ISG

A comparative study of fouling-free nanodiamond and nanocarbon electrochemical sensors for sensitive bisphenol A detection

Wed, 02 Dec 2020 00:00:00 +0000

EuroScience Open Forum 2020 Trieste

Tue, 01 Dec 2020 00:00:00 +0000

[Read Blog entry here] (https://www.euroscience.org/news/esof2020-trieste-interview-with-travel-grantees/)

Silver nanoparticle synthesis by hemoglobin modified electrodes

Wed, 27 May 2020 00:00:00 +0000

We report a novel electrochemical approach for synthesising colloidal silver in aqueous phase by means of a haemoglobin-modified boron-doped diamond electrode. The resulting Ag nanoparticles are within 10 nm size and highly monodisperse with minimal electrode deposition. We also introduce a method for measuring the yield of synthesised nanoparticles using square-wave voltammetry as an alternative to UV-vis spectroscopy. More than 50% of transferred electrons contributed directly to the formation of silver nanoparticles. This high yield indicates that such electrochemical synthesis is an efficient one-pot method for producing colloidal silver free of toxic reagents and offers a path toward green metal nanoparticle synthesis in solution. A comparative study using alternative electrodes, modifiers and surfactants suggests a mechanism for the formation of silver nanoparticles mediated by haemoglobin-modified boron-doped diamond.

High-Yield Electrochemical Synthesis of Silver Nanoparticles by Enzyme-Modified Boron-Doped Diamond Electrodes

Thu, 14 May 2020 00:00:00 +0000

Bayes in times of Corona

Tue, 05 May 2020 00:00:00 +0000

R app Antibody Explorer (english)

R app AntiGorputz Explorer (euskeraz)

Trends and innovations in biosensors for COVID‐19 mass testing

Mon, 04 May 2020 00:00:00 +0000

Self-propelled nanomotors

Wed, 01 Apr 2020 00:00:00 +0000

The World Wide Test for Covid-19

Wed, 25 Mar 2020 00:00:00 +0000

Introduction

The outbreak of COVID-19 has put around a billion people in quarantine and brought the economies of many countries to a halt. However, the real impact on society is yet to come. While some criticise severe lockdowns as alarmist, others are calling for even stricter measures. Panic spreads quicker than the virus and is fuelled by a lack of information such as the real number of infected cases and the actual case fatality ratio (CFR). This leads to large uncertainties in quantifying and predicting the extent of this pandemic.

To obtain this key information, reliable diagnostics of COVID-19 for tracking and surveillance of new infections and recoveries becomes essential. For SARS, the development of tests took about five months. With COVID-19, it has been remarkable the short time it took from the detection of the first case (Nov. 2019) [1] to the sequencing of the viral genome by Chinese scientists (11 Jan 2020) [2] and the development of the first molecular assay (13 Jan 2020) [3]. Nevertheless, in many countries, testing is still minimal or rationalised, as the testing capacity is overwhelmed by the extent of the outbreak. This has led to significant variations in testing numbers per population across countries [4]. Insufficient statistically well-designed testing prevents us from knowing the real number of infected cases and leads to a more than likely overestimate of the CFR [5], once adjusted for delays in reporting finalised cases (mean delay of 13 days from confirmation of disease to outcome) [6]. Unreported infections (either asymptomatic or mild cases) may have contributed to the surge in cases around the world. Countries with widespread mass testing and surveillance strategies like South Korea, have been able to contain the spread successfully [7].

So what are the molecular diagnostic methods for COVID-19 that are currently available? How do they work? What are their limitations? What emerging technologies are we expecting in this direction? This article aims to answer these questions and explores how we can accelerate sensitive and accurate mass testing.

1. Reverse transcription polymerase chain reaction (RT-PCR)

Molecular diagnostic assays aim to detect the presence of viral RNA specific to SARS-COV-2 (the virus responsible for COVID-19), such as sequences from regions of the virus nucleocapsid gene. The gold standard test involves the amplification of the viral RNA by a process called Reverse transcription polymerase chain reaction (RT-PCR).

1.1. How the RT-PCR test works

A swab is taken from the nose or throat of the potentially infected individual, and the sample is then processed for nucleic acid extraction and amplification. We can divide this process into three steps: RNA extraction, transcription of RNA into complementary DNA (cDNA) and PCR amplification of DNA.

Steps in the RT-PCR test: a) Specimen is taken from the nose or throat of individual b) RNA is extracted and c) is transcribed into complementary DNA (cDNA) , d) Once the primers have bound to the DNA, they provide a starting point for the DNA polymerase to help copy it. DNA polymerase then degrades the bound probe which results in an increased fluorescence signal e) The fluorescence increases as copies of the virus DNA are made. If the fluorescence level crosses certain threshold, the test result is positive.

