Opportunities For Applications Research Articles

IMMERSIVE ANALYTICS

Immersive Analytics focuses on the benefits and challenges of using immersive environments for data analysis, and developing designs to improve efficiency. Although immersive technologies are widely available, practical solutions have not gained widespread acceptance in real- world applications. Research in this field focuses on abstract 3D visualization, immersive environments, paper sampling and use case evaluation. 03 Related Works • Brooks early review of VR applications found it effective in specific domains like flight simulators, automotive engineering, and astronaut training. • Van Dam et al. highlighted VR applications for SciVis, benefiting archaeology and medical fields. • Laha and Bowman reviewed VR techniques for visualizing volume data, highlighting the need for controlled experiments to explore individual components of immersion. • Reda et al. summarized research for hybrid reality environments like the CAVE2, emphasizing the possibility of collaborative data analysis. • Brath collected evidence that 3D visualizations offer advantages beyond 2D, focusing on immersive displays. 05 Result • Overall, immersive analytics can lead to better data comprehension, better decision-making, more engagement and teamwork, effective big data exploration, creative data visualization methods, non-technical users' empowerment, and applications in a variety of fields. • These results add to the increasing importance of immersive analytics as an efficient tool for decision support and data analysis. Introduction • To facilitate data-driven analytical reasoning, immersive analytics leverages interactive technology like as virtual reality glasses, big flat screen displays, and even the internet of things. • Immersion refers to an experience that creates a genuine sense of presence in a virtual environment. • A person experiences a shift in awareness from their immediate real environment to another reality. • Immersion analytics is still a relatively new field that has mostly been studied in use cases and workshops. • The notion remains extremely difficult, even within the small community of immersive analytics practitioners. Methodology 4.1 Immersive environments • The study focuses on immersive environments leading to a mixed reality experience. • Abstract 3D visualizations must be presented in a mixed or VR environment where hardware and user interact closely. 4.2 Abstract 3D visualizations • Data that lacks a physical representation or intrinsic spatial organization is referred to as abstract data. • In visualization, abstraction is obtained by using colors and shapes that are not directly associated with the object. 4.3 Paper sampling • Paper sampling in immersive analytics refers to the process of selecting and gathering relevant research papers and publications related to immersive analytics. Conclusion and future scope • In conclusion, immersive analytics has the potential to completely transform how we work with data by facilitating deeper understanding, better decision-making, and improved teamwork. • Immersion analytics will develop further and contribute significantly to data analysis and decision support in the future by tackling issues and seizing opportunities in technological innovation, domain-specific applications, ethical issues, and user experience design.

Spatiotemporal vortex strings.

Light carrying orbital angular momentum (OAM) holds unique properties and boosts myriad applications in diverse fields. However, the generation of an ultrafast wave packet carrying numerous vortices with various transverse OAM modes, i.e., vortex string, remains challenging, and the corresponding detection method is lacking. Here, we demonstrate that a vortex string with 28 spatiotemporal optical vortices (STOVs) with customizable topological charge (TC) arrangements can be generated in one wave packet. The diffraction rules of STOV strings are revealed theoretically and experimentally. Following these rules, the TC values and positions of all STOVs in a vortex string can be simultaneously recognized from the diffraction pattern. Such STOV strings facilitate STOV-based optical communication. As a proof-of-principle demonstration, the transmission of an image is realized with 16-STOV strings. This work provides guidance for revealing the underlying properties of the transverse OAM light and opens up opportunities for applications of the structured light in optical communication, quantum information processing, etc.

Experiments in supply chain management research: A systematic review and future directions

AbstractThe supply chain management discipline has seen a tremendous growth in the use of experimental methods. Given the large number of published studies, the time seems opportune to systematically review the use of such approaches. In this note, we consider multiple dimensions of experimental design used in articles published in six of our premier journals. We present these findings and contemplate opportunities for future applications of experimental methods. In particular, we highlight a need to more regularly conduct and report on the results of power analyses and experimental checks, more carefully contemplate the justification and use of WEIRD (Western, educated, industrial, rich, and democratic) participants, develop and test mediated theoretical models, and increase our focus on teams as the unit of analysis when using experimental methods.

