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Polymer dielectrics with excellent capacitive performance are urgently needed in advanced electrical and electronic systems. However, due to the dramatic increase in the conduction loss, the energy density and efficiency of polymers degrade severely at elevated temperatures, limiting their application in harsh environments up to 150 °C. Herein, an all-organic polyurea (PU)/polyetherimide (PEI) blend film is designed to prepare high-temperature polymer dielectric. It is found that carrier traps can be introduced by blending, and the hydrogen bond between PU and PEI increases the trap depth, leading to suppressed leakage current and enhanced breakdown strength, thus improving the energy storage performance. PU/30%PEI exhibits a high discharged energy density of ∼3.74 J/cm3 with an efficiency higher than 90% at 150 °C, which is 78% and 70% higher than pristine PU and PEI, respectively. This work provides a facile strategy to improve the energy storage performance of polymer dielectrics by introducing deep traps through blending. [ABSTRACT FROM AUTHOR]

In response to a community prediction challenge, we simulate the nonadiabatic dynamics of cyclobutanone using the mapping approach to surface hopping (MASH). We consider the first 500 fs of relaxation following photoexcitation to the S2 state and predict the corresponding time-resolved electron-diffraction signal that will be measured by the planned experiment. 397 ab initio trajectories were obtained on the fly with state-averaged complete active space self-consistent field using a (12,11) active space. To obtain an estimate of the potential systematic error, 198 of the trajectories were calculated using an aug-cc-pVDZ basis set and 199 with a 6-31+G* basis set. MASH is a recently proposed independent trajectory method for simulating nonadiabatic dynamics, originally derived for two-state problems. As there are three relevant electronic states in this system, we used a newly developed multi-state generalization of MASH for the simulation: the uncoupled spheres multi-state MASH method (unSMASH). This study, therefore, serves both as an investigation of the photodissociation dynamics of cyclobutanone, and also as a demonstration of the applicability of unSMASH to ab initio simulations. In line with previous experimental studies, we observe that the simulated dynamics is dominated by three sets of dissociation products, C3H6 + CO, C2H4 + C2H2O, and C2H4 + CH2 + CO, and we interpret our predicted electron-diffraction signal in terms of the key features of the associated dissociation pathways. [ABSTRACT FROM AUTHOR]

Standard approximations for the exchange–correlation functional in Kohn–Sham density functional theory (KS-DFT) typically lead to unacceptably large errors when applied to strongly correlated electronic systems. Partition-DFT (PDFT) is a formally exact reformulation of KS-DFT in which the ground-state density and energy of a system are obtained through self-consistent calculations on isolated fragments, with a partition energy representing inter-fragment interactions. Here, we show how typical errors of the local density approximation (LDA) in KS-DFT can be largely suppressed through a simple approximation, the multi-fragment overlap approximation (MFOA), for the partition energy in PDFT. Our method is illustrated on simple models of one-dimensional strongly correlated linear hydrogen chains. The MFOA, when used in combination with the LDA for the fragments, improves LDA dissociation curves of hydrogen chains and produces results that are comparable to those of spin-unrestricted LDA, but without breaking the spin symmetry. MFOA also induces a correction to the LDA electron density that partially captures the correct density dimerization in strongly correlated hydrogen chains. Moreover, with an additional correction to the partition energy that is specific to the one-dimensional LDA, the approximation is shown to produce dissociation energies in quantitative agreement with calculations based on the density matrix renormalization group method. [ABSTRACT FROM AUTHOR]

It has long been postulated that within density-functional theory (DFT), the total energy of a finite electronic system is convex with respect to electron count so that 2Ev[N0] ≤ Ev[N0 − 1] + Ev[N0 + 1]. Using the infinite-separation-limit technique, this Communication proves the convexity condition for any formulation of DFT that is (1) exact for all v-representable densities, (2) size-consistent, and (3) translationally invariant. An analogous result is also proven for one-body reduced density matrix functional theory. While there are known DFT formulations in which the ground state is not always accessible, indicating that convexity does not hold in such cases, this proof, nonetheless, confirms a stringent constraint on the exact exchange–correlation functional. We also provide sufficient conditions for convexity in approximate DFT, which could aid in the development of density-functional approximations. This result lifts a standing assumption in the proof of the piecewise linearity condition with respect to electron count, which has proven central to understanding the Kohn–Sham bandgap and the exchange–correlation derivative discontinuity of DFT. [ABSTRACT FROM AUTHOR]