RNA extraction: RNA is isolated and purified using fast spin-columns (e.g. QIAamp Viral RNA Mini Kit by QIAGEN).

Master mixture preparation for RT-PCR: A mixture is prepared containing a forward primer (short oligonucleotides needed to start DNA synthesis), a backward primer and a fluorescent probe , together with the enzymes Reverse Transcriptase (responsible for converting RNA into cDNA) and DNA polymerase (responsible for DNA replication). National laboratories and companies around the world have developed different primers and probes addressing different regions of the viral genome. Some companies provide these mixtures in lyophilised form for direct use.

Reagent mixing and Real-Time PCR Amplification: In a single or two-step RT-PCR, first RNA is converted first into complementary DNA and then the DNA signal is amplified by a real time polymerase chain reaction (a.k.a quantitative PCR). In Real-Time PCR the probe strand (containing two dyes: a reporter and a quencher dye) binds to a specific target sequence to SARS-COVID-19 located between the forward and reverse primers (Figure 1d). During the extension phase of the PCR cycle, the polymerase degrades the bound probe, causing the reporter dye to separate from the quencher dye, resulting in an increased fluorescent signal. The fluorescence intensity is monitored at each amplification cycle.

The fluorescence signal increases as more copies of DNA are produced. If the fluorescence crosses a certain threshold, set above expected background levels, the test result is positive. If the virus was not present in the sample, the PCR test would not have made copies, so the fluorescence threshold is not reached and the test result is then negative (Figure 1e). The cyle threshold (Ct) is the number of PCR cycles required to achieve such a threshold (i.e. exceed the background level). Internal positive (samples known to contain SARS-COV-2 RNA) and negative controls are run in parallel to confirm the validity of the result.

1.2. What can go wrong ?

An important question arises regarding the sensitivity of these tests. The limit of detection (LoD) sets the lowest concentration of SARS-COV-2 that can be detected by the PCR test. The LoD is determined by detecting the presence of the viral RNA in at least 95% of the cases. For COVID-19 assays, the LoD can reach levels lower than 10 genome copies per reaction (0.5 cp/$\mu l$) [8]. However, the sensitivity varies depending on the chosen kits and PCR instrument. Failure to detect the virus in infected patients (false negatives) can be due to low sensitivity or other issues, such as laboratories working under pressure, or poor sample collection and preparation. It is yet unknown which types of specimens are optimal for detection with RT-PCR. A recent study from Wuhan suggests that nasopharyngeal swabs may offer greater consistency than other types of samples [9]. These tests could also lead to false positives if, for example, specimens are contaminated or the protocol is not followed appropriately.

Whether positive or negative, the PCR test is only indicative of whether the virus is present at the time the test is taken. It neither rules out whether the patient was infected in the past and therefore has developed immunity, nor that the patient is at an early infection stage and will show symptoms in the future.

The long processing time and high demand for testing kits and ancillary ingredients needed for sample preparation and the test represent a serious bottleneck. The whole process from sample can provide results in 4 to 6 hours, although some centralised labs might require up to 48 hours from sample to answer. While large providers such as Roche Diagnostics, Qiagen and Thermo Fisher Scientific, have ramped up the capacity to provide kits and reagents, it is questionable whether they can currently meet the needs of many countries at the moment. Some companies are providing their own kits and proprietary rapid point-of-care molecular diagnostic systems, mostly based on RT-PCR, which include robotic automation and microfluidic handling of samples (an extensive list can be found in [10]).

2. Rapid tests (antigenic and serological)

Facing reagent shortages, many countries like Spain and the UK are raising an urgent call out to the life sciences sector to help increase the development and supply of antigen testing kits for COVID-19, so-called “rapid tests”.

These tests are less reliable than RT-PCR tests but can be performed at the point-of-care, or in community settings without the need for expensive equipment. The concept of the test is a somewhat similar to how pregnancy tests work. Normally they rely on lateral flow assays, simple cellulose-based devices intended to detect the presence of a target analyte in a liquid sample. They make use of antibody-antigen recognition, using monoclonal antibodies to detect viral antigens. Test strips are coated with antibodies that bind to a viral protein, although some prototypes use aptamers instead. If the patient’s sample contains the viral proteins, they will bind to the antibodies forming a coloured indicator on the strip. Colloidal gold nanoparticles are the most commonly used material to induce a change in colour in the presence of the analyte. This represents one of the wonderful uses of nanoplasmonics.

