mind or can technology sometimes have sinister intent?
Since its inception in the Stone Age, Technology has always been a double-edged sword. A kitchen knife used with malice can be fatal, but a Lancet in the hand of a skilled surgeon can cure and prolong life. Although Nuclear Power can be used to generate electricity, nuclear weapons cause devastation as witnessed in the Japanese cities of Hiroshima and Nagasaki in 1945. More recently, in 2020, a novel method of Genetic Engineering was considered worthy of a Nobel Prize; but a year later an article in Scientific American entitled “The Dark Side of CRISPR” stated: “Its potential ability to “fix” people at the genetic level is a threat to those who are judged by society to be biologically inferior”
Researching the full implications of technological innovations has been a fascinating journey and we are extremely grateful to our student authors for their insightful, and at times sceptical, contributions to SCOPE 2022. The human like robots depicted on the front and back inside cover may well be a reality for our younger readers, as they approach the adult world in an uncertain future.
Param Thakrar (L6H2)
Kayan Vekaria (L6R2)
Charlie Pickford (L6J1)
Haberdashers’ Boys’ School Butterfly Lane, Elstree, Hertfordshire WD6 3AF
Telephone: 020 8266 1700 Registered charity no: 313996
Dr A. Perera Staff EditorThe Science and Technology Journal of Haberdashers’ Boys’ School, Elstree.
Letter mrom Editors
Param Thakrar (L6H2) Kayan Vekaria (L6R2) Charlie Pickford (L6J1) & Dr A. Perera
A Brave New World?
Computer and Programming: a brief outline of the origin and milestones
Devarshi Mandal (10J2)
Technology and space exploration Ishan Visvanath (7C)
(L6H1)
Are NFT’s sustainable?
Amey Gupta (10H1)
Biotechnology: an introduction to CRISPR-Cas9 Aarav Rajput (8H)
Quantum Computing in a nutshell Gautham Arun (9C1)
Technology, regulations and Formula 1 Zuhair Hemani (L6M1)
technology: past, present and future Rishi Maha (10M2)
How did X-ray diffraction help to confirm the structure of Benzene? Charlie Pickford (L6J1)
How a French Mathematician’s interest in heat revolutionised data storage Sahrid Kancherla (11R2)
Anil (10H1)
The impact and consequences of the rapid advancement of Artificial Intelligence on business and employment.
Faraz Ahmad (11R2)
Can we see a future where robots take over the jobs of doctors? Aamir Salim (7S)
Smart cities: a smart choice? Niccolo Ruju (10S1)
Is technology really an advancement to our society? Shuaib Magamedov (8C2)
Work experience: my reflections on shadowing an Orthopaedic consultant Sanjit Naique (L6C1)
The 2021 Nobel Laureates
Computers are required to fulfil many purposes, be it leisure, or work-related. However, their origins stem from simply being machines used to perform calculations, rather than the complex, versatile machines they are today. This article aims to detail the conception and creation of the first computer, and address the recognition of their extraordinary capabilities, with the beginning of programming. What followed the birth of the first computer was a revolution in information technology and artificial intelligence [1].
The term “Turing-complete,” in simple usage, refers to a general-purpose computer which roughly has the
capability of simulating the computational characteristics of other general-purpose computers. The Analytical Engine, designed in 1836, was the first general-purpose computer that could be described as Turing-complete and is therefore often referred to as the first computer, with its designer Charles Babbage being described as the father of the computer. Its predecessor, the Difference Engine, was Babbage’s original attempt at constructing a computing device. It was a special-purpose machine, which would calculate, and subsequently index, polynomial functions. However, due to a number of obstacles, its construction was abandoned. Alternatively, the Analytical Engine’s descendants have seen more success, and a variety of
similarities can be noted between them.
The Analytical Engine was yielded instructions through the use of punched cards, providing it the capacity to be a programmable device. This gave it an unprecedented degree of versatility. The method was inspired by that of the Jacquard loom, designed in 1801, by a weaver named Joseph Marie Jacquard. This was a loom that used wooden punch cards to automate the design of woven fabrics. The punch card system was then further developed by Herman Hollerith to calculate the 1880 US census and he subsequently proceeded to establish a company that would become IBM. [2][3]
Ada Lovelace, in 1843, would annotate a set of notes by Luigi Federico Menabrea based on Babbage’s 1840 Turin seminar. Included in these annotations is an algorithm with the purpose of calculating Bernoulli numbers. Often regarded as the first algorithm designed with the purpose of being implemented on a computer, Lovelace is remarkably credited as the first computer programmer. Moreover, she highlighted the fact that the potential of
such devices exceeded mere calculation, predicting the use of modern computers a century before a similar comprehension.[3]
In 1936 Alan Turing conceptualised the universal machine that would compute all that was computable [4]. The Turing machine is the basis of modern computers. In 1950 Turing published a famous paper entitled “Computing Machinery and Intelligence” in which he introduced the Turing Test which determines if a computer can demonstrate the same intelligence as a human [4].
The first electronic digital computers were believed to be the Colossus, built by the British in 1943 and the ENIAC built by the Americans in 1945 [5]. The Electronic Numerical Integrator and Computer (ENIAC) was the first programmable electronic digital computer, designed for general purposes [5]. Two years later, in 1947, Bell Laboratories invented the transistor, a binary switch and the fundamental building block of a computer. A modern central processing unit of a computer can have up to a billion transistors [6].
Figure 1. Evolution of the computer. [11]
The first computer language COBOL (Common BusinessOriented Language) was developed in 1959 and was originally designed by Grace Hopper in 1953 [7]. COBOL was created with the intention of having a portable programming language for data processing by the US Department of Defence. Instead of using numbers for computer instructions COBOL uses ‘English-like’ words and is a high-level programming language for business applications. In other words, it is closer to human language than machine language. Almost in parallel to COBOL, in 1954 IBM introduced the programming language FORTRAN, which is mainly suited for numeric and scientific computing [1]. The first ever Artificial Intelligence (AI) conference was held in 1956 and in 1958 the integrated circuit was invented by two American electrical engineers, Jack Kirby and Robert Noyce. Although Noyce passed away in 1990, he founded the Intel Corporation in 1968 [13] [14]. Kirby was awarded the Nobel Prize in 2000 for the ‘computer chip’ [4].
The invention of the computer chip undoubtedly led to an exponential rise in the development of computer technology and artificial intelligence; and in 1967 the first computer based on a neural network that ‘learned’ through trial and error was built. This followed a decade of research on neural networks and by the 1980s they were widely used in several AI applications. Neural networks are meant to mimic the behaviour of the human brain and are used in the fields of AI, machine learning and deep learning [8]. An invention which was to allow multi-tasking
with a graphical user interface was introduced in 1984 by Bill Gates and Microsoft. Windows was to revolutionise the use of computers, and through partnerships with personal computer makers, became the dominant operating system in business and homes worldwide [9]. In a similar fashion in 1989 the British scientist Tim Berners-Lee, working at CERN, invented the World Wide Web which was meant to meet the demand for automated information-sharing between scientists and institutes around the world [10]. Ten years later, in 1999, users became familiar with the term ‘Wi-Fi’ as the possibility of connecting without wires, accommodating the exchange of data by radio waves.
The decade starting from 2000 saw the launch of the first MacBook Pro by Apple in 2006 and a year later, in 2007, the same company released the first iPhone. The MacBook Pro was Apple’s first intel-based, dualcore mobile computer and the iPhone brought the computer to the palm of our hands [1]. A further leap in computer technology occurred in 2016 when the first reprogrammable quantum computer was created. In summary, computers have become an important part of everyday living and the dependence on technology is ever increasing. The first full-sized digital computer was developed in 1944 and weighed five tons. [11] These firstgeneration computers, from 1940 – 1956 used a basic machine language for programming. From 1956 – 1963 saw the second-generation computers with transistors and the third-generation machines (from 1964-1971) contained the integrated circuits.
The Computer and Programming: a brief outline of the origin and milestones
Virtual Reality (VR) can be either similar or completely different from the real world. It is a computer-generated simulated experience, which is comparable to, but distinct from Augmented Reality (AR), which is an interactive experience of a real-world environment. The objects in the real world are enhanced by computer-generated information of the different mental perceptions, such as vision and sound [1]. Virtual reality is one of the most recent developments in the technology world and it has many possibilities.
VR allows the user to simulate an experience using a headset, within an interactive computer-generated environment. In this virtual world, the user is able to learn from the immersive simulated experience by wearing special 3D goggles or gloves that provide sensory feedback [2]. The use of VR in medicine is becoming increasingly popular in a variety of applications, which include clinical training for doctors and medical students, patient care, marketing and public awareness of diseases,
conditions and processes. Given the reliance on VR for medical training, it is not surprising that in the near future, the estimated global market for VR could be more than around 4 billion dollars [2].
The dissection of cadavers was the norm for every medical student for centuries, in all parts of the world. However, with VR, the interior of the human body can be visualised, unveiling otherwise inaccessible parts. Computer graphics can offer in-depth detail of any part of the body and can also be used to mimic common surgical situations. In addition, real-life surgical procedures can be filmed from multiple angles and incorporated with models of the site of operation, providing the student with an opportunity to operate in VR [2]. In terms of orthopaedic surgery, a study has found that students with VR training for a particular procedure completed it 20% faster. In addition, the VR trained group completed 38% more steps correctly than those with traditional training [3].
