MXene‐Based Aptameric Fluorosensor for Sensitive and Rapid Detection of COVID‐19

MXene‐Based Aptameric FluorosensorsThe aptamer‐functionalized MXene nanosheet acts as an effective bionanosensor for fluorescence‐enhanced detection of COVID‐19 with high sensitivity and specificity. This fluosensor is capable of detecting SARS‐CoV‐2 spike protein (limit of detection: 38.9 fg mL−1) and SARS‐CoV‐2 pseudovirus (limit of detection: 7.2 copies) within 30 min, and can also detect clinical samples. More details can be found in article number 2301146 by Binwu Ying and co‐workers.

Noncontact liquid–solid nanogenerators as self-powered droplet sensors

Liquid–solid triboelectric nanogenerators (L–S TENGs) can generate corresponding electrical signal responses through the contact separation of droplets and dielectrics and have a wide range of applications in energy harvesting and self-powered sensing. However, the contact between the droplet and the electret will cause the contact L–S TENG's performance degradation or even failure. Here we report a noncontact triboelectric nanogenerator (NCLS-TENG) that can effectively sense droplet stimuli without contact with droplets and convert them into electrical energy or corresponding electrical signals. Since there is no contact between the droplet and the dielectric, it can continuously and stably generate a signal output. To verify the feasibility of NCLS-TENG, we demonstrate the modified murphy's dropper as a smart infusion monitoring system. The smart infusion monitoring system can effectively identify information such as the type, concentration, and frequency of droplets. NCLS-TENG show great potential in smart medical, smart wearable and other fields.

Effect of trade barriers on export performance during COVID-19 pandemic: a comparative study among South Asian textile industries

Studiul s-a concentrat pe determinarea politicilor guvernamentale esenţiale si a barierelor comerciale care afectează performanţa exporturilor industriei textile în timpul pandemiei de COVID-19. Acest studiu a analizat influenţa politicilor guvernamentale de export asupra performanţei la export a industriei textile. Acest studiu a comparat, de asemenea, factori din trei industrii textile din Asia de Sud, respectiv Pakistan, India si Bangladesh. Studiul a identificat nouă politici guvernamentale de export esenţiale si bariere comerciale bazate pe vizualizarea organizaţiei industriale (Vizualizarea I/O). A fost utilizat un model de regresie de tip panel pentru a analiza semnificaţia fiecărei politici guvernamentale si barierele comerciale care afectează performanţa exporturilor de produse textile. Rezultatele studiului au arătat că ratele de schimb valutar, costul de export, timpul de export, stabilitatea politică a ţării, calitatea infrastructurii din ţară, libertatea din corupţie, costul de afaceri al terorismului si stabilitatea economică în ţară au un efect semnificativ asupra performanţei la export a industriei. În schimb, taxele pentru desfăşurarea afacerilor au un efect nesemnificativ asupra performanţei la export. Testul de Estimare aparent fără legătură (SUEST) a comparat diferenţele de performanţă la export ale industriilor textile din Pakistan, India si Bangladesh datorate politicilor guvernamentale. Rezultatele au arătat că un nivel mai ridicat de timp pentru export, costul de export si costul pentru desfăsurarea afacerilor terorismului duc la performanţa scăzută la export a industriei textile. În acelasi timp, un nivel mai ridicat al cursurilor de schimb valutar, stabilitatea politică a ţării, calitatea infrastructurii, libertatea din corupţie si stabilitatea economică în ţară duc la performanţe ridicate la export ale industriei textile. Mai mult, taxele pentru desfăsurarea afacerilor au un efect nesemnificativ asupra performanţei la export. Acest studiu este printre puţinele care abordează industria textilă în timpul pandemiei de COVID-19. Din cauza circumstanţelor incerte, va fi greu pentru guvern să identifice factori importanţi care ar putea ajuta exportatorii de textile să supravieţuiască si să se dezvolte în timpul pandemiei de COVID-19. Studiul a identificat politici guvernamentale importante si bariere comerciale care afectează exporturile de textile pe baza unui sprijin teoretic solid si a comparat si a elaborat, de asemenea, importanţa fiecărui factor în trei ţări din Asia de Sud. Acest studiu va ajuta factorii de decizie să-si reconsidere factorii legaţi de export pentru a-si spori exporturile de textile si pentru a-si relansa economia după pandemia de COVID-19.Alternate :The study focused on determining essential government policies and trade barriers affecting the textile industry's export performance during the COVID-19 pandemic. This study has analysed the effect of government export policies on the export performance of the textile industry. This study has also compared factors among three South Asian textile industries, including Pakistan, India, and Bangladesh. The study identified nine essential government export policies and trade barriers based on Industrial Organization View (I/O View). A panel regression model was used to analyse the significance of each government policy and trade barrier affecting textile export performance. Results of the study showed that currency exchange rates, the cost to export, time to export, political stability of the country, quality of infrastructure in the country, freedom from corruption, business cost of terrorism and economic stability in the country have a significant effect on export performance of the industry. In contrast, taxes on doing business have an insignificant effect on export performance. The Seemingly Unrelated Estimation (SUEST) test compared the differences in export performance of Pakistani, Indian and Bangladeshi textile industries due to governmen policies. The results showed that a higher level of time to export, cost to export and business cost of terrorism lead to the low export performance of the textile industry. At the same time, a higher level of currency exchange rates, political stability of the country, quality of infrastructure, freedom from corruption and economic stability in-country lead to the high export performance of the textile industry. Further, taxes on doing business have an insignificant effect on export performance. This study is among the few contributing to the textile industry during the COVID-19 pandemic. Due to uncertain circumstances, it becomes hard for the government to identify important factors which could help textile exporters to survive and grow during the COVID-19 pandemic. The study has identified important government policies and trade barriers affecting textile exports based on strong theoretical support and has also compared and elaborated on the importance of each factor across three South Asian countries. This study will help policymakers reconsider exportrelated factors to enhance their textile exports and revive their economy after the COVID-19 pandemic.