For an electronic system, given a mean field method and a distribution of orbital occupation numbers that are close to the natural occupations of the correlated system, we provide formal evidence and computational support to the hypothesis that the entropy (or more precisely −σS, where σ is a parameter and S is the entropy) of such a distribution is a good approximation to the correlation energy. Underpinning the formal evidence are mild assumptions: the correlation energy is strictly a functional of the occupation numbers, and the occupation numbers derive from an invertible distribution. Computational support centers around employing different mean field methods and occupation number distributions (Fermi–Dirac, Gaussian, and linear), for which our claims are verified for a series of pilot calculations involving bond breaking and chemical reactions. This work establishes a formal footing for those methods employing entropy as a measure of electronic correlation energy (e.g., i-DMFT [Wang and Baerends, Phys. Rev. Lett. 128, 013001 (2022)] and TAO-DFT [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)]) and sets the stage for the widespread use of entropy functionals for approximating the (static) electronic correlation. [ABSTRACT FROM AUTHOR]

Continuum solvation models are becoming increasingly relevant in condensed matter simulations, allowing to characterize materials interfaces in the presence of wet electrified environments at a reduced computational cost with respect to all atomistic simulations. However, some challenges with the implementation of these models in plane-wave simulation packages still persists, especially when the goal is to simulate complex and heterogeneous environments. Among these challenges is the computational cost associated with large heterogeneous environments, which in plane-wave simulations has a direct effect on the basis-set size and, as a result, on the cost of the electronic structure calculation. Moreover, the use of periodic simulation cells is not well-suited for modeling systems embedded in semi-infinite media, which is often the case in continuum solvation models. To address these challenges, we present the implementation of a double-cell formalism, in which the simulation cell used for the continuum environment is uncoupled from the one used for the electronic-structure simulation of the quantum-mechanical system. This allows for a larger simulation cell to be used for the environment, without significantly increasing computational time. In this work, we show how the double-cell formalism can be used as an effective periodic boundary conditions correction scheme for nonperiodic and partially periodic systems. The accuracy of the double-cell formalism is tested using representative examples with different dimensionalities, both in vacuum and in a homogeneous continuum dielectric environment. Fast convergence and good speedups are observed for all the simulation setups, provided the quantum-mechanical simulation cell is chosen to completely fit the electronic density of the system. [ABSTRACT FROM AUTHOR]

Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice. In this paper, novel algorithms and software are presented that enable extreme-scale quantum chemistry capabilities with particular emphasis on exascale calculations. This includes the development and application of the multi-Graphics Processing Unit (GPU) library LibCChem 2.0 as part of the General Atomic and Molecular Electronic Structure System package and of the standalone Extreme-scale Electronic Structure System (EXESS), designed from the ground up for scaling on thousands of GPUs to perform high-performance accurate quantum chemistry calculations at unprecedented speed and molecular scales. Among various results, we report that the EXESS implementation enables Hartree–Fock/cc-pVDZ plus RI-MP2/cc-pVDZ/cc-pVDZ-RIFIT calculations on an ionic liquid system with 623 016 electrons and 146 592 atoms in less than 45 min using 27 600 GPUs on the Summit supercomputer with a 94.6% parallel efficiency. [ABSTRACT FROM AUTHOR]

Electronic transitions are observed for the O 2 + –Ar and O 2 + –N2 complexes over the 225–350 nm range. The transitions are not associated with recognized electronic band systems of the respective atomic and diatomic constituents (Ar+, Ar, O 2 + , O2, N 2 + , and N2) but rather are due to charge transfer transitions. Onsets of the O 2 + –Ar and O 2 + –N2 band systems occur at 3.68 and 3.62 eV, respectively, corresponding to the difference in the ionization potentials of Ar and O2 (3.69 eV), and N2 and of O2 (3.51 eV), suggesting the band systems arise from intramolecular charge transfer transitions to states correlating with O2 (X 3 Σ g − ) + Ar+ (2Pu) and O2 (X 3 Σ g − ) + N 2 + (X 2 Σ g + ) limits, respectively. The dominant vibronic progressions have ωe values of 1565 cm−1 for O 2 + –Ar and 1532 cm−1 for O 2 + –N2, reasonably close to the value for the neutral O2 molecule in its X 3 Σ g − state (1580 cm−1). Higher energy band systems for O 2 + –Ar and O 2 + –N2 are assigned to transitions to states correlating with the O2 (a1Δg) + Ar+ (2Pu) and O2 (a1Δg) + N 2 + (X 2 Σ g + ) limits, respectively. [ABSTRACT FROM AUTHOR]