Medical training of practitioners no longer considers the rote memorisation of facts a priority, but rather how an individual evaluates and applies the information gathered for patient care. This requires more clinically relevant and practical teaching, which includes VR-based learning [2]. For example, the student can be in a virtual A&E department facing a patient with chest pains. The need for taking a history, undertaking an examination with the family members present, and working in the midst of a busy environment can be challenging. However, virtual training allows the student to learn how to focus on the critical task of decision making, critical thinking and critical reasoning whilst at the same time encountering numerous distractions [4].
In terms of patient care, individuals with phobias are treated with simulated VR experiences. These could be most useful for conditions such as agoraphobia or acrophobia where exposure of the fear in small increments can help overcome the phobia especially after the immersive experience [2].
In addition to the use of VR in hospitals and universities, other healthcare systems are adopting the use of VR simulation in 18 NHS trusts across England [4]. The objective and standardised nature of the various simulated scenarios employed allows institutions to implement programmes of recruitment and assessment using VR. For example, clinical competency can be assessed by employing various VR scenarios as part of the interview process [4].
Despite the many benefits of the immersive technology, the most obvious impediment of using VR in clinical practice is the cost of the hardware and software components [5]. The future projection for the value of the VR market in in 2026 will be approximately $41 billion, which is a significant increase from a mere $2.7 billion in 2020 [6].
The increasing demand for VR in healthcare arises from a desire for companies and medical groups to investigate the versatility and potential of the technology. The expansion
of VR into the varied and diverse uses currently employed in the medical industry is also due to the technology becoming more affordable and accessible [6]. Recent advances in hardware and software have enabled the use of more comfortable headsets and software which is more compelling to the working environment. Lightweight headsets allow the user to wear them for longer periods without discomfort and the more sophisticated software provides a greater visual experience for in-depth immersion [6].
Due to the global rise in mental health demands, treatments such as cognitive behaviour therapy (CBT) have turned to VR as a tool for obtaining more positive outcomes [7]. Virtual Reality Exposure Therapy (VRET) has proved successful for treatment of anxiety disorders such as Post-Traumatic Stress Disorder (PTSD) and social phobia. A form of CBT, the treatment allows the patient to face a simulated version of the feared scenario or object, instead of the real or imaginary threat. This form of therapy ensures patients are in a safe environment
and will be more comfortable facing the challenge of the unpleasant experience. Due to the possibility of creating complex or delicate scenarios, VR has also been used within the CBT framework for treatment of substance abuse and eating disorders [7].
The emergence of digital health companies such as Sharecare, which offer powerful VR tools for medical education, further fuels the desire for VR in medicine [8]. The award-winning content produced by the Sharecare Reality Lab include medically accurate physiology, anatomy, disease and treatment simulations in stunning 3D detail. In July 2019, Sharecare announced a licensing agreement with Yale School of Medicine (YSM) to supplement its curriculum with resources for virtual training and instruction [9]. Sharecare YOU will allow students to visualise the functions of the human body and organ systems in a 3D environment.
Faraz Ahmad (11R2)
In the last six decades, we have made vast scientific gains and relatively recently, in the late 1990s, there has been an accelerated increase in technological progress and development. Specifically, in the last decade alone algorithms in machine-learning have grown with the advancement of enhanced deep learning and smarter neural networks [1]. Figure 1 depicts the differences between Machine and Deep learning.
Figure 1. Differences between Machine Learning and Deep Learning [2]
100 is fully digitalised)
information and communication
Accomodation and food services
Professional. scientific and technical activities
Computers, electronics, machinery and equiptment
Automotive All Utilities Commodities
Administrative and support services
Real estate activities
Basic manufacturing Transportation and storage
Wholesale & retail trade Construction
Figure 2. The most digitalised industries [8].
0 10 20 30 40 50 60 70 n 2018 n 2016
AI can be used to improve businesses in areas including predictive maintenance, where its ability to analyse large amounts of data from audio and images can easily detect anomalies in factory-based assemblies such as in aircraft engines [3]. In businesses with high demands of logistics, these new AI systems can effectively optimize routing for consumer delivery, thus improving fuel efficiency and reducing delivery times all allowing the business to cut costs and gain better reputations [4]. In sales and retail, combining customer data and past transactions with social media monitoring, all help generate individualized recommendations for the consumer, allowing retailers to target their demographic accurately [5]. In many of these cases, AI adds value by improving on previous analytical techniques to encourage industries to develop [6]. A fundamental property of AI is Data Analysis, which is used in every facet of business. It is reported that over 90% of the most successful businesses have ongoing investments in artificial intelligence. A survey carried out by IBM, a world leader in technology, found that 45% of respondents from companies with over 1000 employees have adopted AI. In addition, in 2020, the business market for AI was valued at $51.08 billion, with the projection for 2028 being over $640.3 billion [6].
Even though many organisations have already embraced AI, the pace and its extent are very uneven. Only around
half of the respondents in a 2018 McKinsey survey on AI adoption say their companies have embedded a minimum of one AI system within their business with another 30% still steering towards AI [7].
The gap between early AI adopters and others is rapidly widening. Sectors that are highly ranked in the DMCC Industry Digitization Index (Figure 2), such as high-level tech and financial services, are leading AI adopters and have the most ambitious AI investment plans. As these firms expand their AI adoption, those lagging behind will find it harder to catch up [8].
Around half of all work is currently automatable. They include mainly physical activities in highly predictable, structured environments (such as food preparation), as well as in data collection and processing, which together account for roughly half of the activities across the major sectors in developed economies. Figure 3 shows the existing risk of automation with different job types [9].
The pace and extent of AI’s adoption and its impact on jobs will depend on several other factors besides availability. Among these are the cost of distribution, adoption and the labour market dynamics, including its supply and quality of work. The public acceptance and various governing factors will also determine the timing. How all these factors play out across sectors and countries will vary, and countries will be depending on the labour market dynamics to give them the correct workforce. For example, the United States is an advanced economy meaning that jobs affected by automation there could be more than double that in India due to a wider availability to AI.
The impact and consequences of the rapid Advancement of Artificial Intelligence on business and employment
Due to the multitude of these considerations, it is difficult to make accurate projections of the future, although there is a rough outline:
Firstly: Jobs lost. The adoption scenario of AI till 2030 suggests that about 15% of the global workforce (400 million workers) could be removed by automated systems [10].
Secondly: Jobs gained. The number of jobs gained through these are thought to be 133 million globally by 2022 and reach 555-890 million by 2030 suggesting a net gain [11]. However, it is important to note that in many emerging economies with younger populations, there already is an ever-increasing need to provide jobs to people entering the workforce. Furthermore, in developed economies, people are remaining longer in their jobs due to better living conditions, so fewer still are entering the workforce.
First off, millions of workers will have to change their careers within companies, sectors and sometimes even countries due to processes such as brain drain. While occupations in physical structured environments and in data analysis will decline, others providing issues to automation will grow. These include managers, teachers and other professionals in a field, but also construction workers and plumbers etc, who work in unpredictable physical environments [11].
Secondly, workplaces and workflows will change as people work alongside machines. For instance, as self-checkouts have been integrated into shops, cashiers have now moved from scanning goods to helping customers.
Last of all, automation will pressurise average wages jobs in advanced economies like ours. Quite a few middle-wage
jobs are presently automatable such as in manufacturing and accounting. As of this, higher-wage jobs will grow significantly, especially in high-skill and professional fields [11].
To tackle these transitions many economies are starting afresh due to shortages in relevant skills as well as declines in transition support for workers and on-the-job training.
The potential benefits of AI to business and the economy should encourage business leaders to embrace and adopt AI. At the same time, the impending challenges to its adoption and its impact on work cannot be overlooked. Currently, the UK has an interest in embracing AI due to its anticipated help in economic growth and businesses. Other countries should also find a strong need to keep up with global leaders such as the US and China. However, for this broad deployment of AI, solutions in the challenges mentioned must be made to ensure benefits, we must:
• Invest in and continue to innovate in AI research.
• Support the existing digitisation efforts by building upon the foundations of AI.
To tackle the possibly unwanted impacts of AI we must continue our strong economic and productivity growths necessary for a rise in jobs. This is vital to productivity as this creates more businesses encouraging the establishment of new jobs. To address this, we should:
• Edit education systems to focus on STEM skills and in critical thinking to address the change in workplaces for future generations.
• Alter wages and incomes by considering the prestige of a job to encourage more people to explore those fields.
Ishan Visvanath (7C)
On July 21 1969, Neil Armstrong first stepped foot on the moon, by uttering those now illustrious words: “One small step for man, one giant leap for Mankind”, he successfully predicted the status that space travel would one day yield [1]. The race to explore, chart and conquer the ‘beyond’ continues to captivate, and inspire the world, even in the present, which is flooded with a myriad of distractions. However, since the late nineteensixties, space travel has flown further than ever before. NASA have sent two Rovers, Curiosity and Perseverance, all the way to Mars and multiple more spacecrafts and satellites across the galaxy such as the Pioneer 11, and the Mariner 10 to Saturn and Mercury respectively [2][3][4]. This alone proves the potential of space exploration with sufficient funding.
Figure 1. The Apollo 11 Saturn V space vehicle lifts off with Astronauts Neil A. Armstrong, Michael Collins and Edwin E. Aldrin Jr. at 9:32 a.m. EDT July 16, 1969, from Kennedy Space Center’s Launch Complex 39A. [1]
To put it in simple terms, the space Industry is at its absolute peak, and thanks to the development of innovative technology, it is now possible to go even further into the galaxy to explore uncharted territory and uncover new phenomena. This is the subject of recent splurges of government funding which lets our aspirations of the expanse of viable space travel, surpass that of even our wildest dreams [5]
At the very heart of space travel is data [6]. Stemming all the way back to the space race during the peak of the Cold War, data has enabled governments and institutions to further develop ships and shuttles to better equip them for a mission. Vast amounts of data prove crucial for critical work and analysis in mission control, to help supporting systems gather information and come to a verdict of how a particular task is progressing.