These tests can be done in 10 to 30 min and far away from big laboratories but in order for them to give reliable measurements, the concentration of the analyte needs to be higher than 10 copies/ul. This means that most of these tests may only work in symptomatic individuals. Spain has announced the purchase of 640000 antigenic rapid tests.

Typical lateral flow assay for a serological test a) Inside the cassette is a strip made of filter paper and nitrocellulose. Typically, a drop of blood is added to the cassette through one hole (sample well), and then a number of drops of buffer usually through another hole (buffer well). Buffer carries the sample along the length of the cassette to the results window. b Interpretation of results. c A schematic of the COVID-19 lateral flow test from 11. The antibody first binds to an antigen conjugated to colloidal gold in the conjugation pad, and the resultant complex is captured on the strip by a band of bound antibodies, forming a visible line (T - test line) in the results window. A control line (C- control line) gives information on the integrity of the antibody-gold conjugate.**a)****a)**a)

Serological tests make use of the same principle as other immunoassays, but instead of detecting viral antigens, the assay detects the presence of antibodies against the virus in the patient sample. These tests can be used to detect current and past exposure to SARS-COV-2 and can be done in batches in a laboratory or individually at point-of-care settings. Quantifying the number of immune populations will help assess the true extent of an outbreak, and inform prevention and control strategies.

A problem with both antigen and serological immunoassays is that antibodies may cross-react and a SARS-COV-2 could also give a positive result with other types of coronavirus. As many companies around the world race to produce rapid tests, probing the accuracy of such tests will require trials with hundreds of known SARS-COV-2 infected cases.

3. Towards mass testing and technology innovations

Researchers at the Technion in Israel have accelerated the RT-PCR testing rate by taking a pooling approach, enabling the simultaneous testing of dozens of samples. This group testing method is able to identify a positive sample among 64 different samples [12]. No new technology is needed, but the necessary logistics to implement the pooling strategy, substituting the current individual testing. Such a pooling method, if scaled up appropriately could lead to massive testing, thus making better use of current resources and quickly rejecting negative cases.

Another innovative approach is a CRISPR-based lateral flow assay. CRISPR is a powerful gene-editing tool that has already led to ground-breaking outcomes in clinical trials in the past years. Going beyond Cas9 and its capacity to act as “molecular scissors”, CRISPR and its associated proteins can offer more than that.

On a race for CRISPR-based diagnostics, Mammoth Bioscience and the Broad-Institute are using CRISPR as a molecular diagnostic tool, rather than as an editing tool, to create fast, cheap and more accurate tests to detect illnesses. CRISPR based tests offer the possibility of diagnosing infections as accurately as conventional methods, and almost as simply as pregnancy test strips. They have recently secured $45 Million For Crispr-based diagnostics and have partnered at UC San Francisco to use their test against coronavirus. Their published results on SARS-COV-2 promise a 30 min low-cost CRISPR-based lateral flow assay [13]. The Broad-Institute at MIT has developed an analogous technique called SHERLOCK [14], with a COVID-19 specific protocol [15].

Uncertainties in modelling the extent of this pandemic, has given rise to discrepancies in scientific advice provided to governments. Some researchers even suggest, without any serological evidence available yet, that a large fraction of the population could already have developed immunity to COVID-19 [16]. Such widespread immunity would be a game-changer, but serological evidence is needed to support it. This reinforces the case for widespread testing.

While we wait for a vaccine, let us hope we can all connect to the World Wide Test!

This article was published in GlobalBioTech Insights

Quantum computing: from the qubit to a commercial reality

Tue, 26 Feb 2019 00:00:00 +0000

Quantum computers have been a dream for over 40 years, which comes from harnessing the laws of quantum physics to process information. Although one might hear of this concept often, the general public do not realise the importance of quantum computers and understand how it would affect our society.

Quantum computers promise a technology which is orders of magnitude more powerful than current systems, capable of disrupting entire industries. In the face of an ideal quantum computer, our current network security would be as fragile as a house of cards. It is also believed that quantum computers would bring AI into the next stage, bringing supercomputers from �fiction to reality.

Carrying a high expectation, quantum computing is driving significant investment worldwide (currently estimated at $ 4 billion/year), mostly due to its potential value for economic and information security. Governments are the key investors in quantum computing, both directly and via defence contractors. It is estimated that the total revenue generated from potential quantum computing markets could exceed *$*15 billion by 2028.

Quantum computing is now more than a scientifi�c curiosity and is rapidly transitioning into a technical reality. But how far away we are from real quantum computing?

