Contamination of water sources with various organic and inorganic non-biodegradable pollutants is becoming a growing concern due to industrialization, urbanization, and the inefficiency of traditional wastewater treatment processes. Transition Metal Carbides/Nitrides (MXenes) are emerging as advanced nanomaterials of choice for treating contaminated water owing to their excellent conductivity, mechanical flexibility, high specific surface area, scalable production, rich surface functionalities, and layered morphology. MXenes have demonstrated enhanced ability to adsorb various organic and inorganic contaminants depending upon their surface terminal groups (-OH, -F, and -O) and interlayer spacing. Titanium carbide (Ti3C2Tx) is most researched to date due to its ease of processing and stability. Ti3C2Tx has shown excellent performance in absorbing heavy metal ions and radioactive heavy metals. This review summarizes state-of-the-art Ti3C2Tx synthesis, including selective etching techniques, optimization of the desired adsorption features (controlling surface functional groups, intercalation, sonication, and functionalization), and regeneration and adsorption mechanism to remove contaminants. Furthermore, the review also compares the adsorption performance of Ti3C2Tx with other commercial adsorbents (including chitosan, cellulose, biomass, and zeolites). Ti3C2Tx has been found to have an adsorption efficiency of more than 90% in most studies due to its layered structure, which makes the functional groups easily accessible, unique and novel compared to other conventional nanomaterials and adsorbents. The challenges, potential solutions, and prospects associated with the commercial development of Ti3C2Tx as adsorbents are also discussed. The review establishes a framework for future wastewater treatment research using MXenes to address the global problem of water scarcity.
Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the global spatial and temporal variation in the pandemic spread has strongly anticipated the requirement of designing area-specific preventive strategies based on geographic and meteorological state-of-affairs. Epidemiological and regression models have strongly projected particulate matter (PM) as leading environmental-risk factor for the COVID-19 outbreak. Understanding the role of secondary environmental-factors like ammonia (NH3) and relative humidity (RH), latency of missing data structuring, monotonous correlation remains obstacles to scheme conclusive outcomes. We mapped hotspots of airborne PM2.5, PM10, NH3, and RH concentrations, and COVID-19 cases and mortalities for January, 2021-July,2021 from combined data of 17 ground-monitoring stations across Delhi. Spearmen and Pearson coefficient correlation show strong association (p-value 0.60) and PM10 (r > 0.40), respectively. Interestingly, the COVID-19 spread shows significant dependence on RH (r > 0.5) and NH3 (r = 0.4), anticipating their potential role in SARS-CoV-2 outbreak. We found systematic lockdown as a successful measure in combatting SARS-CoV-2 outbreak. These outcomes strongly demonstrate regional and temporal differences in COVID-19 severity with environmental-risk factors. The study lays the groundwork for designing and implementing regulatory strategies, and proper urban and transportation planning based on area-specific environmental conditions to control future infectious public health emergencies.
The continuous deterioration of the environment due to extensive industrialization and urbanization has raised the requirement to devise high-performance environmental remediation technologies. Membrane technologies, primarily based on conventional polymers, are the most commercialized air, water, solid, and radiation-based environmental remediation strategies. Low stability at high temperatures, swelling in organic contaminants, and poor selectivity are the fundamental issues associated with polymeric membranes restricting their scalable viability. Polymer-metal-carbides and nitrides (MXenes) hybrid membranes possess remarkable physicochemical attributes, including strong mechanical endurance, high mechanical flexibility, superior adsorptive behavior, and selective permeability, due to multi-interactions between polymers and MXene's surface functionalities. This review articulates the state-of-the-art MXene-polymer hybrid membranes, emphasizing its fabrication routes, enhanced physicochemical properties, and improved adsorptive behavior. It comprehensively summarizes the utilization of MXene-polymer hybrid membranes for environmental remediation applications, including water purification, desalination, ion-separation, gas separation and detection, containment adsorption, and electromagnetic and nuclear radiation shielding. Furthermore, the review highlights the associated bottlenecks of MXene-Polymer hybrid-membranes and its possible alternate solutions to meet industrial requirements. Discussed are opportunities and prospects related to MXene-polymer membrane to devise intelligent and next-generation environmental remediation strategies with the integration of modern age technologies of internet-of-things, artificial intelligence, machine-learning, 5G-communication and cloud-computing are elucidated.
Comprehending the morphological disparities between SARS-CoV-2 and SARS-CoV viruses can shed light on the underlying mechanisms of infection and facilitate the development of effective diagnostic tools and treatments. Hence, this study aimed to conduct a comprehensive analysis and comparative assessment of the morphology of SARS-CoV-2 and SARS-CoV using transmission electron microscopy (TEM) images. The dataset encompassed 519 isolated SARS-CoV-2 images obtained from patients in Italy (INMI) and 248 isolated SARS-CoV images from patients in Germany (Frankfurt). In this paper, we employed TEM images to scrutinize morphological features, and the outcomes were contrasted with those of SARS-CoV viruses. The findings reveal disparities in the characteristics of SARS-CoV-2 and SARS-CoV, such as envelope protein (E) 98.6 and 102.2 nm, length of spike protein (S) 10.11 and 9.50 nm, roundness 0.86 and 0.88, circularity 0.78 and 0.76, and area sizes 25145.54 and 38591.35 pixels, respectively. In conclusion, these results will augment the identification of virus subtypes, aid in the study of antiviral medications, and enhance our understanding of disease progression and the virus life cycle. Moreover, these findings have the potential to assist in the development of more accurate epidemiological prediction models for COVID-19, leading to better outbreak management and saving lives.