Several decades ago, it was the IBM 7090’s mainframe computer which helped to put America into space, but today supercomputers are used for crunching information and propelling space exploration further [7][8]. They are a vital part of I.C.T systems all around the globe which enable ventures in space to go beyond prior anticipation [9].
Taking up lengths of physical space, supercomputing systems are capable of processing colossal amounts of data in mere nanoseconds, ensuring scientists have the information that they need, when they need it [10]. Often, this information is critical and needs to be fed to real-time rockets thousands of miles away [9]. In the International Space Station (ISS), depicted in Figure 2, data transmission occurs very fast despite being 240 miles (400 kilometres) away from Earth [9].
Additionally, artificial intelligence (AI) is already extensively used by those who sit at the forefront of science and technological programs across a multitude of organisations and has made many notable discoveries which have undoubtedly changed the course of history [9]. For instance, a NASA AI program discovered a brand-new planet, over 2545 light years away from earth using merely existing data from space shuttles and telescopes [11]. The hot and rocky dwarf planet named ‘Kepler-90i’ was discovered by machine learning tools which were trained to be able to detect beings beyond the confinements of our solar system. The fact that new planets are being discovered a mere 52 years after the first moon landing speaks volumes about the rate of technology being produced. The biggest benefit of AI is how it can sift through data at a rate so rapid that humans can never match [10]. This increases the chance of making discoveries and helps dispose of unwanted information which can bias further findings. In fact, many tests have confirmed that AI can be instrumental in locating extra-terrestrial life because of how
rovers are able to withstand hostile conditions of the Solar system [2].
As further investment in technology rapidly grows, so too will be our understanding of exploration and potential ventures outside the confinement of our galaxy. Technological adaptation itself has changed in leaps and bounds. Adoption of technology is at not only a faster rate, but also universally embraced a lot sooner. As a result, the time between significant scientific milestones such as the moon landing, the first space station or the Mars Rovers can only decrease thanks to the rapid development and adaptation of technology into Ecosystems. To be frank, if technological adaptation continues at such a rapid rate, it would not be outrageous to think that one day we might be living amongst the starts as opposed to just looking at them. In reality, with sufficient funding, there would not be such things as ‘limitations’ to potential space exploration, especially considering the magnitude of accomplishments in the past.
Jenson Avery (L6H1)
To understand how dye-sensitized solar cells work, first we must consider how a conventional solar cell converts solar energy into an electric current. The solar cell is composed of two sides. Both are made of silicon: a semiconductor with four valence (outer shell) electrons. One side, the p type is doped with boron. Boron has only three valence electrons and therefore requires another to bond with the silicon, this space for an electron is known as a hole. The other side, the n type is doped with phosphorous, that has five valence electrons. Therefore, when phosphorous bonds with silicon there is a free electron from the phosphorous not involved in the bonding [1].
As shown in Figure 1, at the junction between these two layers, the free electrons from the n type move to fill the holes in the p type creating positive ions in the n type and negative ions in the p type. The region in which this happens is called the depletion zone. When electrons fill all the holes in the p-type side, of the depletion zone, they become negative ions and as the electrons were provided by the n-type side, there is a deficit of electrons and hence positive ions are formed. As electrons will be repelled by the negative ions in the p-type side, an internal electric field is created and prevents further transfer of electrons from the n-type to the p-type layer which prevents its further expansion of the depletion zone [1]. In the absence of sunlight, the depletion zone forms by the interaction between some electrons and holes to create
neutral species [2]. The neutral zone formed prevents the two charged regions from complete combination. When a photon of light from the sun collides with a silicon atom in the depletion zone, it excites an electron of that atom, enabling its escape. This creates an electron-hole pair. The free electron will be attracted to the n-type and the hole to the p-type (due to the electrical field previously set up in the depletion zone). The more this happens (i.e., the brighter the sun) the greater the potential difference between the p type (which gets more positive) and the n type (that gets more negative). This potential difference can be used to power a circuit (or charge a battery) when the n type is connected to the p type by a conducting wire.
Figure 1. Schematic representation of a solar cell, showing the n-type and p-type layers, with a close-up view of the depletion zone around the junction between the n-type and p-type layers [1].
Dye-sensitized solar cells (DSSC) were invented by Michael Grätzel and Brian O’Regan in 1991 [3]. The photoactive material in the DSSC is the dye, which produces electricity when sensitised by sunlight. Behaving like chlorophyll in photosynthesis, the dye absorbs the photons, from either sunlight or artificial light, and converts light energy to electrical energy by the excitation of electrons [3]. The excited electrons are injected by the dye to nanocrystalline titanium dioxide, which in turn conducts them to an electrolyte in the cell, which closes the circuit by returning the electrons to the dye [3].
the semiconductor is used solely for charge transport, since a separate photoactive dye-layer act as the source of the photoelectrons. The charges are separated at the surfaces between the dye layer, semiconductor, and electrolyte [4]
As shown in Figure 2, sunlight enters the cell through a transparent electrode (the anode). Some of these photons are absorbed by the dye molecules on the surface of the titanium dioxide, exciting electrons into a higher energy state in the titanium dioxide known as the conduction band. The free electron moves due to the electron concentration gradient to the transparent anode. As the dye molecule has lost an electron, it will have a degradative chemical reaction unless another electron is provided. The iodide electrolyte provides this electron and is later regenerated by an electron from the counter electrode (fig 3), therefore creating a potential difference between the two electrodes [4].
Figure 2. How a DSSC (dye-sensitized solar cells) works [4]
Grätzel and O’Regan thought that the DSSCs would be a significant advancement toward Europe’s 2020 solar energy targets. They have several key advantages over conventional solar cells: they are made from cheaper materials which can be manufactured into semi-flexible, semi-transparent sheets and they supply higher power conversion efficiencies in cloudy/artificially lit conditions [4]. This means that the manufacturing process is easier and thus cheaper than that for silicon cells as these sheets can be mass-produced and the total cost to produce these cells will be lower [4].
In a silicon cell, the silicon acts as the source of photoelectrons and supplies the necessary electric field to separate the electrons and holes to generate an electric current. In DSSC (dye-sensitized solar cells), the bulk of
Dye sensitised solar cells are currently the most efficient thin filmed solar technology available [3], at 11% efficiency, compared to the traditional low-cost commercial silicon panels which run at 12-15%. This is largely because the energy needed to free an electron is slightly more for DSSCs than silicon cells. The current generated by a DSC is 18 mA/cm2, while a traditional silicon-based solar cell delivers about 35mA/cm2 for an average amount of sunlight [4][5].
Dye sensitised solar cells do have some disadvantages: at low temperatures, the liquid electrolyte may freeze and stop power production, leading to possible physical damage [4]. When the liquid expands due to higher temperatures, sealing the panels can be a problem. Another disadvantage is the fact that there is a potential resource cap on the worldwide manufacturing of dyesensitized solar cells, due to competing demands for both platinum and rhodium, since fuel cells, industrial catalysts and catalytic converters exceed their current supply of these precious metals already [6].
Dye-sensitized solar cells’ best use, due to being mechanically robust and lightweight but limited in output and number, make them great for low density applications such as on rooftops, rather than use in large solar farms.
Dye-Sensitised Solar Cells (DSSC)
Rishi Maha (10M2)
Despite the rapid advances in Artificial Intelligence which have revolutionised medical technology in recent years, it is surprising to note how instruments introduced in the nineteenth century are still employed in the daily care of patients. The stethoscope, which was invented in 1816, transformed medical diagnosis. The simple but highly effective instrument was used to enhance the conduction of sounds generated by the heart and lungs [1][2]. The sphygmomanometer (blood pressure monitor) was established in 1881 and is still used in its original form as a manual instrument. Although modern versions include a digital meter, there appears to be a trade-off between accuracy and convenience [3].
Two of the major developments in medical technology in the twentieth century were the dialysis machine and the Magnetic Resonance Imaging (MRI) scanner (Figure 2). Haemodialysis provides a means of purifying the blood of a patient who is suffering from kidney failure [5]. Dialysis machines are used routinely in hospitals as an outpatient facility, where the treatment is initiated and managed by specialised staff made up of nurses and technicians. However, when kidney dialysis is performed at home, the treatment can either be self-initiated or with the assistance of a family member who is a trained helper [5]. Since its introduction and development, during the two decades between 1970 and 1990, MRI has proven to be a powerful imaging technique most prominently used in diagnostic and biomedical research [6]. Unlike CT and PET scans, MRI does not involve the use of X-rays or ionising radiation. Instead, the scanners employ magnetic fields and radio waves to generate images of the various organs of the body.
Although the concept of modern robotic surgery began in the early twentieth century, the first recorded robot assisted surgery occurred during the decade of 1980-1989 [9]. In the year 2000, the Da Vinci surgical robot was approved and has since dominated the market as the most prevalent device in the field [8][9]. Robotic surgery is designed to assist the surgeon and is often used to make complex procedures easier to perform. It permits doctors to perform surgery with more control, flexibility and precision in comparison to conventional methods. Being minimally invasive, it reduces patients’ recovery time and lessens scars and blood loss. However, technical robotic surgery may seem, the robotic arm is still controlled by an actual surgeon with a computer. Once general anaesthesia is administered to the patient, small surgical tools are attached to the arm of the robot and directed towards the human. At present, there are a wide range of surgical procedures that involve the assistance of a robot. These include coronary artery surgery, kidney transplant and joint replacement surgery [9].