Development of the quantum computer

To better understand the current stage of quantum computer, it is worth to have a look at the history of the digital computer. The ENIAC was the �first electronic computer built for general purposes in 1945. It occupied large rooms, containing more than 20000 vacuum tubes and was operated with switches that needed to be rewired for every new calculation. Vacuum tubes were later replaced with transistors that today power every electronic design. Progressive miniaturisation of microprocessors has taken us in less than a century from vacuum tubes to pocket-sized digital computers, following Moore’s law .

A similar revolution is taking place today with the advent of quantum computation. Many current prototypes of quantum computer are still hybrid ones (leveraging both quantum and classical computation), which occupy a few garages and have less processive power than the most basic PC. However, the development of quantum computers is moving fast.

IBM showcased a quantum computer at the Consumer Electronics Show (CES) in Las Vegas earlier this year. The prototype, which IBM claims is the �first integrated, general-purpose quantum computer, has been named the ‘Q System One’, and is enclosed in a 3-meter sealed cube made of borosilicate glass. IBM claims that Q System One is, with 20 qubits, more reliable than its previous experimental prototypes, bringing the company a step closer to the commercialization of this technology.

As expected, large IT players are at the forefront of quantum computing. Just like the early players in classical computers ended up dominating the market, the same might be true for the emerging quantum computing market. This is why larger blue-chip companies are moving into the quantum computing race. For example, Intel is working on a 49-qubit chip, Google designing a 72-qubit quantum processor called Bristlecone, and Microsoft is working on a scalable quantum computer. The image below shows some important players and investors in quantum computing.

Worldwide investment and key players in quantum computing. The size of circles shows the investment.

From bit to quantum bit But what is a quantum computer and how is it different than a classical computer? The word quantum suggests some exotic property closely linked with quantum physics, which is the branch of physics that describes the world of atoms and its subatomic particles. Despite the name, quantum computers only differ from classical computers in the way they represent and process information. Classical computers process information with the limitations of classical physics. Information is represented by bits (either 0 or 1). Quantum computers, however, make use of an important quantum phenomenon, known as superposition, by which the state can be in both 0 and 1. This coherent superposition of 0 and 1 is a quantum bit (qubit). A quantum bit when represented on a sphere, the angles the radius forms is related to the probabilities of the state being in either 0 or 1 ((shown in Figure 2) Source: Nielsen, M. A. & Chuang, I. (AAPT, 2002)) . This strange quantum property allows for a quantum bit to encode more information than a regular classical bit. For example, a pair of qubits can represent four states, three qubits eight states, and N qubits can represent 2N bits.

How to build a quantum computer? Quantum computing is no longer a mere scientifi�c curiosity, only discussed in some theoretical physics textbook. In the past years, engineers have realised several qubit platforms experimentally. Two promising technologies stand out as physical implementations of quantum computers, namely ion traps and superconducting qubits. The most natural approach is to use single atoms as qubits, trap them in a con�ned space and manipulate them with lasers. In ion traps, each atom can represent the binary code values of 0 or 1 (or a super¬position of the two), as illustrated in (Figure 3 right). In superconducting qubits, however, the strategy is based on building superconducting circuits that can take on the value of 0 or 1 or a superposition, by the presence or absence of a microwave photon (Figure 3 left).

We are used to desktop computers (and phones) with billions of classical bits. Quantum engineers have managed to create quantum computers beyond 20 qubits. Why is this so challenging? An essential requirement is to generate and maintain isolation of individual quantum particles and retain their “quantumness”. Qubits lose their quantum properties easily and become mere classical bits (a process known as decoherence). This is why the physical implementations of quantum computers often require extreme conditions to avoid any sources of noise, such as ultralow temperatures and ultrahigh vacuum. The fragility of qubits makes large-scale quantum computation practically impossible, unless a form of error correction is used. Quantum error correction is a crucial aspect of quantum computation and helps preserve the fragile quantum states making quantum computation feasible. Sceptics point out that the high sensitivity to noise is a signi�cant roadblock for successfully implementing quantum computers that are better than classical ones. However, experimental efforts to reduce the noise, increase the lifetime of the qubits and reduce the time required for single operations are on their way.

The IBM Q System One is a superconducting quantum computer of 20 qubits (left, from CES 2019). This technology is, made of superconducting circuits. Qubits can take the value of 0 or 1 or a superposition based on the absence or presence of a microwave photon. The Ion Trap (right) consists of trapping atoms in a con�ned space and storing information in their electronic state. (Image from Christopher Monroe Laboratory)

What can quantum computers do and why should we care? Early on, physicists realised the immense computational potential of qubits. For example, cryptography is one important future application of quantum computing. Decryption of messages could become trivial with quantum computers as they will solve complex calculations in mere seconds. Multiplying two large numbers to get a larger one is easy, but the opposite problem (integer factorisation) is at the foundation of modern communication security cryptosystems. The ability to factor a large number into its prime integers, known as the RSA-problem, is intractable with modern classical computers. Peter Shor’s algorithm shows that an ideal quantum computer could factor integers e�fficiently and therefore break RSA-codes in reasonable times. Figure 4 shows how the time it takes to �nd the RSA- key scales exponentially for classical computers, reaching the age of the universe for problems that quantum computers could solve in a matter of hours.