New generation washable PES membrane face mask for virus filtration

Membrane materials might be used for face protection because they can decontaminate the inhaled air from particle pollution and viruses like the SARS-Cov0-2 which damages our respiration system. In this study, plyethersulfone membranes (PES) were synthesized with green solvent at room temperature and its filtration effectiveness was investigated against nano-bacteria (size 0.05 to 0.2 µm) by measuring their Bacterial Filtration Efficiency (BFE) and micro aerosol size (0.3 µm), and Particulate Filtration Efficiency (PFE). The average SARS-CoV-2 diameters are between 50 nm to 160 nm. A series of experiments were performed to accomplish between 0.03 to 0.21 µm PES sponge like diameters so that can be used for SARS-CoV-2 filtration. Results showed that nanofiltration/ultrafiltration could filter 99.9% of bacteria and aerosol from contaminated air the size of the Covid-19 molecule.

Mosaic Patterned Surfaces toward Generating Hardly‐Volatile Capsular Droplet Arrays for High‐Precision Droplet‐Based Storage and Detection

Mosaic Patterned SurfacesIn article number 2206274, Yanjun Hu, Lin Li, and co‐workers report a mosaic patterned surface‐based chip that acquires mutually independent and hardly‐volatile capsular droplet arrays. The concept shows high compatibility and practicability, paving the way for the new microfluidic chips used in COVID‐19 diagnosis and other high‐precision detection.

Academic performance prediction associated with synchronous online interactive learning behaviors based on the machine learning approach

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students participating in online class. Five machine learning models are employed to predict academic performance of an engineering mechanics course, taking online learning behaviors, comprehensive performance as input and final exam scores (FESs) as output. The analysis shows the gradient boosting regression model achieves the best performance with the highest correlation coefficient (0.7558), and the lowest RMSE (9.3595). Intellectual education score (IES) is the most important factor of comprehensive performance while the number of completed assignment (NOCA), the live viewing rate (LVR) and the replay viewing rate (RVR) of online learning behaviors are the most important factors influencing FESs. Students with higher IES are more likely to achieve better academic performance, and students with lower IES but higher NOCA tend to perform better. Our study can provide effective evidences for teachers to adjust teaching strategies and provide precise assistance for students at risk of academic failure in advance.