Rapid technological advancements have created opportunities for new solutions in various industries, including healthcare. One exciting new direction in this field of innovation is the combination of skin-based technologies and augmented reality (AR). These dermatological devices allow for the continuous and non-invasive measurement of vital signs and biomarkers, enabling the real-time diagnosis of anomalies, which have applications in telemedicine, oncology, dermatology, and early diagnostics. Despite its many potential benefits, there is a substantial information vacuum regarding using flexible photonics in conjunction with augmented reality for medical purposes. This review explores the current state of dermal augmented reality and flexible optics in skin-conforming sensing platforms by examining the obstacles faced thus far, including technical hurdles, demanding clinical validation standards, and problems with user acceptance. Our main areas of interest are skills, chiroptical properties, and health platform applications, such as optogenetic pixels, spectroscopic imagers, and optical biosensors. My skin-enhanced spherical dichroism and powerful spherically polarized light enable thorough physical inspection with these augmented reality devices: diabetic tracking, skin cancer diagnosis, and cardiovascular illness: preventative medicine, namely blood pressure screening. We demonstrate how to accomplish early prevention using case studies and emergency detection. Finally, it addresses real-world obstacles that hinder fully realizing these materials' extraordinary potential in advancing proactive and preventative personalized medicine, including technical constraints, clinical validation gaps, and barriers to widespread adoption.
Existing public health emergencies due to fatal/infectious diseases such as coronavirus disease (COVID-19) and monkeypox have raised the paradigm of 5th generation portable intelligent and multifunctional biosensors embedded on a single chip. The state-of-the-art 5th generation biosensors are concerned with integrating advanced functional materials with controllable physicochemical attributes and optimal machine processability. In this direction, 2D metal carbides and nitrides (MXenes), owing to their enhanced effective surface area, tunable physicochemical properties, and rich surface functionalities, have shown promising performances in biosensing flatlands. Moreover, their hybridization with diversified nanomaterials caters to their associated challenges for the commercialization of stability due to restacking and oxidation. MXenes and its hybrid biosensors have demonstrated intelligent and lab-on-chip prospects for determining diverse biomarkers/pathogens related to fatal and infectious diseases. Recently, on-site detection has been clubbed with solution-on-chip MXenes by interfacing biosensors with modern-age technologies, including 5G communication, internet-of-medical-things (IoMT), artificial intelligence (AI), and data clouding to progress toward hospital-on-chip (HOC) modules. This review comprehensively summarizes the state-of-the-art MXene fabrication, advancements in physicochemical properties to architect biosensors, and the progress of MXene-based lab-on-chip biosensors toward HOC solutions. Besides, it discusses sustainable aspects, practical challenges and alternative solutions associated with these modules to develop personalized and remote healthcare solutions for every individual in the world.
The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.
Constantly mutating SARS-CoV-2 is a global concern resulting in COVID-19 infectious waves from time to time in different regions, challenging present-day diagnostics and therapeutics. Early-stage point-of-care diagnostic (POC) biosensors are a crucial vector for the timely management of morbidity and mortalities caused due to COVID-19. The state-of-the-art SARS-CoV-2 biosensors depend upon developing a single platform for its diverse variants/biomarkers, enabling precise detection and monitoring. Nanophotonic-enabled biosensors have emerged as 'one platform' to diagnose COVID-19, addressing the concern of constant viral mutation. This review assesses the evolution of current and future variants of the SARS-CoV-2 and critically summarizes the current state of biosensor approaches for detecting SARS-CoV-2 variants/biomarkers employing nanophotonic-enabled diagnostics. It discusses the integration of modern-age technologies, including artificial intelligence, machine learning and 5G communication with nanophotonic biosensors for intelligent COVID-19 monitoring and management. It also highlights the challenges and potential opportunities for developing intelligent biosensors for diagnosing future SARS-CoV-2 variants. This review will guide future research and development on nano-enabled intelligent photonic-biosensor strategies for early-stage diagnosing of highly infectious diseases to prevent repeated outbreaks and save associated human mortalities.
Infectious outbreaks are the foremost global public health concern, challenging the current healthcare system, which claims millions of lives annually. The most crucial way to control an infectious outbreak is by early detection through point-of-care (POC) diagnostics. POC diagnostics are highly advantageous owing to the prompt diagnosis, which is economical, simple and highly efficient with remote access capabilities. In particular, utilization of nanomaterials to architect POC devices has enabled highly integrated and portable (compact) devices with enhanced efficiency. As such, this review will detail the factors influencing the emergence of infectious diseases and methods for fast and accurate detection, thus elucidating the underlying factors of these infections. Furthermore, it comprehensively highlights the importance of different nanomaterials in POCs to detect nucleic acid, whole pathogens, proteins and antibody detection systems. Finally, we summarize findings reported on nanomaterials based on advanced POCs such as lab-on-chip, lab-on-disc-devices, point-of-action and hospital-on-chip. To this end, we discuss the challenges, potential solutions, prospects of integrating internet-of-things, artificial intelligence, 5G communications and data clouding to achieve intelligent POCs.