In addition to breaking cryptocodes, ideal quantum computers can search unsorted databases and solve optimisation problems more e�fficiently. More importantly quantum computers can serve as “quantum simulators” for more complex systems, with applications in drug development and material science.

The perspective of combining machine learning algorithms with the computational power of quantum computers has opened up a new �eld of Quantum Machine Learning. Quantum computers will help solve complex AI problems more e�fficiently. Finding patterns in a sea of data, using these to predict future outcomes will open the door to many possibilities, ranging from traffic control to supply chains. With the vast amount of data that we generate today, it is in this area that quantum computers can be disruptive. Quantum supremacy is the moment when quantum computers are able to solve problems that classical computers cannot. There is a long road ahead to reach that goal. There are a number of technical obstacles and thus far quantum computers are not faster than a classical computer. While the software and hardware challenges are still considerable, large-scale realisations of quantum computers are on their way. The journey for the classical computer took a century, from the vacuum tubes to the smartphone. The race for the quantum computer is on, and it moves fast. Whether big or small, we will soon �and out what kind of impact quantum computers will bring.

If you wish to learn more about quantum computing please contact us at: research*@*IDTechex.com

Authors:

Dr. Ibon Santiago is a physicist at the Technical University of Munich.

Dr. Luyun Jiang is a technology analyst from IDTechEx.

Published for IDTechEx Market Research here

Sources:

1 The Economist (2017).

2 Nielsen, M. A. & Chuang, I. (AAPT, 2002).

3 Debnath, S. et al. Demonstration of a small programmable quantum computer with atomic qubits. 536, 63 (2016).

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Tue, 05 Feb 2019 00:00:00 +0000

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Documentation

Self-Propulsion Strategies for Artificial Cell-Like Compartments

Tue, 01 Jan 2019 00:00:00 +0000

DNA nanotechnology and self-assembly of active matter

Fri, 21 Dec 2018 00:00:00 +0000

Open Access: Scientific Publishing 3.0

Tue, 23 Oct 2018 00:00:00 +0000

Original Blog entry in Nature Chemistry here

Before the creation of scholarly journals to publish scientific findings researchers engaged in correspondence to communicate and claim priority in their discoveries. Galileo sent letters to contemporary astronomers like Kepler, to claim priority in the discovery of the moons of Jupiter (Medicean stars).

Eventually, the secretary of the Royal Society Henry Oldenburg started publishing some of the letters he received in the form of a journal as we are familiar today [1]. The purpose was to have a registry of discoveries and archiving, as a well as a tool for dissemination and impact of discoveries. This represented a first revolution in scientific publishing, aided by the advent of the printing press.

One of the earliest scientific journals is the Philosophical Transactions (Phil Trans) of the Royal Society. Phil. Trans. pioneered the subscription journal model and the peer-review system. At first, journals were owned mainly by scientific societies and they published scholarly research for the benefit of their members. Although it added value to the scientific community, publishing journals was not a very profitable enterprise because of high expenses. It wasn?t until the 20th century that commercial publishers entered the world of scientific publishing, due to a high demand of new journals that would cover emerging research fields. The apparent non-lucrative business led to what librarians call the ?serials-pricing crisis?, resulting in costly subscription prices growing faster than the inflation rate.

In this context, libraries and academic institutions, even the ones with a large budget, cannot afford to subscribe to all journals. They have to choose which journals to subscribe to, or sometimes even cancel many subscriptions to meet budgetary demands. This leaves a long list of publications inaccessible to the reader. The Bodleian Library (University of Oxford) alone spends more than £2 million per year in subscription fees to the ten largest publishers of academic journals [2]. Institutions are often involved in complex negotiations with publishers around the price of their license and how limited the reuse of content should be.

Beyond the financial dimension to this problem, high subscription fees also raise ethical concerns, as access to information for readers, students and researchers is at stake. Constraining access to knowledge harms the creation of knowledge itself and does not contribute to effective scientific communication.