Academic performance prediction associated with synchronous online interactive learning behaviors based on the machine learning approach

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students participating in online class. Five machine learning models are employed to predict academic performance of an engineering mechanics course, taking online learning behaviors, comprehensive performance as input and final exam scores (FESs) as output. The analysis shows the gradient boosting regression model achieves the best performance with the highest correlation coefficient (0.7558), and the lowest RMSE (9.3595). Intellectual education score (IES) is the most important factor of comprehensive performance while the number of completed assignment (NOCA), the live viewing rate (LVR) and the replay viewing rate (RVR) of online learning behaviors are the most important factors influencing FESs. Students with higher IES are more likely to achieve better academic performance, and students with lower IES but higher NOCA tend to perform better. Our study can provide effective evidences for teachers to adjust teaching strategies and provide precise assistance for students at risk of academic failure in advance. [ FROM AUTHOR]

Failure Prediction, Testing, and Retrofit of Open Web Steel Joists in an Undergraduate Curriculum

This paper provides an overview of how failure prediction of critical members in an open web steel joist is used in multiple courses in a structural engineering curriculum. The forensic example is used in an introductory engineering mechanics course to demonstrate how the method of sections and joints can be used to analyze a truss system widely used in practice. Combining the concepts of steel yielding, column buckling, and factor of safety allows the students are tasked to predict the critical members in the joist. Immediately, following the analytical exercise, students experimentally verify their predictions. Later in the curriculum, students revisit their analysis in a steel design course. The students are posed with a retrofit competition where groups compete to increase the load carrying capacity of the joist and changing the failure mode of the joist. The group that completes this task for the least costs (material and labor) is crowned class champion. Students often conduct an analysis to determine forces in members;however, rarely do they predict critical member and failure mode in an assembly and then verify their results in real time. Even more rarely does this experience carry through multiple courses. The format of the lectures, laboratory exercises, laboratory execution, assignments, and competition are presented. Additionally, the paper includes discussion on how the experience was altered due to COVID considerations. Assessment data, student feedback, and recommendations for additional expanded assignments are presented. © Forensic Engineering 2022: Elevating Forensic Engineering - Selected Papers from the 9th Congress on Forensic Engineering.All rights reserved.

Nanotechnology-Enhanced Face Masks: Future Scopes and Perspectives

The coronavirus disease 2019 pandemic has shown that a disposable surgical face mask is a good protective wall against infection due to its ability to prevent virus transmission from sick to healthy people. Nevertheless, these surgical masks are disposable, not ecofriendly, and are single-use items. The use and disposal of traditional masks lead to high secondary risks such as environmental pollution, pathogen transmission, overload demands, and user discomfort. Nanotechnology is one of the most investigated strategies to safely and economically reuse masks in the 21st century. These strategies are based on four key elements as follows: (1) super mechanical properties that give masks flexibility, durability, and good lifetime storage;(2) high thermal properties that give masks heat self-sterilization;(3) an electric charge controller that gives masks triboelectric (TE) filtration;and (4) response to the antimicrobial effect that stays in the mask before, during, and after safe use. These properties give new-generation masks the ability to remove the drawbacks of traditional surgical masks, such as microbial growth and low filtration efficiency. The graphene family has introduced the self-sterilization and TE effects of surgical masks. Silver nanoparticles have supported antimicrobial effects. Nanofiber membranes are fabricated to have a high surface area that improves the fiber diameter and porosity ratio. A traditional mask could only block a maximum of 50% of the exhaled viruses, but a nanofiber-based mask has been tested to intercept 90% to 99% of particle viruses while breathing during use. Complex nanocomposite materials have succeeded in collecting all these advantages.