Biochemical characterization of immobilized recombinant subtilisin and synthesis and functional characterization of recombinant subtilisin capped silver and zinc oxide nanoparticles

This pioneering research explores the transformative potential of recombinant subtilisin, emphasizing its strategic immobilization and nanoparticle synthesis to elevate both stability and therapeutic efficacy. Achieving an impressive 95.25 % immobilization yield with 3 % alginate composed of sodium along with 0.2 M CaCl2 indicates heightened pH levels and thermal resistance, with optimal action around pH 10 as well as 80 °C temperature. Notably, the Ca-alginate-immobilized subtilisin exhibits exceptional storage longevity and recyclability, affirming its practical viability. Comprehensive analyses of the recombinant subtilisin under diverse conditions underscore its adaptability, reflected in kinetic enhancements with increased Vmax (10.7 ± 15 × 103 U/mg) and decreased Km (0.19 ± 0.3 mM) values post-immobilization using N-Suc-F-A-A-F-pNA. UV–visible spectroscopy confirms the successful capping of nanoparticles made of Ag and ZnO by recombinant subtilisin, imparting profound antibacterial efficacy against diverse organisms and compelling antioxidant properties. Cytotoxicity was detected against the MCF-7 breast cancer line of cells, exhibiting IC50 concentrations at 8.87 as well as 14.52 µg/mL of AgNP as well as ZnONP, correspondingly, indicating promising anticancer potential. Rigorous characterization, including FTIR, SEM-EDS, TGA and AFM robustly validate the properties of the capped nanoparticles. Beyond therapeutic implications, the investigation explores industrial applications, revealing the versatility of recombinant subtilisin in dehairing, blood clot dissolution, biosurfactant activity, and blood stain removal. In summary, this research unfolds the exceptional promise of recombinant subtilisin and its nanoparticles, presenting compelling opportunities for diverse therapeutic applications in medicine. These findings contribute substantively to biotechnology and healthcare and stimulate avenues for further innovation and exploration.

Photofunctional Gold Nanocluster Composites for Bioapplications.

Gold nanoclusters (AuNCs), with customized structures and diverse optical properties, are promising optical materials. Constructing composite systems by the assembly and incorporation of AuNCs can utilize their optical properties to achieve diagnostic and therapeutic applications in the biological field. Therefore, the exploration of the assembly behaviors of AuNCs and the enhancement of their performance has attracted widespread interest. In this review, we introduce multiple interactions and assembly modes that are prevalent in nanocomposites and microcomposites based on AuNCs. Then, the functions of AuNC composites for bioapplications are demonstrated in detail. These composite systems have inherited and enhanced the inherent optical performances of the AuNCs to meet diverse requirements for biological sensing and optical treatments. Finally, we discuss the prospects of AuNC composites and highlight the challenges and opportunities in biomedical applications.

Interfacial Mass Diagnostics: Quantitative Perspective on Construction and Mechanism Understanding of Dye-Sensitized, Perovskite and Quantum Dots Solar Cells.

Dye-sensitized solar cells (DSSCs), quantum dot-sensitized solar cells (QDSSCs) and perovskite solar cells (PSCs) have attracted wide attention. DSSCs, QDSSCs and PSCs can be prepared by liquid phase or solid phase, which causes a certain range of interface micro-mass changes during preparation. In addition, the photoelectric conversion process occurring inside the device also inevitably causes interface micro-mass changes. Interpretation of these interface micro-mass changes can help to optimize the cell structure, improve the stability and performance repeatability of the device, as well as directly or indirectly infer, track and predict the internal photoelectric conversion mechanism of the device. Quartz crystal microbalance (QCM) is a powerful tool for studying surface mass changes, extending this technology to the fields of solar cells to directly obtain interface micro mass changes, which makes the research more in-depth and opens up a new perspective for explaining the basic principles of solar cells. This review summarizes the research progress of QCM application in DSSCs, QDSSCs and PSCs in recent years, and explores the challenges and new opportunities of QCM application in new solar cells in the future.

Microwave irradiation-induced yield enhancement of coconut shell biomass-derived graphene-like material

Abstract This paper reports a new strategy (rapid and selective microwave irradiation) to achieve an improved yield of graphene-like material derived from coconut shell biomass. The influence of various microwave irradiation (MWI) powers (80, 240, and 400 W) treatment on the crystalline structures, morphology, and electrochemical performance of the produced samples was determined and compared with the virgin-untreated specimen. The obtained samples were analyzed using varied analytical techniques. The FESEM images of the irradiated samples revealed the existence of graphene-like morphologies accompanied by some thin and transparent sheets. The sample at 80 W displayed the best quality with the highest yield, improving the carbon content, reducing the oxygen functional groups, and increasing the BET-specific surface area by as much as 1238.48 m²/g. The electrochemical properties of the sample treated at 80 W (optimum MWI power treatment) exhibited rectangular curves against scanning speeds, indicating an ideal capacitive behaviour called electric double-layer capacitance (EDLC). It is asserted that the proposed systematic and eco-friendly approach in obtaining the high-performance graphene-like material at low cost may open up sundry opportunities for practical applications, leading towards sustainable development.