In this paper, we present an extended dissipaton equation of motion for studying the dynamics of electronic impurity systems. Compared with the original theoretical formalism, the quadratic couplings are introduced into the Hamiltonian accounting for the interaction between the impurity and its surrounding environment. By exploiting the quadratic fermionic dissipaton algebra, the proposed extended dissipaton equation of motion offers a powerful tool for studying the dynamical behaviors of electronic impurity systems, particularly in situations where nonequilibrium and strongly correlated effects play significant roles. Numerical demonstrations are carried out to investigate the temperature dependence of the Kondo resonance in the Kondo impurity model. [ABSTRACT FROM AUTHOR]

Herein, a novel enhancement-mode (E-mode) GaN-based p-channel FETs (p-FETs) with a linearly graded AlGaN (LGA) p-channel is proposed and numerically studied by Silvaco TCAD. Thanks to strong polarization-induced doping, three-dimensional hole gas (3DHG) can be uniformly generated in LGA to form a continuous p-channel with a hole concentration over 1018 cm–3. Combined with an optimized recessed gate structure, the LGA p-FET can simultaneously achieve a large threshold voltage (| V TH|) > 2 V and a high current density (| J DS|) of ∼10 mA mm−1 at V DS = −10 V. Additionally, two critical parameters of the LGA p-FETs, i.e. the depth of recessed gate and initial Al composition of LGA, are specifically studied to reveal the unique carrier behavior of 3DHG in the devices. Importantly, the LGA structure is further optimized and implemented as the p-type cap layer to construct an E-mode GaN n-FET. Thereby, based on the same LGA configuration, a GaN-based inverter with the matched complementary n- and p-FETs is monolithically constructed, showing sharp voltage transition. The reported novel LGA structure and its availability in both GaN-based E-mode n- and p-FETs provides valuable insights and guidance to construct highly efficient GaN p-type devices and All-GaN-based integrated circuits for compact power electronic systems. [ABSTRACT FROM AUTHOR]

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Background: It has been proposed that prolonged use of anti-inflammatory and anti-fibrotic drugs diminish the probability of development of lung fibrosis. Prolonged low-dose corticosteroid may prevent remodeling of the lung in survivors. Pirfenidone and colchicine may exhibit anti-fibrotic and anti-inflammatory properties as well. Methods: This retrospective observational study was conducted at post COVID-19 clinic, Mansoura University Hospitals, during the period between October 2020 and March 2022. This study included 104 patients who had COVID-19 pneumonia confirmed either by RT-PCR or radiologically by CT scan and divided into 3 groups; group A (corticosteroids only) included 33 (31.7%) patients, group B (corticosteroids and colchicine) included 56 (53.8%) patients, and group C (corticosteroids, colchicine, and pirfenidone) included 15 (14.4%) patients. All patients were assessed during follow-up visits in post COVID-19 clinic 1 and 3 months after discharge by evaluation of resting SpO2, spirometry, and radiological assessment. Patients' data during hospitalization was collected from hospital electronic systems. Results: There was non-statistically significant improvement in FEV1 in group A while there was statistically significant improvement in FEV1 in groups B and C (P value = 0.002 and 0.041, respectively) 1 month and 3 months after discharge. Group B exhibited more statistically significant improvement in FVC as well compared to group C (P value = 0.003 and 0.025, respectively) while group A showed non-statistically significant improvement in FVC. There was a statistically significant decrease in CT severity score in all the groups during follow-up with P value < 0.001 in groups A and B and to less extent less statistically significant decrease in group C comparing the 3 groups to each other. Conclusion: The use of colchicine added to corticosteroids after acute phase of COVID-19 pneumonia resulted in statistically significant improvement regarding functional and radiological changes during follow-up when compared to corticosteroids alone. The addition of pirfenidone (which is a relatively expensive drug) to corticosteroids and colchicine did not add more statistically significant improvement in functional or radiological changes. [ABSTRACT FROM AUTHOR]