The Digital Age has triggered another change in scientific publishing, namely the open access publication, thanks to new digital tools and the internet. In Open Access (OA) journals the costs of accessing articles are not paid by readers, thereby removing a powerful artificial barrier to dissemination that was not possible with printed journals. [3]

Although there is still a general misunderstanding of the open access jargon, many funding agencies are discussing the adoption of new regulations (e.g. Plan S, Horizon 2020, ERC), which will make it mandatory for publicly funded research to be open access. However, Article Processing Charges (APC) can be excessive if not supported by the funding agencies or employers. To encourage researchers to take the OA route, Open Access today generally takes two complementary forms: Gold Open Access, which encourages publishers to adopt open access policies and Green Open Access, which asks researchers to self-archive their works in university repositories. Gold Open Access normally comes associated with Article Processing Charges to be paid by the author or the author’s employer or funder and makes the work openly available at the time of publication. This has been the model adopted by the new Communications journals of the Nature Publishing Group. Green Open Access, on the other hand, is cost-free and makes the outcomes of the research available in a public repository, subject to embargoes dictated by the journal where the research was published.

Open Access offers to create a cheaper and more efficient system of scientific communication. However, we are still at an early stage to gauge its advantages, as the subscription-based model continues to dominate. More than 80 percent of articles continues to be published under the subscription model, according to Elsevier [4]. This means that researchers advocating for OA will still need pay for subscription journals, on top of the publication fees of their articles. While the benefits of OA regarding dissemination and impact are hard to challenge, it will remain to be seen if OA will become more cost-effective or will increase the budgetary burden of researchers.

As more OA publications become available online, they compete for visibility and may not attract a large audience automatically. Non-research content, as well as the boundless growth of predatory journals will become a threat to the maintenance of curated and high-quality scholarly publications.

All the same, scientists should have the academic freedom to choose the journal where they want to publish. With more researchers choosing the OA route, then perhaps the era that started with the Phil Trans 353 year ago and the subscription-based model will be replaced, favouring a new open access culture in scholarly publications.

References

[1] Guédon, J.-C. In Oldenburg’s long shadow: Librarians, research scientists, publishers, and the control of scientific publishing. (Association of Research Libraries, 2001).

[2] Lawson, S. & Meghreblian, B. Journal subscription expenditure of UK higher education institutions. F1000Research3, doi:10.12688/f1000research.5706.3 (2015). Data available here.

[3] Suber, P. Open access. (MIT Press, 2012). More information on Open Access by Peter Suber here.

[4] Hersh, G. Working towards a transition to open access, Elsevier (2017). URL

Thanks to Amalia Gonzalez for help with illustration Kaiola ireki (2018)

Nanocarbon and nanodiamond for high performance phenolics sensing

Thu, 27 Sep 2018 00:00:00 +0000

Phenolic compounds are pollutants of major concern, and effective monitoring is essential to reduce exposure. Electrochemical sensors offer rapid and accurate detection of phenols but suffer from two main shortcomings preventing their widespread use: electrode fouling and signal interference from co-existing isomers. Here we demonstrate a potential solution based on environmentally friendly and biocompatible carbon nanomaterials to detect monophenols (phenol and cresol) and biphenols (hydroquinone and catechol). Electrode fouling is tackled in two ways: by introducing electrochemically resistant nanodiamond electrodes and by developing single-use nanocarbon electrodes. We provide a comprehensive analysis of the electrochemical performance of three distinct carbon materials (graphene, nanodiamond and nanocarbon). Nanocarbon exhibits the lowest detection limit below 10−8 M, and one order of magnitude higher sensitivity than the other carbon nanomaterials. We detect co-existing phenol isomers with nanocarbon electrodes and apply it in river water and green tea samples, which may pave the way towards low-cost industrial scale monitoring of phenolic compounds.

Nanocarbon and nanodiamond for high performance phenolics sensing

Mon, 06 Aug 2018 00:00:00 +0000

Enzymatic nanomotors carrying a DNA cargo

Fri, 27 Jul 2018 00:00:00 +0000

A physical theory of the biological world requires that we quantitavely understand Active matter. These are systems that are maintained out-of-equilibrium and are capable of sustained motion, while they consume energy from their environment.

Molecular motors (kinesin, myosin, etc.) are examples of active matter at the nanoscale that convert ATP into mechanical energy in an environment dominated by thermal fluctuations and viscous forces. What are the physical constraints we have to overcome to manufacture devices of comparable complexity? . From first principles, we make use of simple building blocks, such as nanoparticles, enzymes and nucleic acids in order to self-assemble nanodevices capable of mimicking molecular motors, the workhorses of cells. With the tools of DNA nanotechnology we can self-assemble nanostructures from bottom-up (DNA Origami) and functionalise site-specifically these nanostructures with nanomotors. We use catalytic nanoparticles, as well as enzymes to help reach propulsion that goes beyond diffusion.