Highly efficient molybdenum nanostructures for solar thermophotovoltaic systems: One-step fabrication of absorber and design of selective emitter

Efficient solar energy harvesting materials or structures have become a topic of great interest in response to the ever-increasing energy demand. Refractory transition metals have been found to exhibit attractive properties in broadband absorptance, making them highly effective in solar thermophotovoltaic (STPV) systems that aim to surpass the Shockley-Queisser limit. Typically, broadband absorbers are made from hybrid materials or complex geometrical structures, which require multi-step fabrication technologies. In this study, we successfully developed a highly efficient broadband absorber based on molybdenum (Mo) nanosheets using a one-step physical vapor deposition process. The nanosheets result in the high absorber efficiencies of 96.1 % for blackbody radiation (BBR) at 5778 K and of 96.4 % for air mass (AM) 1.5 spectrum, and are insensitive to polarization and incident angle. After annealing at 1650 K for 24 h, the Mo nanosheets absorber demonstrates outstanding thermal stability without compromising the efficiency of the STPV system. To complete the STPV system, a selective narrowband Mo-based gratings emitter was further designed with a high emissivity of 96 % at a wavelength of 2.17 μm, resulting in a high PV cell efficiency of 41.8 % around 1723 K. Through a series of theoretical calculations, the proposed STPV system can achieve an overall conversion efficiency of 40.2 % by a trade-off between the structure temperature and the sun concentration. Furthermore, an efficiency of 35.5 % can be achieved at a low temperature of 1073 K with a low solar concentration of 500 suns.The results provide tremendous opportunities for widespread applications of high-performance STPV systems.

Structural characterization of the polysaccharide from the black crystal region of Inonotus obliquus and its effect on AsPC-1 and SW1990 pancreatic cancer cell apoptosis

In this study, one water soluble polysaccharide (IOP1–1) with a weight average molecular weight of 6886 Da was obtained from the black crystal region of Inonotus obliquus by hot water extraction, DEAE-52 cellulose extraction and Sephadex-100 column chromatography purification. Structural analysis indicated that IOP1–1 was a glucan with a main chain composed of α-Glcp-(1 → 4)-α-Glcp-(1 → 4)-β-Glcp-(1 → 4)-β-Glcp-(1 → 4)-α-Glcp-(1 → 6)-β-Glcp-(1 → 4)-α-Glcp-(1 → 3)-β-Glcp-(1→. The CCK-8 assay results showed that IOP1–1 inhibited AsPC-1 and SW1990 pancreatic cancer cell proliferation in a concentration-dependent manner. Flow cytometric analysis revealed that IOP1–1 induced cell cycle arrest in AsPC-1 and SW1990 cells. Hoechst 33342 staining and Annexin V-FITC/PI double staining analysis showed that IOP1–1 could induce apoptosis in AsPC-1 and SW1990 cells. Furthermore, western blot analysis confirmed that IOP1–1 could induce apoptosis in AsPC-1 and SW1990 pancreatic cancer cells through three pathways: the mitochondrial pathway, the death receptor pathway, and endoplasmic reticulum stress. According to these research data, IOP1–1 may be utilized as an adjuvant treatment to anticancer medications, opening up new application prospects and opportunities.

Enhancing Thermal Insulation of Poly(β-Hydroxybutyrate) Composites with Charring-Foaming Agent-Coated Date Palm Wood

Date palm fiber (DPF) holds great potential for composite materials, but its flammability limits its practical applications. In this study, DPF was modified using a pad-drying method to impregnate it with a 5 wt.% solution of ammonium dihydrogen phosphate (ADP). These treated fibers were then utilized to fabricate poly(β-hydroxybutyrate)- (PHB-) based composites. The resulting thermal insulators were comprehensively evaluated for their flammability, physical, mechanical, and thermophysical properties, as well as morphological and thermal stability characteristics. The findings revealed a significant reduction in flame spread and smoke suppression; however, the concentration used is not sufficient to achieve the desired rating grades. The thermal insulation capacity of the modified fiber composites was substantially enhanced, particularly with the 40% PHB/DPF-ADP composite displaying the lowest thermal conductivity at 0.0564 W/m.K. Moreover, the presence of gaps and voids at the interface led to a reduction in tensile strength to 4-7 MPa. Additionally, the modified fiber composites exhibited significantly reduced water absorption (~0.76%), attributed to the formation of a highly water-resistant substance containing a furan compound. This work provides a simple and effective approach for achieving durable flame retardancy and long-term thermal insulation performance, offering promising opportunities for the practical application of biobased PHB composites.