For the first time, mathematical models for evaluating biomedical images were obtained using fuzzy set methods on the basis of expert knowledge bases, thus making it possible to carry out complex qualitative diagnostics and increase the reliability and efficiency of diagnosis. A methodology for analyzing biomedical images was formed based on the fuzzy set apparatus, which allowed a fuller assessment of the level of disease for glaucoma patients. Aspects of the practical implementation of the optical–electronic system for biomedical information processing were considered. An algorithm and an optical–electronic system for biomedical image analysis are proposed, and they can be used to increase the informativeness and reliability in the diagnosis of eye pathologies and glaucoma in particular. [ABSTRACT FROM AUTHOR]

Virtual Prototypes (VPs) at the Electronic System Level (ESL) are being increasingly adopted by the semiconductor industry and play an important role in modernizing the System-on-Chips (SoCs) design flow to raise design productivity and reduce time-to-market constraints. Due to their early availability and significantly faster simulation speed in comparison to Register Transfer Level (RTL) designs, VPs are used as reference models for lower levels of abstraction. Leveraging VPs and extending their use cases for early security validation are shown as a promising direction. As the cost of fixing any security flaws increases with the stage of development, VP-based security validation can significantly avoid costly iterations. In this article, we present a novel VP-based dynamic information flow analysis approach at the ESL, consisting of three main phases which are runtime behavior extraction (in terms of transactions), transactions transformation, and security validation. The proposed approach empowers designers to validate the information flow policies of a given VP-based SoC against the most occurring security threat models which are information leakage (confidentiality) and unauthorized access to data in a memory (integrity). Experimental results including an extensive set of standard benchmarks and two real-world VP-based SoCs demonstrate the scalability and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

As the demand for miniaturization of thermal management systems for electronic devices rises, numerous researchers are dedicating their efforts to the study of single-phase forced convective heat transfer (FCHT) within nanoscale channels. However, investigating FCHT in nanochannels (FCHT-NC) using experimental and theoretical methods is challenging. Alternately, molecular dynamics (MD) simulations have emerged as a unique and powerful technique in recent years. This paper presents a comprehensive review of the application of the MD simulation method in the study of FCHT-NC. Firstly, the current paper reviews various simulation techniques and models, along with their associated primary parameters employed in FCHT-NC, through a detailed and systematic literature survey and critical analysis. Evaluating the current methods and discussing their limitations provide helpful guidelines for future studies. Furthermore, based on the existing literature in the MD simulation, this review outlines all influencing parameters on the performance of FCHT-NC, covering their effects and discussing underlying mechanisms. Finally, key challenges and future research directions are summarized in this review, thereby providing essential support for researchers seeking to apply the MD simulation method to investigate FCHT-NC. [ABSTRACT FROM AUTHOR]

Under fatigue load, insulated gate bipolar transistor (IGBT) experience structural damage and performance degradation, imparting the reliability of power electronic systems. To address this, the relationship between solder layer fatigue crack length and thermal resistance is derived based on heat transfer theory, firstly. The Darveaux model is used to characterize the evolution law of solder layer cracks in IGBT, and a new IGBT performance degradation model along with a method for estimating its undetermined coefficients is proposed. Then, considering the non-stationary characteristics of actual working conditions, a variable amplitude fatigue load model for IGBT is established using the response surface methodology. The rain flow counting method and linear cumulative damage citation are then employed to assess the extent of IGBT performance degradation. Finally, using a type of IGBT product as an example, power cycling thesis are conducted, and performance degradation modeling and analysis are carried out based on experimental data, verifying the effectiveness of the models and algorithms. [ABSTRACT FROM AUTHOR]