Revisualizing Statics

This evidence-based practice paper describes the study of Statics or Engineering Mechanics 1 course. This is an entry-level course for freshman or sophomores in many engineering disciplines and includes topics such as forces, equilibrium of forces, truss analysis, centroid, and moment of inertia. It is observed that this is a difficult course for students and the passing rate is 60.7% [1]. To reduce the failure rate of students in class, instructors often try to implement a variety of methods. Hands-on models, active learning methods, ExCEEd model [2], Flipped Classroom model [3], and Montessori Based Engineering (MBE) Model [4] are some of the models used by instructors. Student success improved by 3%-7% [5] when these methodologies were used. Hands-on models when used in combination with other active learning methods are engaging and useful in maintaining student interest [2]. In-class instruction is usually expected for active learning using hands-on models for Statics 1. This has been especially difficult during COVID-restricted learning situations and has created a learning gap between current students and former. This paper describes the use of Virtual Reality (VR), a computer-generated simulation of a three-dimensional object or space, to fill both of these issues caused by remote learning.VR is a powerful flexible platform that when utilized can generate differentiating perspectives of problems. The VR tool Tilt Brush [6] was used to replace the physical hands-on models typically used in class to provide an engaging diverse experience. Typically, the students are introduced to a 3D Vector problem as a picture in a book or PowerPoint slide and the instructor proceeds to explain the problem using direct instruction. This method can work for some students. However, students might not be entirely clear on how the vectors and angles are actually represented in 3D space. Instructors have tried to use physical hands-on models to help students understand this concept. Most students develop an understanding of visualizing and analyzing 3D vectors after working with these physical models, thus it is great for in-person learning. However, this is not possible in an online environment. There is no denying that higher education is moving toward online learning [7]. COVID brought to everyone's attention how educators need to better prepare to transition into an online learning environment. With this in mind, the authors decided to create "hands-on models" in Virtual Reality. These models were presented in different formats in order to provide a variety of perspectives and to help engage the students in the learning module. Student engagement was very high for this module when students were shown videos. If it was made more hands-on by teaching synchronously, it is expected that student engagement would be even higher. Development of teaching this 3D Vector module, student assessment, survey, and conclusions are included in this paper. The goal of this paper is to inspire and encourage a Statics 1 instructor to start using VR in their own course and then possibly consider expanding the VR technique to other mechanics concepts and major courses. © American Society for Engineering Education, 2022.

From Online to Hybrid: The Evolution of Flipped Learning in a First-Year Engineering Mechanics Course

This paper examines the evolution of a first-year engineering mechanics course, Solid Mechanics I, over the two iterations that it has been flipped. It discusses the teaching strategies that have and haven't worked when delivering the course in both an online and hybrid approach. These include recommended durations for lecture videos, types of assessments, grade distributions, etc. Flipping the classroom was a result of the forced transition online due to Covid-19. To best support the students in the unprecedented times, the instructor opted to combine components from both asynchronous and synchronous teaching styles. Asynchronous lecture videos were accompanied by synchronous class time where the instructor clarified concepts, demonstrated real-life applications, solved higher-level problems, and implemented group activities. A combination of these active learning strategies was the key to structuring the course to keep the students engaged despite being online for all, or part, of the term as delivered in Fall 2020 and Fall 2021, respectively. In the Fall 2020 iteration, the course was delivered fully online to roughly 325 students in civil, environmental, geological, and architectural engineering. Since then, the course had been improved and adjusted in response to the students' feedback collected from an end-of-term survey. Approximately 270 students were enrolled in the course in the subsequent Fall 2021 term which took a hybrid approach as Covid-19 restrictions began to lighten. With students being able to learn in-person again, the course had shifted to emphasize student-to-student and student-to-instructor interactions. Feedback became immediate, allowing for the course to be molded to the students' satisfaction as the term progressed. Changes between the two years have been documented in the paper along with recommendations for future adaptations. © American Society for Engineering Education, 2022

Understanding System Complexity in the Non-Destructive Testing of Advanced Composite Products