Looking to the future, the world’s smallest surgical robot, Versius (Figure 3), is predicted to transform keyhole surgery [8]. If approved for clinical use, it could be employed by the NHS to perform tens or even hundreds of surgical procedures per year. Another technology that is becoming increasingly popular in medicine, with development in the field opening opportunities to revolutionise healthcare, is 3D printing. It produces physical objects from a digital file by adding layers of a material to build a single structure [10]. First developed in the 1980s 3D printing, also known as Additive Manufacturing, involves printing successive layers of an appropriate material to create a new version of the subject from information received from a digital model or blueprint. The forecast is for 3D printing in the medical field to be worth $3.5 billion by 2025, compared to its value in 2016 which was a mere $713 million [10]. The uses of 3D printing in medicine include creating biological tissues and organoids, surgical tools, patient-specific surgical
models and custom-made prosthetics [10]. The advanced technology of bioprinting of tissues and organoids involves the use of a computer guided pipette to add layers of living cells, one on top of another, to create artificial but living tissue in the laboratory.
Current day technology has revolutionised our everyday lives. From toasters to computers, it is something that we have relied on for years, both inside and outside our homes. In the future it is inevitable that technology will take over aspects of the healthcare sector, as new advances could improve the efficiency of manufacturing, procedures and other tasks. Whilst recent developments have made great strides, the question of what the future holds is intriguing.
In conclusion, it is fair to say that technology has benefited the healthcare system. Its development has already assisted the medical world and continues to do so. Whilst costs can be diminished, production can be elevated, improving the economy in the long run. The future looks likely to bring exciting prospects in technological medicine, perhaps with surgery becoming more and more mechanical. Healthcare as we know it today could be much slicker, more personalised and efficient, ultimately proving technology will have a positive impact on the medical world.
In 1822, Joseph Fourier, a French mathematician, published his Analytical Theory of Heat [1], which mathematically formulated heat flow as a partial differential equation (PDE) of a multivariable temperature function u(x, t) of an infinitely thin metal rod at position x and time t:
as a superposition of sines and cosines, solving supposedly difficult partial differential equations would be much easier and more efficient. In addition, if solved numerically, the accuracy of the solution is likely to be greater.
Without dwelling much on the mathematical jargon, this equation essentially states that the rate of change of temperature over time is proportional to the rate of change of the derivative of temperature depending on the position. The constant of proportionality α is a coefficient that takes into account thermal conductivity, the specific heat, and the density of the material [2]. PDE’s must be solved first, before they can be applied to engineering and the understanding of other systems. Fourier set out to solve this, but in a rather intriguing fashion: he noticed the linearity of sinusoidal waves, meaning sums of sinusoidal waves are just the sums of the amplitudes of each wave [3]. Furthermore, since the heat equation is linear, the solutions can be written as sums of solutions of individual components. Combining these two ideas, we can set the initial condition, u(x,0) = sin nx, or any other trigonometric function, which makes it very easy to solve, and write any function as a sum or a superposition of sines and cosines. This means that all solutions can be written as a sum or superposition of solutions to individual trigonometric functions in the initial condition. The reason this was so brilliant was because if every single function could be written
Figure 1 Fourier Analysis [10]
Fourier Series and the Fourier Transform: Fourier used an infinite sum of sine and cosine functions, each with its own coefficient, and this could be used to represent any function, including discontinuous ones:
He even had general formulae for these coefficients in terms of integrals: [4] [4]
Where f(x) was the function being represented as this sum. These were named Fourier Series. He extended this idea of Fourier Series to the entire number and called it the Fourier Transform. The maths of how to get to this integral is unimportant, but it felt apt to mention this beautiful formula:
[5]
One of the most useful techniques in all of signal processing is data compression. Reducing the size of data can be extremely important in storing quantities of data of significant magnitude, especially in largescale servers. Compressing data is key to achieving this, and the Fourier Transform is one of the main tools used to carry out compression [6].
Let us consider one of the most commonly seen, but also likely the most ignored, acronyms: JPEG. The Joint Photographic Experts Group (JPEG) is an indication that a type of compression has been used [7]. It combines five different compression steps. The first step converts the colour and brightness information, which starts out as three different intensities for red, green, and blue, into three mathematical representations. One (luminance) represents the overall brightness and the other two (chrominance) are the differences between the luminance and the amount of blue and red light, respectively [8].
The second step consists of coarsening the chrominance data or reducing it to a smaller range of numerical values [9]. This step alone halves the amount of data, though it does no perceptible harm because the human visual system is much less sensitive to colour differences than the camera is.
The third step is where the Fourier Transform comes in. A variant of the Fourier Transform is used, which does not use a signal that changes over time, but a pattern in twodimensional space, though the mathematics is virtually identical. This space is an 8 × 8 sub-block of pixels from the image. For simplicity, consider just the luminance component, although the same idea applies for the chrominance. For each of the 64 pixels, only one number is stored: it’s luminance value [9]. The discrete cosine transform, which is a special case of the Fourier Transform, decomposes the image into a superposition of standard ‘striped’ images. In half of them, the stripes run horizontally, and vertically in the other half. They are spaced at different intervals like the various harmonics in the usual Fourier Transform, and their greyscale values are a close approximation to a cosine curve. In coordinates on the block, they are discrete versions of cos mx cos ny for various integers m and n
This step paves the way to step 4: a second exploitation of the deficiencies of human vision. We are more sensitive to variations in brightness and colour over large regions than to closely spaced variations. So, the patterns in the figure can be recorded less accurately as the interval between stripes gets smaller. Finally, the last step is to uses a ‘Huffman Code’ [9], but that is irrelevant to this discussion.
Although the average human eye is very good at picking up fine details of brightness, it is less sensitive to fine spatial changes of colour [8]. So, your camera can take about ten times as many pictures on a memory card, before anyone other than an expert might notice; and that is the immense power of Fourier Transforms in the technological world of data compression.
One of the biggest inventions that has been introduced to society is Artificial Intelligence (AI), an invention said to shape our future on Earth. However, how would medicine and the health care system be affected if every medical doctor was replaced by a robot? Many hospitals have been considering this idea, as shown by the impact that COVID-19 restrictions have had on the number of staff vaccinating, treating COVID-19 patients, and specializing in specific fields of medicine [1]. The current status of AI in healthcare is that it enhances
what doctors do by performing certain tasks at a much faster pace. However, future estimates are that around 80% of what medical practitioners do will be replaced by AI [2].
Disease in the medical world can be quite unpredictable and hard to identify, but unlike a human doctor, a robot doesn’t get tired and so it can monitor a patient 24/7. Using imaging and algorithms built into them to detect certain diseases would result in faster diagnosis, as illnesses that may not match the patient’s symptoms can be ruled out instantly [2].
we see a future where robots take over the jobs of doctors?
Modern AI excels at anomaly detection as it can see detail that is invisible to the human eye. A relatively recent study has shown that deep learning models could detect tumours on an ultrasound image, with the same level of accuracy as a radiologist. This is quite remarkable considering the fact that it took seven minutes for researchers to train their models, while it takes several years for doctors to perfect their diagnostic skills [2]. Nevertheless, the final say on the patient’s illness, is mainly based on how the patient is feeling, something a robot cannot see. The reason a doctor would not base it off the symptoms of a patient alone is because many illnesses can cause similar symptoms, but robots would still help narrow down what the patient may be suffering from.
that often require a range of different extremely intricate hand movements, whilst maintaining tremor reduction. The three or four arms of the robot are controlled by a trained surgeon sitting in a console when the robot performs the surgery [4][5].
A medical specialty that could benefit from robots is Pathology. A repetitive and tedious task such as cell counting could be done by AI, liberating the pathologist to perform more complex tasks which require specialist knowledge [6]. For example, currently lung adenocarcinoma (a type of cancer) requires a pathologist to visually examine the microscopic slides in order to identify the tumour patterns and subtypes. However, using recent advances in machine learning, a deep neural network seems capable of classifying different types of this form of cancer, from information obtained from a histopathology slide. The accuracy level of the AI was found to be comparable with that of the trained pathologists [6].
With the constant need, of most employees, for higher pay and better working conditions a hospital without doctors would be ideal for governments. A robot will not demand a pay rise or suffer from low morale due to longer working hours. It is also a fact that computers are significantly more advanced and able to process far more information and at a faster rate than a human. However, at present, the type of robot that is in use is the surgical robot which is remote-controlled by a surgeon; the robot does not control the scalpel but performs the surgery [3]. The Da Vinci surgical robot (Figure 1) is currently used worldwide for minimally invasive operations
It is undoubtedly true that technology has advanced greatly and is helping doctors in fields such as surgery, diagnosis and pathology. However, it should always be the case that AI should be augmenting a physician’s work rather than replacing the person doing the job. Medical practice is often described as ‘the art of medicine’ as despite the science and technology involved, especially in recent times, there is a humanistic approach to the profession [4]. Doctors must consider numerous clinical variables and social circumstances which are unique to each patient, when deciding on a suitable treatment. A robot could never establish the unique doctorpatient relationship [4].
Overall, I think that replacing every doctor with a robot would be a bad idea. Doctors do not just treat diseases; they also look after patients and help them to feel better mentally as well as physically. It would be impossible for a robot to convey this sort of compassion genuinely. No matter how much money we may potentially save by doing this, you can’t put a price on compassion.
Can we see a future where robots take over the jobs of doctors?