Introduction Electronic nicotine-delivery systems (ENDS) can reduce tobacco-related health risks for adults who smoke cigarettes (AWS) by facilitating complete switching away from cigarettes. However, little is known about ENDS use and switching among subpopulations that have been disproportionately affected by smoking. Aims and Methods AWS (age ≥ 21 years) were recruited following their first purchase of a JUUL Starter Kit in 2018. Participants who self-reported switching (no past-30-day cigarette smoking) at 1-, 2-, 3-, 6-, 9-, 12-, 15-, 18-, 21-, and 24-month follow-ups. Percent switched and percent with substantial smoking reduction (≥50% decrease in cigarettes per day among those who continued smoking) were calculated. Analyses focused on racial and ethnic minorities, persons with low income and education levels, sexual minorities, and those with mental and physical health conditions. Results Overall rates of switching away from cigarettes increased across follow-ups to 51.2% (month-12) to 58.6% (month-24, 87% of whom used ENDS). Among those who continued to smoke at 24 months, 45.4% reduced cigarettes per day by ≥ 50%. Rates of switching and substantial smoking reduction were largely similar across subgroups, with some statistically significant, but small, differences in month-24 switching rates (eg, education, mental and physical health conditions; switch rate range: 42%–57%). Conclusions AWS demonstrated progressively increasing switching rates over 2 years after purchasing JUUL products. Similar trends in switching and smoking reduction were observed across populations disproportionately affected by smoking. By facilitating switching and smoking reduction, ENDS products such as JUUL may provide an opportunity to reduce smoking-related harm among some populations disproportionately affected by smoking, potentially reducing tobacco-related health disparities. Implications ENDS have the potential to benefit population health if they can replace cigarettes. This benefit must extend to populations disproportionately affected by smoking. In this real-world study, 59% of JUUL purchasers reported complete switching 2 years later (no past-30-day smoking, with most continuing to use ENDS). Furthermore, 45% of those who continued to smoke reduced cigarette consumption by at least half. These rates of switching and smoking reduction were largely comparable across populations disproportionately affected by smoking (defined, eg, by ethnicity and income). ENDS can serve as an effective harm reduction strategy to complement current efforts to reduce tobacco-related disparities. [ABSTRACT FROM AUTHOR]

As the foundation of circuits and electronic systems, the quality of printed circuit boards (PCBs) is directly related to the reliability of the whole system. At present, deep learning-based target detection technology has a broad application prospect in PCB defect detection. However, there are still some shortcomings in the process of detection. For example, the detection speed is slow, and the detection accuracy is not ideal for defects with small size. Therefore, this paper proposes an improved algorithm based on the YOLOv5s model to improve the detection of PCB defects. The algorithm enhances the connection between the shallow and high layers of the network by improving the backbone network structure. Meanwhile, a self-attention mechanism is introduced into YoloHead to enhance the feature extraction and the ability to focus on the global information of the feature map, and the self-attention mechanism is optimized by combining the computational characteristics of the SENet, the CBAM and the residual unit. While improving the accuracy of PCB defect detection, better computational efficiency is ensured. In subsequent experiments, this paper trains and tests the improved YOLOv5s algorithm using publicly available PCB defect datasets. The results show that the algorithm achieves a detection rate of 39.7 frames per second and a maximum average precision of 96.14%, which is a 4.68% improvement over the original YOLOv5s. [ABSTRACT FROM AUTHOR]

Lightweight, electrically insulating and high thermally conductive materials are highly desirable in electronic and power systems because they can effectively transfer heat and avoid temperature rise of the equipment and devices, thus guaranteeing normal operation. In this work, silica-coated spherical boron nitride (SiO2@s-BN) was successfully fabricated and prepared as a thermally conductive composite by blending with silicone rubber (SR). Due to the modulus matching, SiO2@BN could decrease the thermal resistance between the SR matrices and the thermally conductive fillers, thus achieving higher thermal conductivity compared with the original BN at the same filler loading. When the SR composite is filled with 40 wt% SiO2@BN, the thermal conductivity can reach 1.2 W m−1 K−1, which is 16.5% higher than that of the 40 wt% s-BN/SR composite. Simultaneously, the 40 wt% SiO2@BN/SR composite material not only exhibits excellent dielectric, thermal, and mechanical properties but also demonstrates outstanding processability, maintaining a low precursor viscosity of only 14.5 Pa·s. Overall, this work provides a novel strategy for developing high thermally conductive SR composites with good processability. [ABSTRACT FROM AUTHOR]

This article explores the implementation of a digital verification system known as Electronic Visit Verification (EVV) across homecare services for older and disabled adults within the US Medicaid program. EVV systems are used to conduct daily check-ins through GPS tracking and biometric identity verification. While touted as a means to identify and deter "fraud, waste, and abuse," the digital monitoring also generates detailed data trails on the lives and habits of service recipients, as well as constraining their daily movements. Drawing on qualitative interviews with workers and clients, I argue that this case study calls attention to how harms from digitalization of social welfare provision emerge from workplace surveillance and labor management, and how EVV becomes a tool for more finely tuning classifications of different types of paid and unpaid care. The burdensome digital compliance hurdles reinforced older employment tensions between the state, care workers, and public benefits recipients. [ABSTRACT FROM AUTHOR]