Non-destructive testing (NDT) is a quality control measure designed to ensure the safety of products according to established variability thresholds. With the development of advanced technologies and a lack of formalised knowledge of the state-of-the-art, the National Composites Centre, Bristol, has identified that the increasing complexity of composite products will lead to some severe inspection challenges. To address the apparent knowledge gap and understand system complexity, a formulaic approach to introduce intelligence and improve the robustness of NDT operations is presented. The systemic development of a high-fidelity knowledge base (KB) involves the establishment of a capability matrix that maps material, component, and defect configuration to the capabilities and limitations of selected detection methods. Population and validation are demonstrated through the experimental testing of reference standards and evaluated against an assessment criteria. System complexity in ultrasonic testing operations focusses on capturing the inherent risks in inspection and the designation of evidence-based path plans for automation platforms. Anticipated deployment of the validated applicability data within the KB will allow for road-mapping of the inspection technique development and will provide opportunities for knowledge-based decision making. Moreover, the KB highlights the need for Design for Inspection, providing measurable data that the methodology should not be ignored.

Impact of Dialysis Clinical Operating Conditions on Human Serum Protein-Mediated Inflammatory Biomarkers Released in Patients Using Polyarylethersulfone Membranes

Hemodialysis (HD) is a life-sustaining treatment of crucial importance in managing end-stage renal disease (ESRD). However, this membrane-based therapy is associated with acute side-effects due to bioincompatibility issues and limitations on the removal of uremic toxins. The present study assessed the influence of hydrodynamic conditions applied during HD treatment on protein-mediated inflammatory and thrombotic responses. The membrane modules considered are commonly used in Canadian hospitals and are comprised of a polymer blend of polyarylether sulfone-polyvinylpyrrolidone (PAES). The membranes morphology and hydrophilicity were assessed using SEM, AFM, BET, and zeta potential. An in vitro study evaluated the adsorptive behavior of fibrinogen (FB) to the membrane under different flow conditions. Lower rates of 200 mL/min promoted slower and significant FB adsorption, leading to more severe inflammatory and thrombotic responses. Hydrodynamic conditions also affected the concentration of all inflammatory biomarkers. Lower flow rates triggered more complement activation as well as coagulation, clotting, and inflammatory responses compared to higher flow rates. At the end of the dialysis session, patients treated with a Qb of 200 mL/min presented a significant increase in the concentration of C5a (232%), properdin (114%), serpin (545%), IL-1α (50%), IL-6 (450%), and vWF (212%). IL-1β and TNF-α concentrations declined by 12.5 and 35.5%, respectively. Male patients experienced more severe inflammatory responses than female patients at the operating conditions considered. Comparing the pre- and post-dialysis levels of female and male patients, female patients experienced significantly higher levels of IL-6 and properdin, while male patients presented higher levels of C5a, IL-1α, and IL-6. The results of this study will help clinical doctors evaluate the impact of HD operating conditions on blood activations before prescribing treatment and inform expectations for outcomes in female and male patients.

Green Synthesize and Characterization of Copper Nanoparticles Using Iranian Propolis Extracts

The propolis produced by bees is used by them to protect their hives. The cavity inside the hive’s walls is filled in during cold days to reduce entry points and mummify any intruders to ensure their survival. A current focus in nanotechnology and nanoscience is the green biosynthesis of nanoparticles (NPs) using biomaterials. Research on green methods for making metal oxide NPs is gaining momentum to safeguard the environment from the potential dangers associated with toxic chemicals. This study aimed to synthesize copper NPs (CuNPs) via propolis extraction, a novel application of nanoscience. The study was conducted under a range of pH, time conditions, and concentration ratios, and its properties were characterized by UV-Vis absorption spectra, XRD, and FTIR. An FTIR analysis revealed that compounds found in propolis extract could have an effect on the surface modification of the synthesized NPs. The propolis (Khalkhal) extract spectrum exhibited a sharp peak at 3422 cm−1, caused by free hydroxyl groups and their intra/intermolecular hydrogen bonds. There were sharp peaks at 2925, 1637, and 1515 to 1076 cm−1 associated with the C = O and C = C aromatic stretching frequencies. According to UV-Vis spectrophotometry investigation, CuO NPs exhibit a characteristic peak at 385 nm, showing significant surface plasmon resonance (SPR) with propolis (Khalkhal) extract. Furthermore, specific wavelengths of CuO NPs demonstrate peaks at 243, 292, and 350 nm for propolis (Gilan) extract. The green synthesis of CuNPs from Gilan and Khalkhal propolis can be an appropriate candidate for clinical applications such as drug delivery systems, drug formulation, and biomedical applications.