Visualizing simultaneous eye-hand movements in a MATLAB dashboard

Eye-hand coordination (EHC) is crucial to our daily activities, and its underlying mechanisms are being intensely studied. The analysis of simultaneous eye and hand movements can provide valuable insights into EHC, particularly for individuals struggling with dexterous control, such as might be caused by stroke or traumatic brain injuries. Despite advancements in motion-capture and eye tracking technologies, there is currently no automated method for visualizing concurrent eye- and hand-movement data. To address this need, we have developed a MATLAB-based dashboard designed for near instantaneous analysis and visualization of eye and hand-tracking data. This paper introduces the design of the dashboard and presents experimental results obtained from its application, leveraging simulated data inspired by our recent work in stroke. This testing suggests that our solution has the potential to significantly aid in understanding and investigating EHC by providing side-by-side and time-locked comparison of eye/hand movements along with their timing and spatio-temporal errors, offering novel opportunities for research and clinical applications.•Continuous eye movement data is collected throughout the experiment•Continuous hand movement data is collected throughout the experiment•Combine datasets and display time-locked eye-hand data in a single dashboard

Research on clustering algorithms based on the Iris dataset

In the burgeoning field of machine learning, clustering algorithms play a quintessential role in uncovering hidden patterns and structures within data. This study commences by highlighting the critical importance of machine learning and the expansive application of clustering algorithms across various disciplines. It then provides a brief background, tracing the development history of clustering algorithms and elucidating the unique characteristics and methodologies inherent to different algorithms. Through empirical analysis conducted on the Iris dataset, this research evaluates the performance of the K-means, hierarchical clustering, and DBSCAN algorithms, leveraging experimental charts and datasets for a nuanced assessment. The comparative analysis reveals distinct advantages and disadvantages of each algorithm, facilitating a balanced discussion on their practical implications. The conclusion synthesizes these findings, offering insights into the comparative merits of the algorithms and suggesting avenues for future research. This investigation aims to deepen the comprehension of the application challenges and opportunities presented by clustering algorithms, thus offering a guiding framework for future explorations in the field.

Unlocking Preclinical Alzheimer's: A Multi-Year Label-Free In Vitro Raman Spectroscopy Study Empowered by Chemometrics.

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods.

Remote Short Sessions of Heart Rate Variability Biofeedback Monitored With Wearable Technology: Open-Label Prospective Feasibility Study.

Heart rate variability (HRV) biofeedback is often performed with structured education, laboratory-based assessments, and practice sessions. It has been shown to improve psychological and physiological function across populations. However, a means to remotely use and monitor this approach would allow for wider use of this technique. Advancements in wearable and digital technology present an opportunity for the widespread application of this approach. The primary aim of the study was to determine the feasibility of fully remote, self-administered short sessions of HRV-directed biofeedback in a diverse population of health care workers (HCWs). The secondary aim was to determine whether a fully remote, HRV-directed biofeedback intervention significantly alters longitudinal HRV over the intervention period, as monitored by wearable devices. The tertiary aim was to estimate the impact of this intervention on metrics of psychological well-being. To determine whether remotely implemented short sessions of HRV biofeedback can improve autonomic metrics and psychological well-being, we enrolled HCWs across 7 hospitals in New York City in the United States. They downloaded our study app, watched brief educational videos about HRV biofeedback, and used a well-studied HRV biofeedback program remotely through their smartphone. HRV biofeedback sessions were used for 5 minutes per day for 5 weeks. HCWs were then followed for 12 weeks after the intervention period. Psychological measures were obtained over the study period, and they wore an Apple Watch for at least 7 weeks to monitor the circadian features of HRV. In total, 127 HCWs were enrolled in the study. Overall, only 21 (16.5%) were at least 50% compliant with the HRV biofeedback intervention, representing a small portion of the total sample. This demonstrates that this study design does not feasibly result in adequate rates of compliance with the intervention. Numerical improvement in psychological metrics was observed over the 17-week study period, although it did not reach statistical significance (all P>.05). Using a mixed effect cosinor model, the mean midline-estimating statistic of rhythm (MESOR) of the circadian pattern of the SD of the interbeat interval of normal sinus beats (SDNN), an HRV metric, was observed to increase over the first 4 weeks of the biofeedback intervention in HCWs who were at least 50% compliant. In conclusion, we found that using brief remote HRV biofeedback sessions and monitoring its physiological effect using wearable devices, in the manner that the study was conducted, was not feasible. This is considering the low compliance rates with the study intervention. We found that remote short sessions of HRV biofeedback demonstrate potential promise in improving autonomic nervous function and warrant further study. Wearable devices can monitor the physiological effects of psychological interventions.