Electrical triggering of a metal-insulator transition (MIT) often results in the formation of characteristic spatial patterns such as a metallic filament percolating through an insulating matrix or an insulating barrier splitting a conducting matrix. When MIT triggering is driven by electrothermal effects, the temperature of the filament or barrier can be substantially higher than the rest of the material. Using X-ray microdiffraction and dark-field X-ray microscopy, we show that electrothermal MIT triggering leads to the development of an inhomogeneous strain profile across the switching device, even when the material does not undergo a pronounced, discontinuous structural transition coinciding with the MIT. Diffraction measurements further reveal evidence of unique features associated with MIT triggering including lattice distortions, tilting, and twinning, which indicate structural nonuniformity of both low-and high-resistance regions inside the switching device. Such lattice deformations do not occur under equilibrium, zero-voltage conditions, highlighting the qualitative difference between states achieved through increasing temperature and applying voltage in nonlinear electrothermal materials. Electrically induced strain, lattice distortions, and twinning could have important contributions in the MIT triggering process and drive the material into nonequilibrium states, providing an unconventional pathway to explore the phase space in strongly correlated electronic systems. [ABSTRACT FROM AUTHOR]

In order for full utilization of the switching devices and safe continued operation of the power converter at the same time, the junction temperature of the switching devices needs to be accurately monitored without shutting down the motor drive. This paper derives an analytical junction temperature calculation method by using Laplace transformation and thermal network theory. Based on an actual motor drive, a simulation model is established using platform for power electronic systems (PLECS). Through comparison, the derived method is proven to be able to calculate junction temperature accurately. [ABSTRACT FROM AUTHOR]

This paper is devoted to the application of object localization and identification with information combined from a radar system and a dedicated portable/mobile electronic device equipped with a global positioning system (GPS) receiver. This device is able to provide object's (staff member, and staff vehicle) rough location and identification. Such systems are required in very restrictive security areas like airports (e.g., open-air area and apron). Currently, the outdoor area of the airport is typically protected by a surveillance system operated by security guards. Surveillance systems are composed of different sensors, video and infrared cameras, and microwave radars. The sheer number of events generated via the system can lead to fatigue among staff, potentially resulting in the omission of critical events. To address this issue, we propose an electronic system equipped with a wireless module and a GPS module. This approach enables automatic identification of objects through the fusion of data from two independent systems (GPS and radar). The radar system is capable of precisely localizing and tracking objects, while the described system is able to identify registered objects. This paper contains a description of the subsystems of a portable/mobile electronic device. The fusion of information from the proposed system (rough location and identification) with the precise location obtained from short-range radar is intended to reduce the number of false alerts in the surveillance system. [ABSTRACT FROM AUTHOR]

Digital Twins (DT) play a key role in Industry 4.0 applications, and the technology is in the process of being mature. Since its conceptualisation, it has been heavily contextualised and often misinterpreted as being merely a virtual model. Thus, it is crucial to define it clearly and have a deeper understanding of its architecture, workflow, and implementation scales. This paper reviews the notion of a Digital Twin represented in the literature and analyses different kinds of descriptions, including several definitions and architectural models. A new fit-for-all definition is proposed which describes the underlying technology without being context-specific and also overcomes the pitfalls of the existing generalised definitions. In addition, the existing three-dimensional and five-dimensional models of the DT architecture and their characteristic features are analysed. A new simplified two-branched model of DT is introduced, which retains a clear separation between the real and virtual spaces and outlines the latter based on the two key modelling approaches. This model is then extended for condition monitoring of electronic components and systems, and a hybrid approach to Prognostics and Health Management (PHM) is further elaborated on. The proposed framework, enabled by the two-branched Digital Twin model, combines the physics-of-degradation and data-driven approaches and empowers the next generation of reliability assessment methods. Finally, the benefits, challenges, and outlook of the proposed approach are also discussed. [ABSTRACT FROM AUTHOR]