NFTs, non-fungible tokens, are digital tokens stored on the blockchain that can be used to show ownership of unique items digitally [1]. They are non-interchangeable and unique, so nobody can copy or delete one [2]. Few people had heard of NFTs in 2020, but in 2021 they became very popular, with the first NFT artwork offered at a major auction house selling for $69 million in March 2021 (Figure 1)[1]. Many game developers such as Ubisoft and EA have plans to include NFTs in their games (although met with much backlash), and GameStop is launching its own NFT marketplace, showcasing the rise in their popularity [3][4].
Given that it is technically possible for anything to be a NFT, they would form the basis of ownership in an eventual metaverse that companies are planning where they could form the groundwork of how users assert ownership over items such as land in the virtual space [5]. Since each NFT is secured by a cryptographic key that cannot be copied or deleted, it enables robust, decentralised verification, making it necessary for a metaverse to succeed. [2] NFTs have huge potential to be very important in the future and are a technology that is already making impacts. As unpredictable as cryptocurrencies are, blockchains and NFTs have potential for much wider applications in the world, beyond just digital
art. But are they sustainable? There has been a lot of concern over the enormous amounts of energy needed for cryptocurrency networks and the energy-intensive process of mining them. Bitcoin is estimated to consume 123 terawatt-hours (TWh) annually, more than the country of Argentina [7][8]. Ethereum, one of the main blockchains that NFTs run on, is estimated to consume 106 TWh per year, comparable to Kazakhstan [9][10]. Although different estimates provide quite different values, what can definitely be said is that these cryptocurrencies, along with countless others that use a Proof of Work system, do consume a large amount of energy. They are unsustainable even in their current state, and they would consume much more electricity if hypothetically most people started
to carry out transactions using cryptocurrencies. There is a debate around it: how much energy consumed would be viable for a financial system such as Bitcoin. Some would argue that all energy consumed by it is wasted: it is a slow system that does not provide many benefits. Conversely it is revolutionary and its decentralised nature provides freedom: that surely is a good use of energy?
A Proof of Work (PoW) system is one where the miners compete to find a correct hash for a block according to the difficulty target set by the network [11]. The miners perform millions or billions, even trillions of hashes per second to find the correct one first, and to add a new block to the blockchain, containing information of transactions that have occurred [12][13]. The miner gets a reward for the
Figure 2: The Bored Ape collection is one of the most popular collections of NFTs [6]
block. In a PoW system, the network is secured against malicious hackers because of the vast amounts of computational power going into the network [11]. A hacker would theoretically need to control 51% of the total computational power to be able to keep adding malicious blocks that have fake transactions, which is quite impractical for a cryptocurrency as big as Bitcoin or Ethereum [14]. The problem with a PoW system is that it requires a lot of energy to be secure, and it is not good for the environment because of the large amounts of energy used.
Ethereum (ETH), which a lot of NFTs operate on, is in the process of moving to a Proof of Stake (PoS) system, where validators stake their own ETH and get rewards for performing actions that benefit the network, such as checking the work of other validators or processing transactions into new blocks [15]. As a validator, you can lose your ETH for carrying out malicious actions, and this is how the network is secured. The hardware requirements for being a validator are much lower than being a miner because you do not need to perform the millions of hashes per second, competing with others. It is much riskier for a hacker to carry out an attack because they risk losing all the ETH they staked, rather than just the cost of electricity they consumed.
The Beacon Chain, a separate chain made by Ethereum to test the PoS system, was launched in December 2020, and according to the data gathered by this, Ethereum estimates that moving to a PoS system will reduce its energy usage by “at least 99.95%” [16]. This would mean that Ethereum would go from consuming the energy of a mediumsized country, to consuming the energy of a small town. Apart from reducing the energy usage, switching to PoS also promises increased network capacity and transaction speed. “The Merge”, when the Beacon Chain will merge with the main chain to complete the switch to what is called Ethereum 2.0 is expected to go live in the near future.
Although the numbers from the Beacon Chain look promising, it is still very early to predict how accurately this will affect the energy consumption. The signs point towards it overcoming what has been a big concern for most cryptocurrencies. In the current state, NFTs consume vast amounts of energy, and have a large carbon footprint, but once Ethereum 2.0 is launched, their energy usage, and with it their carbon footprint, could reduce, making them sustainable and that is what many digital artists and other people hope.
CRISPR-Cas9 is one of many gene-editing tools. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is favoured due to its high degree of accuracy and flexibility [1][2]. It is the first gene-editing technology that enables genetic engineering to be done at a much lower cost. CRISPR also allows the introduction and removal of more than one gene at a time, a feature not present in previous technologies. This reduces the editing time from years to weeks. In addition, as CRISPR technology is not species-specific, it can be used on organisms previously resistant to genetic engineering [3][4].
CRISPR is already being used for a large range of applications. For example, in agriculture CRISPR can be vital in helping to design new grains, roots, and fruits [4][6]. In terms of human health, it can be used to develop innovative cures for rare genetic diseases such as Huntingdon’s and haemophilia. CRISPR is being used to breed transgenic animals which can subsequently produce organs for transplantation into human patients. It is also being considered for gene therapy, which involves inserting normal genes into cells of patients who suffer from cystic fibrosis [4].
Figure 1. A representation of Cas9 cutting the helix-shaped double strand of DNA
Figure 2. CRISPR redacted foods from 2014 – 2018 [6]
The biotechnology of CRISPR originated from a natural defence mechanism used by bacteria, which involves cutting a section of DNA from an invading virus and recording it as their own. The DNA of the virus is cut at a specific location and at either end of the cleaved section a repeating sequence of CRISPR is attached. The storing of viral DNA by bacteria enables them to “remember” it and if subsequently attacked by a similar type of virus, the bacteria can destroy the invading pathogen by using a specific CRISPR-associated protein, number 9 (Cas9), to cut the viral DNA and hence destroy the invader. [7]
Modern biotechnology uses the same CRISPR/Cas9 system to identify and cut a specific sequence of DNA. Ribonucleic acid (RNA) is a biological macromolecule which is involved in the coding, decoding, regulation and expression of genes. As RNA has the ability to read specific genetic information in DNA, it enters the nucleus and targets the DNA sequence that requires editing. The desired site of DNA cleavage is reached by creating a matching RNA sequence that will guide the Cas9 protein to the target DNA sequence. The Cas9 is then able to lock onto the DNA double strand, unzip it and cleave both strands of the DNA at the required position.
Once cleaved by CRISPR/Cas9, the DNA can be edited using other techniques which are able to add, delete or modify the DNA [5][7]. Prime editing is a system that builds upon this knowledge of CRISPR/Cas9 in order to directly substitute one segment of DNA with another, a technique known as base editing. [7]
Figure 4. The future of CRISPR [7]
significant damage to the genetic make-up of an individual. Whilst some cells can recover after DNA alterations, others are unable to do so [7].
There are also ethical concerns, which raise the question of whether CRISPR might be used to enhance human characteristics, such as intelligence and aesthetic beauty. In addition, in most cases, CRISPR will affect the germline of a person and all their offspring will be affected by this. [7] These future offspring have not given consent for these changes to their germline and this sparks a whole host of ethical questions. There are also socioeconomic disadvantages of CRISPR technology. Although CRISPRCas9 is much cheaper than its predecessors, it is still highly expensive. Thus, gene editing seems as if it will only be available to those with a high enough disposable income to pay for it. This service, if ever available, will hugely widen the inequalities between the wealthy and economically disadvantaged in society. In addition, many governments across the world are struggling with how to implement legislation in order to regulate CRISPR and other gene editing technologies.
Finally, an important question that arises when discussing CRISPR-Cas9 technology is whether we are playing the role of God. On one hand, some suggest that editing the human genome is tampering with God’s creation. The argument against this is that the development of technology has been allowed by God and hence we cannot be playing his role as this has been allowed to happen.
So, where do we draw the line? When is it right to stop when it comes to gene editing? There are thousands of diseases that affect mankind, and whilst CRISPR may be used to cure diseases such as HIV, it may also be used to cure minor imperfections that do not significantly impact a human in day-to-day life. [8][9]
In terms of safety, there is a distinct possibility that CRISPR could target an unintended sequence of DNA, resulting in
CRISPR-Cas9 has many benefits which outweigh the disadvantages and risks. Overtime, we will be able to learn more about the human genome, and if this technology is utilised to its full potential, we can eliminate many harmful diseases and the human race may live for longer.
Biotechnology:an introduction to CRISPR-Cas9
Figure 3. CRISPR/CAS9 systems allow scientists to make targeted changes to an organism’s DNA [7]
What are the many challenges and bioethical issues with human gene editing?
Benzene plays a central role in a vast array of industrial processes and products, from manufacturing chemicals to pharmaceutical drugs. However, after it was first identified nearly 200 years ago, an understanding of its structure eluded some of the world’s greatest scientific minds.
Benzene was first isolated by Michael Faraday in 1825 from lamp oil residue [1]. He named the substance “bicarburet of hydrogen” and determined its empirical (CH) and molecular (C6H6) formula. He did this by first purifying the residue by fractional distillation and recrystallisation. Following this he
burnt the resulting substance and measured the amounts of carbon dioxide and water evolved from its combustion to determine its chemical formula [2].
There were multiple proposals for the structure of benzene. Ladenburg’s prismane placed the six carbon atoms on the vertices of a triangular prism. Armstrong’s centroid structure proposed that six of the bonds, or “affinities”, act towards a centre [3]. Dewar suggested several possible structures [5] (of which it was later discovered that one was a real isomer of benzene [4]) but ultimately, he was in agreement with German chemist August Kekulé’s structure.
How did X-ray diffraction help to confirm the structure of Benzene?