Opportunities and challenges for commercial encryption applications in the Internet of Vehicles

The rapid development of vehicle networking technology has brought broad opportunities for commercial encryption applications, but it is also accompanied by many challenges. As an important guarantee for the information security of the Internet of vehicles, commercial encryption applications have obtained significant development opportunities in terms of technological innovation, market demand and policy support. However, the commercial encryption applications of connected vehicles are also facing challenges such as technical difficulties, lack of standardization, and increasing security threats. This paper aims to deeply analyze the opportunities and challenges of the commercial encryption application of the Internet of vehicles, and put forward corresponding development suggestions, in order to provide reference for the security development of the Internet of vehicles industry.

Broadband silicon nitride integrated polarization rotators at 780 nm

Polarization management, and in particular polarization rotation, is becoming increasingly important for photonic integrated circuits (PICs). While fiber-optic networks are generally polarization insensitive, the large aspect ratio of high-index-contrast PIC waveguides leads to a large polarization-dependent response of integrated components such as waveguides, optical cavities, couplers, etc. Although foundry-processed polarization rotators operating at telecom and datacom wavelengths (C- and O-band) have been demonstrated, to date, there have been few reports of devices operating at shorter wavelengths. This work demonstrates silicon nitride (SiN) polarization rotators operating from λ=700-1000 nm (the I/Z-band) that take advantage of optical coupling between two waveguiding layers in a standard foundry process. We demonstrate a broadband white-light polarization measurement setup that enables precise characterization of the polarization-dependent transmission of photonic waveguide devices. Measurements on foundry-processed devices confirm full TE-to-TM rotation exhibiting a maximum polarization extinction ratio (PER) approaching 20 dB (limited by our measurement setup), and an exceptionally large bandwidth of up to 160 nm with an insertion loss less than 0.2 dB. Beam propagation method (3D-BPM) simulations show good agreement with experimental data and enable the device parameters to be adjusted to accommodate different operating wavelengths and geometries with no changes to the existing foundry process. This work opens up opportunities for applications in quantum information and bio-sensing where operation at λ<1000nm is needed.

A comprehensive experimental study on the effects of hexagonal boron nitride particle size and loading ratio on thermal and mechanical performance in epoxy composites

Harnessing the potential of hexagonal boron nitride (h-BN) in epoxy composites for tailoring thermal conductivity is a promising avenue in materials science. However, achieving balanced enhancements in both in-plane and through-plane directions remains a challenge that requires innovative solutions. The primary objective of this research is to evaluate how thermal and mechanical characteristics of an epoxy matrix are affected by the size and amount of h-BN particles. To achieve this goal, h-BN particles with varying sizes (micro and nano) are incorporated into the epoxy matrix at different weight ratios spanning from 0.5 wt % to 20 wt % using a pre-dispersion technique. The epoxy composites reinforced with h-BN through a molding process exhibits enhanced mechanical and thermal performance in contrast to the pristine epoxy material. During the flexural test, acoustic emission data is collected to identify the initiation and progression of damage within the specimens under testing conditions. The most notable enhancement in thermal conductivity is observed when incorporating 20 wt% of micron-sized h-BN particles. This leads to a remarkable 107% increase in the in-plane direction and an impressive 112% increase in the through-plane direction. These results can be attributed to the formation of a three-dimensional thermally conductive network by the larger h-BN particles, which extends the path of phonon scattering. Furthermore, there are significant improvements in both flexural modulus and tensile modulus. Epoxy composites containing 10 wt% of micron-sized h-BN experiences an approximate 42% increase, while those with 20 wt% of the same particles displays a substantial 47% rise in these properties. This study effectively addresses the challenges associated with tailoring the thermal properties of epoxy composites, opening up new opportunities for applications in various industries, including electronics, aerospace and thermal management systems.