Bottom-up synthesis of catalytic nanomotors

Fri, 27 Apr 2018 00:00:00 +0000

Progress in nanotechnology has enabled the synthesis of active particles that can harness chemical energy and translate it into useful work. Catalytic self-propelled motors have implications for understanding out-of-equilibrium systems and have potential applications in active transport at the nanoscale, where they can be used as motors and pumps. Although much research has been done on micron-sized motors, progress in catalytic nanomotors of sub 100?nm is still in its infancy. These nanosized motors are of great importance for future molecular transport at the cellular level because they operate at length scales at which protein motors work. This opinion article focusses on recent advances in the synthesis of catalytic nanomotors and experimental strategies to measure their self-propulsion, which differ from that of micromotors. Enzymatic and metallic nanomotors are surveyed, together with various theoretical models for self-propulsion. Solutions to current challenges are proposed, which include a chemical synthesis approach, new characterisation of motor activity and potential uses of nanomotors in nanomedicine.

Nanoscale active matter matters: Challenges and opportunities for self-propelled nanomotors

Wed, 07 Feb 2018 00:00:00 +0000

Self-propulsion of catalytic nanomotors synthesised by seeded growth of asymmetric platinum-gold nanoparticles

Fri, 02 Feb 2018 00:00:00 +0000

What is active matter and why it matters.

Thu, 11 Jan 2018 00:00:00 +0000

[Read Blog entry here] (https://sruk.org.uk/why-active-matter-matters/)

DNA programmed assembly of active matter at the micro and nano scales.

Sun, 01 Oct 2017 00:00:00 +0000

Phenolic sense and sensibility

Sun, 03 Sep 2017 00:00:00 +0000

Click here for the Nature Chemistry Blog Post. The full paper published in Communications Chemistry is here

Experiments that don’t work as expected sometimes may lead us to new research directions. This is the case for the work in this article, which started with a problem we faced in a different context.

We were investigating water treatment methods using nanocarbon electrodes to remove toxic phenolic compounds from river water. However, soon we realised that the performance of the electrode declined significantly over time, rendering it useless. We knew we were not alone, as many groups had also reported the poisoning of their electrode surface, due to the oxidation of phenol. Therefore, we changed our focus to find a more resistant electrode against poisoning. We searched around the lab and nanodiamond was an immediate choice, as it is well-known for its high chemical resistance. The results were very positive, and we did not observe a significant drop in the signal.

If the goal is to have a stable phenolic sensor for environmental monitoring stations, then nanodiamond is a strong candidate. However, sensors are becoming ubiquitous in our lives, as miniaturised versions are slowly being integrated into many portable devices. That is why we aimed at creating a high-performance sensor that would be more accessible for public use than nanodiamond. Such low-cost sensor would need to be accurate and sensitive enough to detect toxic levels of phenolics. Carbon materials were an attractive choice for this purpose, as they are economical, accessible and do not contaminate the sample like other metal-based sensors. So that forced us to return to nanocarbon, a cheap and abundant material compared with nanodiamond. Although the signal decreased when we used one nanocarbon electrode for many cycles, we found the results for each electrode were highly reproducible. The facile preparation and its reproducibility inspired us to develop a disposable nanocarbon-based sensor, similar to the well-known electrochemical strip for one-time glucose testing.

We also noticed that the oxidation peaks for different phenolic compounds were easily distinguishable. This allowed us to detect different phenolic compounds simultaneously, which is more useful as they often co-exist in real samples.

We set out to test our sensor in different river waters. So, we asked one colleague to bring samples from the Yangtze river in China. Unfortunately, customs officers did not like the idea! In the absence of the Yangtze river water, we decided to test our sensor with more accessible sources: green tea (thanks to the canteen in our building) and Thames river water collected in Oxford.

This work is a combinatorial study of three different carbon-based sensors for detecting four phenolic compounds. We hope it provides a comprehensive account of phenolic sensing and can be helpful for anyone who would like to understand sensors based on different carbon materials.

Luyun Jiang and Ibon Santiago

Acknowledgements

We would like to give special thanks to Amalia González for help with the illustration on this post.

Observation of nanoimpact events of catalase on diamond ultramicroelectrodes by direct electron transfer

Wed, 05 Jul 2017 00:00:00 +0000

2D DNA self-assembled surfaces

Thu, 27 Apr 2017 00:00:00 +0000

Biomolecular self-assembly, using DNA as the building blocks of nanometre-scale structures, can be used to pattern surfaces with near-atomic precision. By combining this new technique with liquid crystal technology we have created DNA tiles that can be used as surfaces for testing liquid crystal (LC) alignment.