Figure 1. Ladenburg’s prismane [7]
Figure 2. Armstrong’s ‘centroid’ [7]
Figure 3. Dewar structure [1]
Although Kekulé’s structure was accepted by many chemists, even into the early 1900s textbooks continued to present a range of possible structures [8] indicating it had not been conclusively proven. Many wondered how such a highly unsaturated compound, with three double bonds, could be so stable – 36 kcal/mole more stable than would be expected for Kekulé’s cyclohexatriene [9].
Kekulé’s structure is the closest to the current accepted structure of benzene, consisting of a hexagonal ring of carbon atoms with alternating single and double bonds. He later amended his theory, proposing that the single and double bonds switch places constantly in an equilibrium. The story goes that a vision came to Kekulé while he was sitting on the top of a London omnibus in 1855 [6]: “One of the snakes had seized hold of its own tail. The form whirled mockingly before my eyes” [7].
It took over a century for the structure of benzene to be confirmed, and it was achieved through X-ray crystallography. This technique is akin to shining a light at an object and, through observation of the shadow it casts, deducing its shape. X rays are fired at a crystal sample from an X-ray tube [10]. As the waves travel through the crystalline structure, they diffract and interfere (combine) with one another. At some points (where the waves are in phase) constructive interference can occur. This produces a signal of increased amplitude, or, as it is commonly called, a reflection. The opposite can happen at places where the waves are out of phase. Here the waves can cancel each other out [11]. Due to these interactions, a regular diffraction pattern can be observed on the other side of the crystal. The sample is rotated, and from a combination of many of these patterns the 3D crystalline structure of the sample, including bond lengths, can be extrapolated. This determination process involves very complex mathematical equations, including Fourier transformations, today solved computationally [12].
Figure 4. Kekulé’s explanation of Benzene [7]
A relatively simple equation to help conceptualise this interference is Bragg’s Law: nλ = 2d sinθ [12]. The equation can be derived geometrically from the the diagram in Figure 6.
How did X-ray diffraction help to confirm the structure of Benzene?
Figure 6. Figure A1. Schematic representation of Bragg’s law conditions. [19]
If the path difference (2d sin θ) of the two waves, initially in phase, is equal to an integer number of wavelengths, maximum constructive interference will occur (this will be the centre of reflections). As the observer knows the wavelength of the X-rays, and at what angles constructive interference will occur (from observation of the diffraction pattern) they can work out the distance between various planes of the crystal structure.
It was a pioneering British scientist, Dame Kathleen Lonsdale, who applied the technology of X-ray crystallography to the unresolved problem of benzene. In 1928, she investigated the crystal of hexamethylbenzene, using equipment she assembled from scratch [13]. After performing calculations involving more than 30 parameters by hand [13], she published her results. Lonsdale conclusively determined that benzene was a flat, hexagonal molecule, with a constant distance of 1.42-1.48 A between each carbon atom [14]. This offered a confirmation, roughly, of Kekulé’s structure. However, in 1931, the American chemist Linus Pauling provided a slight modification [15]. His “resonance” theory showed that instead of Kekulé’s two alternating cyclohexatriene structures, each carbon atom’s p orbital combined into a ring, containing delocalised electrons [9]. This theory accounted for benzene’s unexpected stability.
The understanding of benzene opened up a whole new field of chemistry called aromatic chemistry, initially coined in reference to the chemicals’ distinctive smells [17]. Benzene derivatives are used in a great variety of products, for example aspirin and ibuprofen [1] and in the production of plastics, resins, dyes and adhesives [16].
Figure 7. Delocalised electrons above and below the plane of the Benzene ring [9]
Figure 8. Chemical Structures of Asprin and Ibuprofen. [20]
Figure 9. Photograph 51 (X-ray image of DNA) [21] X-ray diffraction is an analytical technique that has given us a deeper understanding of the fundamental structure of the world we live in. After it revealed the structure of benzene, it was used to help determine the double helix structure of our DNA [18]. This beautiful and complex technique is still being used to satisfy our innate curiosities of the intangible nanoworld of molecules and atoms.
How did X-ray diffraction help to confirm the structure of Benzene?
Whilst there appears to be many definitions, Nanotechnology could be described as the manipulation of materials on an atomic or molecular scale to build microscopic devices and structures [1]. These structures have dimensions in the order of nanometres (1x10-9m or 1 billionth of a metre) and are among the smallest entities that can be made. To help contextualise the size of a nanometre, the average diameter of a human hair is 80,000 nm [2].
Although nanotechnology is not widely understood by the general public, it is used in everyday products around us. For example, sunscreen consists of two common nanoparticles called titanium dioxide and zinc oxide which are highly effective at blocking UV and feel light on the skin [3]. Nano particles of silica are also used in textiles, in order, to create liquid repelling fabrics. Either by spraying the fabric or incorporating into the material, these nanoparticles can create a waterproof or even stainproof coating. Other areas where nanotechnology is used include the manufacture of sport equipment, shoes, cosmetics, agriculture, medicine
and most relevant to this article, aerospace [4]. Using nanotechnology, we can produce a whole new set of engineering marvels, whether they explore the universe or reshape the world around us. Moving into the nanoscale enables us to work in the quantum domain where classical physics starts to break down [3].
Space travel has a number of complications. One major drawback is its cost. Launching paraphernalia into space is ludicrously expensive: it costs around $10,000 (£6,300) to lift every 0.45kg (1lb) of equipment into orbit [5]. Space exploration is a large business and therefore, in order to become sustainable and successful, it needs to be profitable [6]. The space sector also has quite a significant impact on the economy of countries and unsurprisingly profit is a big concern. Additionally, leading organisations, such as NASA, have to work exceedingly hard to budget out their annual costs with the little funding provided by governments [7]. With companies facing these adverse circumstances, the speed of advancement is, unfortunately, limited.
Nanotechnology the key to the future of space exploration?
Furthermore, space exploration is not an eco-friendly activity. Rockets require a large amount of fuel to propel themselves into space. NASA’s Saturn V burnt 4,578,00 lbs of fuel in around 168 seconds [8][9]. In addition to emitting around 336 tonnes of CO2 by burning 112 tonnes of refined kerosene, SpaceX’s Falcon 9 emits other pollutants, which include chlorine, particles of soot and aluminium oxide that destroy the ozone layer [10].
In addition to the large quantities of fuel, rockets require just to leave the atmosphere, spacecrafts are generally not recycled [11]. As spacecraft are designed to burn-up in the atmosphere after a single flight, until now no non-SpaceX spacecraft has visited the International Space Station (ISS) and returned [11]. This means that companies must spend more money on new materials for future spacecraft.
Nanotechnology is infinitesimal with nanoparticles being microscopic; this allows for very light, extremely intricate structures. This quality makes it suitable for wide
implementation throughout the aerospace industry, where weight is extremely important. Nanotechnology could potentially hold the key to making space flight more practical and sustainable [5].
Being lightweight, nanotechnology could significantly reduce the amount of fuel required for the propulsion of spacecraft. Not only does this reduce the carbon footprint of space travel but it also imperatively lowers the cost of propelling spacecraft into orbit [5]. With 95% of a space shuttle’s weight at take-off being fuel, it costs around $20,000 per kilogram to send a payload into space [12]. Incorporating nanotechnology could reduce the weight of spacecraft and payloads, making it much cheaper to send paraphernalia into space. This could be done, for example, by employing materials made from carbon nanotubes [1]. Not only do they reduce the weight of spaceships but they could retain or even increase the structural strength of spaceships [1]. Carbon nanotubes could also potentially be used to develop a space elevator: ‘the Holy Grail of space exploration’[1][13]. Building a space elevator could lower costs of sending equipment into space to as little as $200 per kilogram [12].
Is Nanotechnology the key to the future of space exploration?
Figure 2. Possible approaches for boosting the performance and lifespan of spacecraft electric propulsion (EP) systems by application of nanoscaled materials, for the most determined “bottlenecks” to be possibly resolved with the use of the next-generation nanomaterials and metamaterial systems [15].
Scientists have been working on alternative eco-friendly fuel sources for a few decades now. One of the more developed breakthroughs is green hydrogen. The application of nanotechnology has increased the feasibility of substituting fossil fuels with this promising form of energy [14]. Green hydrogen is produced through the electrolysis process. Water is separated into oxygen and hydrogen in an electrolyser by an electric current generated using renewable energy sources (predominantly solar energy) [14]. Since electrolysers demand high amounts of energy, a team of researchers from the Institut national de la recherche scientifique (INRS) at the University of Quebec and Institute of Chemistry and Processes for Energy, Environment and Health at the CNRS-University of Strasbourg (ICPEES) developed a complex sunlightphotosensitive-nanostructured electrode that undergoes photocatalysis to split water molecules under the sun’s light [14]. The electrode was optimised by modifying titanium dioxide (TiO2) to absorb up to 50% of the light emitted from the Sun [14]. The nano-structuring conducted within the TiO2 was similar to that of a beehive and, consequently, enlarged the operational surface area of the electrode by a factor of more than 100,000 [14]. Developments in green hydrogen
technology should influence the space sector to develop an analogous eco-friendly fuel, or green hydrogen itself, to mitigate their carbon footprint.
The performance of spaceships, spacesuits and equipment used to explore planets and moons could be improved by nanotechnology. Including layers of bio-nano robots in spacesuits could prevent fatal injuries with the outer layer of bio-nano robots responding to damages to the spacesuit i.e. sealing up punctures [1]. Nanotechnology is already used in modern spacecraft today. An example of nanotechnology being used in spacecraft are nanosensors; they are used to search large areas of planets for trace chemicals [1]. NASA employ nanosensors elsewhere too. They have been developed for the ISS and other spacecraft and can monitor the levels of toxins [5].