Comparative analysis of working capital management in Turkish apparel industry in terms of firm sizes

Capitalul de lucru, de care afacerile au nevoie pentru a-şi desfăşura activităţile zilnice si pentru a-şi plăti datoriile pe termen scurt, influenţează, de asemenea, în mod semnificativ profitabilitatea companiilor. Pandemia de Covid-19 din 2020 a forţat ţările să se închidă în perioadele în care boala s-a extins, ceea ce a dus aproape la încetarea comerţului intern şi exterior. Multe întreprinderi cu lichiditate slabă au fost nevoite să-şi închidă datoriile pe termen scurt. Odată cu pandemia, capitalul de lucru a devenit mult mai important pentru întreprinderi. În acest studiu, întreprinderile de îmbrăcăminte care operează în Turcia şi ale căror date din situaţiile financiare pot fi accesate prin intermediul Băncii Centrale au fost clasificate în funcţie de dimensiunea lor şi au fost analizate ratele de lichiditate ale acestor companii în perioada 2011-2020. În ultimii 10 ani, s-a stabilit că, în special întreprinderile mari şi mijlocii şi-au consolidat lichiditatea şi şi-au crescut semnificativ numerarul şi echivalentele de numerar. Cu toate acestea, o astfel de creştere nu a fost observată în puterea de numerar a întreprinderilor mici. În plus, în cadrul studiului au fost analizaţi factorii care influenţează profitabilitatea companiilor şi s-a determinat că scăderea ratei Levier Financiar şi Îndatorare la capitaluri proprii la întreprinderile mari a crescut profitabilitatea. În întreprinderile mijlocii, s-a stabilit că creşterea ratei curente şi a perioadelor de încasare a creanţelor a crescut profitabilitatea. S-a stabilit că singura lichiditate semnificativă care afectează profitabilitatea întreprinderilor mici este lichiditatea curentă.Alternate :Working capital, which businesses need to carry out their daily activities and pay their short-term debts, also significantly affects the profitability of companies. The Covid-19 pandemic in 2020 forced countries to close during the periods when the disease increased, which led to almost cessation of domestic and foreign trade. Many enterprises with weak liquidity had to close their short-term debts. With the pandemic, working capital has become much more important for enterprises. In this study, apparel enterprises operating in Turkey and whose financial statement data can be accessed through the Central Bank were classified according to their size and the liquidity ratios of these companies between 2011-2020 were analysed. In the last 10 years, it has been determined that especially large and medium-sized enterprises have strengthened their liquidity and significantly increased their cash and cash equivalents. However, such an increase was not observed in the cash power of small enterprises. In addition, the factors affecting the profitability of the companies were analysed in the study, and it was determined that the decrease in the Financial Leverage and Debt to Equity ratios in large enterprises increased the profitability. In medium-sized enterprises, it has been determined that the increase in current ratio and receivables collection periods increased profitability. It has been determined that the only significant ratio that affects profitability in small-scale enterprises is the current ratio.