Diffusional Electron Transport Coupled to Thermodynamically Driven Electron Transfers in Redox-Conductive Multivariate Metal-Organic Frameworks.

The development of redox-conductive metal-organic frameworks (MOFs) and the fundamental understanding of charge propagation through these materials are central to their applications in energy storage, electronics, and catalysis. To answer some unresolved questions about diffusional electron hopping transport and redox conductivity, mixed-linker MOFs were constructed from two statistically distributed redox-active linkers, pyromellitic diimide bis-pyrazolate (PMDI) and naphthalene diimide bis-pyrazolate (NDI), and grown as crystalline thin films on conductive fluorine-doped tin oxide (FTO). Owing to the distinct redox properties of the linkers, four well-separated and reversible redox events are resolved by cyclic voltammetry, and the mixed-linker MOFs can exist in five discrete redox states. Each state is characterized by a unique spectroscopic signature, and the interconversions between the states can be followed spectroscopically under operando conditions. With the help of pulsed step-potential spectrochronoamperometry, two modes of electron propagation through the mixed-linker MOF are identified: diffusional electron hopping transport between linkers of the same type and a second channel that arises from thermodynamically driven electron transfers between linkers of different types. Corresponding to the four redox events of the mixed-linker MOFs, four distinct bell-shaped redox conductivity profiles are observed at a steady state. The magnitude of the maximum redox conductivity is evidenced to be dependent on the distance between redox hopping sites, analogous to the situation for apparent electron diffusion coefficients, Deapp, that are obtained in transient experiments. The design of mixed-linker redox-conductive MOFs and detailed studies of their charge transport properties present new opportunities for future applications of MOFs, in particular, within electrocatalysis.

Impedimetric sensor based on molecularly imprinted polythionine from deep eutectic solvent for epinephrine determination

Deep eutectic solvents have obtained growing interest in analytical chemistry due to opportunities related the green chemistry paradigm, i.e., substitution of organic solvents, application of nontoxic ingredients and minimal quantities of wastes formed in their synthesis and usage. In this work, the advantages of deep eutectic solvents were shown in the development of electrochemical sensor for epinephrine determination. Polythionine molecularly imprinted with epinephrine (PTNMIP) was electrodeposited from natural deep eutectic solvent (NADES) consisted of citric acid, glucose, and water in 1:1:6 molar ratio and tested with standard solutions of epinephrine, pharmaceutical preparations, and artificial samples of biological liquids. Only one drop (100 µL) of the monomer dissolved in NADES was applied for sensor preparation on the platform of screen-printed carbon electrode. Electropolymerization was performed by multiple scanning of the potential. The formation of molecular imprints was confirmed by scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). After the template removal, the charge transfer resistance of the surface layer depended on the epinephrine concentration in the range from 100 nM to 316 µM (limit of detection 50 nM). Selectivity of the signal was confirmed against serotonin and norepinephrine commonly present in biological liquids. Sensor was successfully tested for the determination of epinephrine in spiked solutions mimicking influence of the plasma electrolytes, serum proteins, and in real saliva samples. The recoveries calculated for 10 μM epinephrine ranged from 98.3 to 102.6%. Insignificant influence of the additives and stabilizers present in medications was eliminated by sample dilution. Impedimetric sensor developed showed good opportunities for further application in clinical diagnostics, pharmacokinetics studies and medication manufacture control.

Can 2D Semiconductors Be Game-Changers for Nanoelectronics and Photonics?

2D semiconductors have interesting physical and chemical attributes that have led them to become one of the most intensely investigated semiconductor families in recent history. They may play a crucial role in the next technological revolution in electronics as well as optoelectronics or photonics. In this Perspective, we explore the fundamental principles and significant advancements in electronic and photonic devices comprising 2D semiconductors. We focus on strategies aimed at enhancing the performance of conventional devices and exploiting important properties of 2D semiconductors that allow fundamentally interesting device functionalities for future applications. Approaches for the realization of emerging logic transistors and memory devices as well as photovoltaics, photodetectors, electro-optical modulators, and nonlinear optics based on 2D semiconductors are discussed. We also provide a forward-looking perspective on critical remaining challenges and opportunities for basic science and technology level applications of 2D semiconductors.