Here we explore two different approaches: on the one hand a two-layer Origami structure was used, on the other DNA brick/crystals of finite depth were assembled. TEM, AFM and fluorescence microscopy were used to assess the size and surface coverage of the tiles. DNA bricks grew to structures of the order of a micrometer and could be visualised by fluorescence microscopy. These were further developed by introducing a ridge pattern of 10 nm on the DNA surface. Liquid crystal molecules were deposited by inkjet printing and by spin-coating, achieving a LC thickness of few micrometers.

The experimental approach in this project consisted of finding the right DNA self-assembled surface, deposit it on the right substrate, visualise and characterise it. Finally, the liquid crystal was deposited on this surface to study any alignment induced by DNA.

Such structures provide a unique opportunity for studying complex intermolecular interactions at the nanometre scale and give access to a range of application spaces beyond next-generation liquid crystal displays.

Nanoimpact voltammetry of enzymatic nanomotors

Thu, 27 Apr 2017 00:00:00 +0000

Ordering Gold Nanoparticles with DNA Origami Nanoflowers

Fri, 01 Jul 2016 00:00:00 +0000

DNA Nanoflowers

Wed, 27 Apr 2016 00:00:00 +0000

DNA-guided nanoparticle lattices are promising model systems for exploring the controlled assembly of matter. Ordered arrays of gold and silver nanoparticles, for example, are promising building blocks for plasmonic metamaterials.

In this work we created DNA Origami structures to allow flexible control of the effective valency and bond angles of encapsulated gold nanoparticles. These ‘nanoflower’ shaped hybrid nanostructures could be reprogrammed through a number of DNA linker strands to create lattices of different symmetries (hexagonal, square and linear chains).

DNA autocatalytic chemical waves

Mon, 27 Apr 2015 00:00:00 +0000

Quantum degenerate Bose-Fermi mixture of chemically different atomic species with widely tunable interactions

Wed, 09 May 2012 00:00:00 +0000

LiNaK : multi-species apparatus for the study of ultracold quantum degenerate mixtures

Tue, 01 May 2012 00:00:00 +0000

Strongly interacting isotopic Bose-Fermi mixture immersed in a Fermi sea

Wed, 13 Jul 2011 00:00:00 +0000

Bose-Fermi Mixture Immersed in a Fermi Sea

Wed, 27 Apr 2011 00:00:00 +0000

Mixtures of Ultracold Quantum Gases

In the experiment Fermi 1 at the Centre for Ultracold Atoms (CUA) of the Massachusetts Institute of Technology, we created a triply quantum degenerate mixture of bosonic 41K and two fermionic species, 40K and 6Li. In the group of Prof. Martin Zwierlein we built and used Fermi 1 to show that 41K is an efficient coolant for the two fermions, giving a versatile instrument for the observation of fermionic superfluids with imbalanced masses.

Experimental setup of Fermi 1. Two independent Zeeman slowers yield a high flux of $^{6}$Li and K allowing simultaneous loading and trapping in a UHV chamber of three atomic species: fermionic $^{6}$Li and $^{40}$K and bosonic $^{41}$K

More info: LiNaK : multi-species apparatus for the study of ultracold quantum degenerate mixtures by Ibon Santiago

Strongly Interacting Isotopic Bose-Fermi Mixture Immersed in a Fermi Sea

a)-c): Absorption images of triply degenerate quan- tum gases of 41 K, 40 K and 6 Li, imaged after 8.12 ms, 4.06 ms and 1 ms time of flight from the magnetic trap, respectively. The final rf-knife frequency was 500 kHz above the 254.0 MHz hyperfine transition of 41K. The white circles indicate the Fermi radius in time of flight t, RF = 2EF /m t. d)-f): Azimuthally averaged column density. Solid dots: gaussian fit to the wings of the column density. Solid black and blue lines are gaussian and Fermi-Dirac fits to the entire profile.

Bose-Fermi mixture of Na-K

Wed, 27 Apr 2011 00:00:00 +0000

We have created a quantum degenerate Bose-Fermi mixture of 23Na and 40K with widely tuneable interactions via broad interspecies Feshbach resonances. Over 30 Feshbach resonances between 23Na and 40K were identified, including p-wave multiplet resonances. The large and negative triplet background scattering length between 23Na and 40K causes a sharp enhancement of the fermion density in the presence of a Bose condensate. As explained via the asymptotic bound-state model, this strong background scattering leads to wide Feshbach resonances observed at low magnetic fields. Our work opens up the prospect to create chemically stable, fermionic ground-state molecules of 23Na-40K, where strong, long-range dipolar interactions would set the dominant energy scale.

Loss of Longitudinal Landau Damping in the LHC Injectors

Sat, 05 Jan 2008 00:00:00 +0000