Nanotechnology Role Development for COVID-19 Pandemic Management

The global outbreak of coronavirus disease has sent an ominous message to the field of innovative and advanced technology research and development (COVID-19). To accomplish this, convectional technology and recent discoveries can be combined, or new research directions can be opened up using nanotechnology. Nanotechnology can be used to prevent, diagnose, and treat SARS-CoV-2 infection. As the pandemic spreads, a thorough examination of nanomaterials' role in pandemic response is highly desirable. According to this comprehensive review article, nanotechnology can be used to prevent, diagnose, and treat COVID-19. This research will be extremely useful during the COVID-19 outbreak in terms of developing rules for designing nanostructure materials to combat the outbreak.

Aerosol capture and coronavirus spike protein deactivation by enzyme functionalized antiviral membranes

The airborne nature of coronavirus transmission makes it critical to develop new barrier technologies that can simultaneously reduce aerosol and viral spread. Here, we report nanostructured membranes with tunable thickness and porosity for filtering coronavirus-sized aerosols, combined with antiviral enzyme functionalization that can denature spike glycoproteins of the SARS-CoV-2 virus in low-hydration environments. Thin, asymmetric membranes with subtilisin enzyme and methacrylic functionalization show more than 98.90% filtration efficiency for 100-nm unfunctionalized and protein-functionalized polystyrene latex aerosol particles. Unfunctionalized membranes provided a protection factor of 540 ± 380 for coronavirus-sized particle, above the Occupational Safety and Health Administration’s standard of 10 for N95 masks. SARS-CoV-2 spike glycoprotein on the surface of coronavirus-sized particles was denatured in 30 s by subtilisin enzyme-functionalized membranes with 0.02-0.2% water content on the membrane surface.The COVID-19 pandemic highlights the importance of materials that block airborne virus transmission. Here, a nanostructured membrane is shown to filter coronavirus-sized particles, while the membrane surface incorporates enzymes that denature the SARS-CoV-2 spike protein within 30 s.

Structures, properties, and challenges of emerging 2D materials in bioelectronics and biosensors

Bioelectronics are powerful tools for monitoring and stimulating biological and biochemical processes, with applications ranging from neural interface simulation to biosensing. The increasing demand for bioelectronics has greatly promoted the development of new nanomaterials as detection platforms. Recently, owing to their ultrathin structures and excellent physicochemical properties, emerging two‐dimensional (2D) materials have become one of the most researched areas in the fields of bioelectronics and biosensors. In this timely review, the physicochemical structures of the most representative emerging 2D materials and the design of their nanostructures for engineering high‐performance bioelectronic and biosensing devices are presented. We focus on the structural optimization of emerging 2D material‐based composites to achieve better regulation for enhancing the performance of bioelectronics. Subsequently, the recent developments of emerging 2D materials in bioelectronics, such as neural interface simulation, biomolecular/biomarker detection, and skin sensors are discussed thoroughly. Finally, we provide conclusive views on the current challenges and future perspectives on utilizing emerging 2D materials and their composites for bioelectronics and biosensors. This review will offer important guidance in designing and applying emerging 2D materials in bioelectronics, thus further promoting their prospects in a wide biomedical field.

Detection of SARS-CoV-2 using dielectric modulated TFET-based biosensor

Attributable to the rapid increase in human infection of Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the World Health Organization (WHO) has declared this disease outbreak as a pandemic. This outbreak can be tackled to some extent through proper management and early diagnosis. This work reports a biosensor based on vertical tunnel field-effect transistor (VTFET) developed for the detection of SARS-CoV-2 from the clinical samples through the analysis of its spike, envelope, and DNA proteins. Investigation of the sensitivity of the proposed sensor has been done by calculating the shift in drain current. The dielectric constant equivalent of the virus proteins is used to represent the hybridized biomolecules within the nanogaps. The sensitivity of this proposed sensor is found to be significantly high (order of 106) showing the viability of the device to be a superior sensor. Furthermore, the sensitivity analysis concerning DNA charge density is also performed. The effect of DNA charge density variation on the threshold voltage (Vth) and sensitivity have also been studied in this work. The proposed sensor is also investigated for its noise performance and observed the sensitivity with and without the effect of interface trap charges. Finally, the proposed sensor is benchmarked against the sensitivity of various FET-based biosensors already published earlier.