Nanotechnology will push the boundaries in space exploration and many other industries too. In the future it should become more easily accessible to countries all over the world, making space travel a viable activity. We live in an era where nanotechnology has great potential to transform the way we think about space travel. As a rapidly emerging new field of science, it certainly promises to revolutionise space exploration.
Is Nanotechnology the key to the future of space exploration?
Smart cities are urban areas containing and applying modern and advanced technology. These technological advancements are used to improve ease of living, life and working environments and are embedded into government systems such as power grids and transport [1].
However, the definition of a smart city is becoming more vague and more imprecise as the temptation of instilling technology into every aspect of our cities grows. This begs the question: what really is a smart city?
One potential definition is that a smart city uses information and communication technologies to:
• improve efficiency of physical infrastructure via Artificial Intelligence (AI) and data analytics
• efficiently and effectively allow authorities to improve the collective intelligence of the city in a process known as e-governance
• improve the overall intelligence of the city, therefore increasing innovation throughout the whole city [2].
One possible technology to be used by smart cities is the Internet of Things, a global network which collects and shares information about people and cities to optimise features [3]. Today, it is most commonly used in manufacturing, transportation and utility organisations, but it has the potential to be used in many more areas [4].
One important goal of smart cities is helping to reduce climate change. This can be achieved using renewable energy sources such as wind or water-power. Over 100 cities (smart or otherwise) worldwide now report that over 70% of their power is from hydropower, geothermal, solar and wind power [5]. This shows that building blocks already exist for a more sustainable and less damaging future and that helping reduce or even halt climate change via smart cities is a future possibility.
While it may seem like smart cities belong only in the future, many examples already exist. A number of major world cities such as Madrid, London, Milan, New York and Amsterdam are experimenting with these technologies. For example, the Madrid Intelligence Project (MiNT) [6] was designed to create a city centred more around the people. The project includes initiatives such as using smart grid technology to analyse data on traffic congestion and the timing of street lights [6]. Other cities are committed to converting themselves to smart cities, such as Milton Keynes, which created the MK:Smart initiative in 1967 to expand and improve the city and its standard of living, whilst also meeting environmental regulations [7]. It now has the second highest concentration of digital and tech, small and medium enterprises, of any UK city outside London [8].
Whether it is using energy more efficiently or improving accessibility and the way of living, it is becoming increasingly clear that the concept of smart cities must be applied to be the future of human civilisation.
Smart cities are not necessarily without potential downsides. Citizens could be unhappy with not being able to shape their community and living area. Implementing the best technology at the time could lead to short-sightedness, in that it could be thought that there would be no need to continue to improve, hence making the idea of ‘smart’ cities redundant after a short time span [1].
Moreover, policies surrounding using
personal data could eradicate or damage personal privacy, which is likely to be a concern for many citizens. Smart cities may also increase the gap between socio-economic groups, as technological developments may be concentrated in areas of high median income [9]. This would exacerbate already high levels of income segregation that exists in urban areas, as wealthier populations will live in technologically advanced neighbourhoods while those with lower incomes are left behind in zones with poor infrastructure [9].
There is also a risk that a smart city design might be more focused on optimising the technology rather than the citizens’ lives.
With the majority of these potential issues, the problems stem from the design and management of the cities. Therefore, keeping people in mind needs to be at the forefront of the design and implementation of smart cities.
In conclusion, the concept of smart cities is clearly a very ambitious idea and one which, if implemented correctly, will be able to greatly benefit the human population. It will be necessary for the people who design and manage the world’s smart cities to understand potential downsides and consider ways to overcome or minimise them. If this is possible then we could truly see the future of industrialisation and technological advancements implemented in the best way possible.
Smart cities: a smart choice?
Since the 1960’s, the power of our computers has kept growing exponentially, allowing them to get smaller and more powerful at the same time. We started with a computer that was the size of a room, and then we cut it down to our mobile phones which we value so dearly today. Computer parts are approaching the size of an atom, but it is very soon about to reach its physical limits. We now enter quantum computing, the next big leap of mankind. A computer is made up of very simple components, doing very simple functions [1]. For example, it can represent data,
have the means of processing information and possess control mechanisms. This has all been made possible due to the immense capacity of the human brain, which invented the computer chip. It is, therefore, hardly surprising that a poll carried out by CNN in 2004 revealed that the silicon chip was considered the most significant invention in fifty years. Created in 1961 by two American electrical engineers, Jack Kilby and Robert Noyce, the silicon chip has revolutionised miniaturised technology and has made modern computing and computers possible [1]
2. How a logic gate adds 2 and 3 to give 5 [2]
A computer chip contains modules and logic gates which contain transistors, the smallest and simplest component of a chip [2]. Otherwise known as a glorified, tiny switch. This switch processes information in Bits, which can hold the value of either 0 or 1. It creates ‘logic gates’ which means these transistors can use these bits to do addition, subtraction and multiplication, which means it is possible to do most calculations in the free universe [2]. As all of the three functions are simpler than primary school mathematics, a computer can be thought of as a group of seven-year-old pupils solving basic maths problems and combining their efforts towards a common output. Therefore, a group large enough could compute and solve problems from the depths of astrophysics and rocket science to the functions and
codes of application and interface of digital devices. In very simple terms, this is computing in a nutshell.
As with conventional computers, quantum computers perform quantum computations. In quantum computing the collective properties of quantum states such as superposition, interference and entanglement are harnessed, in order, to perform calculations [3]. Conventional computers store information in Bits, the smallest unit of information on a computer. However, quantum computers use qubits, which can also be set to one of two values. A qubit can be any twolevel quantum system, such as a spin or a single photon, 0 and 1 are these system’s potential states. In the quantum universe, a qubit doesn’t have to be in just one of these states but can be in any proportions of both states at once.
Figure 3. Difference between bit and qubit [4]
This is termed Superposition. In superposition, the quantum particles, which are in a combination of all possible states, fluctuate until they are measured. Figure 3 illustrates the difference between a bit and qubit [4].
When quantum particles correlate their measurement results with each other they are said to be entangled. In entanglement they form a single system and influence each other, which means that measurements from one qubit can be used to draw conclusions about others. The addition and entanglement of qubits enables quantum computers to increase their computational capacity exponentially [4]. Finally, in quantum interference the qubit in a superposition state can influence the probability of it collapsing to one of the two binary states.
Quantum computing which was first introduced in the 1980s was found to perform operations at speeds exponentially higher than conventional computers, with reduced energy consumption [5]. It is believed that quantum computing will be of significant benefit to fields such as finance, the military and intelligence, drug discovery, aerospace and machine learning [5].
These computers can be used for database-searching, which could change the world of Data and Security whilst simulations of the Quantum Universe can also be run to affirm this leap of mankind.
Formula 1 is the pinnacle of motorsport, an extreme competition won or lost by the finest of margins, in a matter of milliseconds. Although drivers get most of the media attention during a season, Formula 1 is a team sport. Without the engineers designing the chassis and engine of the car to make it the most aerodynamic and powerful, the team would be unable to compete at the highest standards, regardless of what the driver would do once on the grid. The design of each major component is bound by the rules that the Fédération Internationale de l’Automobile (FIA) dictate, hence shaping the engineering choices made by a team for each season. Therefore, the regulations have much significance on each team’s technology and the end product that competes against the fastest cars in the world. Formula 1 is a sport in constant evolution and therefore, the regulations are of paramount importance, with changes to regulations moulding the face of the motorsport for years to come. All the regulations imposed, and the subsequent alterations made are monitored electronically during the race by the FIA.
The aim of FIA is to regulate changes, in order, to “promote better racing”. The FIA made three main changes to the regulations for the 2022 Formula 1 season related to the design of the car [1]. Firstly, they have brought about the introduction of 18-inch tyres with wheel winglets as opposed to 13-inch tyres, which have been used for decades. The FIA have justified these changes as they have said that the larger tyres have a more aesthetic appearance, whilst also having direct improvement for the racing. For example, the larger tyres are able to improve the handling of the car, as the contact patch of the car increases, meaning the tyre is able to generate greater grip as the amount of traction increases. The contact patch is the portion of the car’s tyre that is in actual contact with the road and traction is the maximum amount of grip that can be generated between the car’s tyres and the circuit without slipping. The improvements introduced enables the driver to manoeuvre the car better and push it to its highest limits.
Figure 1. 13 inch vs 18 inch wheels [2]
A second significant change that the FIA have introduced with their changes to the regulations is a simplified front-wing and a new rear wing with a rolled tip. The wings are used to produce a downforce equal to several times the weight of the car, so that the car gets good grip and does not skid [3]. Previously, the rear wings had hard edges and plates, leaving a path of dirty, turbulent air for the car following behind. The new rear wings have been adjusted so that turbulent air is directed upwards and is above the incoming car, allowing for more overtaking [4]. However, the curved rear wing still does have the Drag Reduction System (DRS) [5].
Thirdly, the regulations have reintroduced the ground-effect floor for the first time since 1982 [7]. This season’s car has two long underfloor tunnels that are used to create a ground effect which effectively ‘sticks’ the car to the ground and generates a downforce [8]. Downforce is a measure of the amount of vertical aerodynamic load created by a Formula 1 car’s aerodynamic surfaces. At high speeds, the downforce created by airflow around the car’s body is far greater than its weight, theoretically allowing it to drive along the ceiling of a tunnel. An increase in downforce allows the cars to travel faster across bends and reduces tyre wear [9]. This increase in downforce is particularly important due to the persistent problem of significant downforce loss. Therefore, the FIA decided to reintroduce the groundfloor effect. However, whilst the ground-floor effect has its benefits in generating additional downforce for the car, it also has its problems, its biggest being the porpoise effect (also known as “porpoising”) [9]. It means that the car has a chassis oscillation when travelling at high speeds, so the car essentially has a jumping effect, due to excessive amounts of downforce, making it extremely hard to drive and control. In my opinion, the regulation changes made are more beneficial than they are detrimental. In theory, the regulation changes are suited to make racing better and hence, they achieve their purpose. The changes effectively eradicate key problems in previous seasons, such as the calamitous loss of downforce, the inability for cars to follow others closely due to the dirty air problem and to promote safer driving. However, the FIA’s changes are not perfect as the reintroduction of the ground-floor effect has also brought about the porpoise effect, so teams will be required to adapt their car throughout the season to minimise its effect.
Figure 2. The new F1 car’s rear wing [6]
Shuaib Magamedov (8C2)
Technology has had many advantages since its first use in the stone age. It has helped us to accomplish tasks that could not be done on our own and we are able to overcome challenges and enhance our chances of survival. Its evolution from the first wheel to the electric car has shown the incredible advancements in our critical thinking. However, over recent times technology has also revealed its darker side, with negative social and psychological consequences, which have mainly arisen from its abuse. How has technology become such a hazard to our lives? Will a day come where technology replaces our humanity?
The benefits of technology to businesses and communication systems have been significant [1][3]. Digital processes have emerged which make financial transactions easier and faster. Inventions such as the credit card and the emergence of e-commerce have made trade and business move at a fast pace, on a local, national and international scale [1]. The expectation for the future is that overseas transactions could be processed in seconds and at a fraction of the current cost, with the introduction of block-chain [1]. Businesses have also
benefited greatly from the internet, which has revolutionised advertising. Marketing has been made easier, more effective and cost-efficient by companies targeting mobile devices of users, with the aim of engaging with potential customers at a personal level. This form of advertising has been crucial for small businesses and start-ups with limited budgets. The rise in the number of people using smartphones has also made this form of advertising exceedingly powerful [3].
Figure 1. Innovation has made our life more straightforward and smoother [2]
Is technology really an advancement to our society?
Technology also allows for online classes and courses as students may live too far and cannot commute. Illness and disability may also restrict access to a learning environment. Once again, the internet provides instant access to an infinite number of subject areas. Learning can be done independent of any institution, library or tutor. In addition, current developments in robotics have meant that many homes now have a virtual personal assistant such as Alexa and Siri responding to instructions from the user and in turn instantly providing the information requested [1].
However, although there are many advantages of technology, it has also provided many disadvantages to our society, mainly in terms of various aspects of mental illness. A study performed using young adults in ages 19-32 years have found a correlation between social media use and feelings of social isolation, which could lead to depression and anxiety [5]. Another factor which leads to severe mental illness is cyber-bullying. This is because no one person can be held accountable for their actions in the absence of in-depth investigation. Physical manifestations due to increased use of technology include bad posture, eyestrain, sleep deprivation and reduced physical activity [5]. Children, rather than adults, seem most vulnerable to the negative impact of technology. With the easy accessibility of the internet and devices, overuse of technology may lead to low academic performance, lack of attention and low creativity. A study in 2015 found that technology adversely affected the overall health of children and teenagers of all ages. Prolonged physical inactivity and poor sleep quality could also lead to obesity and higher BMI [5].
With adults, the constant need to use technology for email, text messages, Facebook and Twitter demands constant multitasking [6]. With smartphones more powerful than advanced computers thirty years ago, people use them constantly to communicate with others and as a source of information. However, it has been found that multitasking leads to the production of the stress hormone cortisol as well as the fight-or-flight hormone adrenaline which can result in a scrambled state of mind [6]. Cortisol production is related to states of anxiety and can also cause aggressive and impulsive behaviour. In addition, scientists at Stanford University have found that reading or studying when multitasking causes the information to be diverted to wrong parts of the brain. With the constant rapid shifting of attention from one task to another, areas of the brain such as the prefrontal cortex and striatum, burn fuel fast leading to a state of exhaustion [6]. The striatum, shown in Figure 3, is a brain structure which is a critical component of the motor and reward system. It is also involved in planning, decision making, motivation and reinforcement [7].
Figure 2. Number of smartphone subscriptions worldwide from 2016 to 2027 [3]
Figure 3. The constant use of technology demands multitasking and causes the prefrontal cortex and striatum (in yellow) to burn up glucose, that is needed to stay on task [6].
In conclusion, although technology has made a significant impact on society, its over-use has led to some damaging effects, mainly in children. As with any powerful tool, technology has the power to cure or kill and it needs to be used in a more controlled and careful manner.
Is technology really an advancement to our society?
In October 2021 I was lucky enough to be able to go on a three-day placement with an orthopaedic consultant at the Lister Hospital in Stevenage. The three days gave me an invaluable experience and a wider view of hospital life for doctors, nurses and other healthcare workers, as well as for patients and their families.
Day one started with an orthopaedic team meeting where the four consultants and a number of junior doctors reviewed each of the past week’s patients’ scans and the outcomes of their operations. The consultants offered each other constructive criticism by recognising where treatments could have been improved. The main aim of the team was to strive for perfection, even if all the operations were successful. Every consultant was making a note of how they could improve their performance.
After this initial meeting what followed was a review of the scans of the A&E admissions during the previous night, as well as the patients on the operating list for that day. Each operation was planned meticulously, with the consultants relentlessly asking the junior doctors questions regarding each case and how they would prepare for any given scenario. Finally, the consultants informed the lead nurse of their schedule for the day by providing a list of the names of the patients that were to be prepared for the operating room (OR) at a given time.
With the meetings concluded, the consultant I was shadowing had a two-hour clinic where he would see new patients, assess their injuries, and discuss possible treatments. He would also have post-treatment consultations with patients where their recovery, or lack of, was assessed and a further plan was discussed. I noticed that for the patients who were children, the doctor would talk directly to the child and clearly explain the situation before speaking to their guardian, in order, to make the child feel included and less anxious about their injury.
After the clinic, I observed how the nurses changed or removed dressings and stitches, in the plaster room. As the nurses were well aware of the discomfort and pain experienced by the patients when removing dressings and
stiches, they made every effort to keep the patients relaxed by making conversation with the patient. They also explained the procedure and informed the patients when it was going to hurt so they were not taken by surprise.
In the afternoon, I joined the consultant I was shadowing in the OR. The major case that afternoon was a man who had a fall while hiking in Cornwall and had damaged his fibula quite badly. As he had diabetes and a few other medical conditions, the majority of the regular anaesthetics could not be used as they would have adverse effects and cause further complications. The patient had to undergo surgery whilst being conscious under local anaesthesia, which meant he was awake and was talking to the team during surgery. The anaesthetist made sure the anaesthetic was still effective by regularly asking the patient if he could feel his leg during the surgery whilst the junior doctors kept talking to the patient, in order, to distract him from the operation, as they understood it was unsettling to be awake during surgery. The consultant invited his registrar to perform the operation, allowing him the freedom to conduct it as he wished, but also giving him guidance, in order, to ensure the operation was completed to a high degree of perfection.
The most significant fact I learnt from my work experience was that working in a hospital is very much a team effort. Treating a broken leg is not just the job of one orthopaedic surgeon, as there are also radiographers, registrars, anaesthetists, nurses, and hospital care workers involved. They all work together, like a well-oiled machine, with one primary goal: always putting the patient first.
Shadowing an Orthopaedic Consultant
The Nobel Prize in Physics 2021 was awarded “for groundbreaking contributions to our understanding of complex physical systems” with one half jointly to Syukoro Manabe and Klaus Hasselmann “for the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming” and the other half to Giorgio Parisi “for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales.” [1]
Manabe demonstrated “how increased concentrations of carbon dioxide in the atmosphere lead to increased temperatures at the surface of the Earth” [2], which was followed ten years later by Hasselmann’s model which “links together weather and climate” [2]. Parisi’s research outlines “hidden patterns in disordered materials” [2]. Their discoveries enhance our understanding of how different parts interact within complex systems and will dramatically influence how scientists approach climate change and other chaotic phenomena
The Nobel Prize in Chemistry 2021 was awarded jointly to Benjamin List and David W.C. MacMillan “for the development of asymmetric organocatalysis.” [3]
This new tool for molecule building makes it possible to control invisible substances so they bond in the desired way, and could revolutionise the worlds of pharmaceuticals and green chemistry.
Figure 1: Syukoro Manabe (left), Klaus Hasselmann (centre), Giorgio Parisi (right)
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The Computer and Programming: A brief outline of the origin and milestones.
Devarshi Mandal
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Virtual Reality in Medical Education and Treatment
Aarav Anil
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The Impact and Consequences of the rapid Advancement of Artificial Intelligence on Business and Employment.
Faraz Ahmad
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Technology and Space exploration
Ishan Visvanath
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Rishi Maha
[Title Image] Heart and Stroke Foundation of Canada. (n.d.). Health in the digital age. [online] Available at: https://www.heartandstroke. ca/articles/health-in-the-digital-age.
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Can we see a future where robots the over the jobs of doctors?
Aamir Salim
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Are NFT’s sustainable Amey Gupta
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How did X-ray diffraction help to confirm the structure of benzene? Charlie Pickford
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Is Nanotechnology the key to the Future of Space Exploration?
Hari Jenirathan
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Smart Cities: A smart choice? Niccolo Ruju
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Technology, Regulations and Formula 1
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Work Experience
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The 2021 Nobel Laureates
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Back Inside Cover
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