A long-standing research goal is to develop computing technologies that mimic the brain's capabilities by implementing computation in electronic systems directly inspired by its structure, function, and operational mechanisms, using low-power, spike-based neural networks. The Loihi neuromorphic processor provides a low-power, large-scale network of programmable silicon neurons for brain-inspired artificial intelligence applications. This paper exploits the Loihi processors and a theory-guided methodology to enable unsupervised learning of spike patterns. Our method ensures efficient and rapid selection of the network's hyperparameters, enabling the neuromorphic processor to generate attractor states through real-time unsupervised learning. Precisely, we follow a fast design process in which we fine-tune network parameters using mean-field theory. Moreover, we measure the network's learning ability regarding its error correction and pattern completion aptitude. Finally, we observe the dynamic energy consumption of the neuron cores for each millisecond of simulation equal to 23 μ J/time step during the learning and recall phase for four attractors composed of 512 excitatory neurons and 256 shared inhibitory neurons. This study showcases how large-scale, low-power digital neuromorphic processors can be quickly programmed to enable the autonomous generation of attractor states. These attractors are fundamental computational primitives that theoretical analysis and experimental evidence indicate as versatile and reusable components suitable for a wide range of cognitive tasks. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in the prevalence of electronic wearables, among which flexible magnetoelectronic skin has emerged as a key component. This technology is part of the rapidly progressing field of flexible wearable electronics, which has facilitated a new human perceptual development known as the magnetic sense. However, the magnetoelectronic skin is limited due to its low sensitivity and substantial field limitations as a wearable electronic device for sensing minor magnetic fields. Additionally, achieving efficient and non-destructive delamination in flexible magnetic sensors remains a significant challenge, hindering their development. In this study, we demonstrate a novel magnetoelectronic touchless interactive device that utilizes a flexible giant magnetoresistive sensor array. The flexible magnetic sensor array was developed through an electrochemical delamination process, and the resultant ultra-thin flexible electronic system possessed both ultra-thin and non-destructive characteristics. The flexible magnetic sensor is capable of achieving a bending angle of up to 90 degrees, maintaining its performance integrity even after multiple repetitive bending cycles. Our study also provides demonstrations of non-contact interaction and pressure sensing. This research is anticipated to significantly contribute to the advancement of high-performance flexible magnetic sensors and catalyze the development of more sophisticated magnetic electronic skins. [ABSTRACT FROM AUTHOR]

The rapid advancements in nucleic acid-based electrochemical sensors for implantable and wearable applications have marked a significant leap forward in the domain of personal healthcare over the last decade. This technology promises to revolutionize personalized healthcare by facilitating the early diagnosis of diseases, monitoring of disease progression, and tailoring of individual treatment plans. This review navigates through the latest developments in this field, focusing on the strategies for nucleic acid sensing that enable real-time and continuous biomarker analysis directly in various biofluids, such as blood, interstitial fluid, sweat, and saliva. The review delves into various nucleic acid sensing strategies, emphasizing the innovative designs of biorecognition elements and signal transduction mechanisms that enable implantable and wearable applications. Special perspective is given to enhance nucleic acid-based sensor selectivity and sensitivity, which are crucial for the accurate detection of low-level biomarkers. The integration of such sensors into implantable and wearable platforms, including microneedle arrays and flexible electronic systems, actualizes their use in on-body devices for health monitoring. We also tackle the technical challenges encountered in the development of these sensors, such as ensuring long-term stability, managing the complexity of biofluid dynamics, and fulfilling the need for real-time, continuous, and reagentless detection. In conclusion, the review highlights the importance of these sensors in the future of medical engineering, offering insights into design considerations and future research directions to overcome existing limitations and fully realize the potential of nucleic acid-based electrochemical sensors for healthcare applications. [ABSTRACT FROM AUTHOR]

The objective of this work is to analyze and compare AC microgrid (ACMG) solutions to introduce the topic to new researchers. The methodology used to achieve this goal is a systematic literature review using five questions: (1) How have ACMGs evolved in five years? (2) What are the standards for ACMGs? (3) What are the different schemes for connecting MGs to the utility grid? (4) What are the different control schemes in ACMGs? (5) What is an appropriate way to compare results when working with ACMGs? The articles were published in Q1/Q2 journals as based on either the Scimago Journal Rank (SJR) and/or the Journal Citation Report (JCR) between 2018 and 2022 and were from three databases: (1) Web of Science (WoS), (2) Scopus, and (3) IEEE Xplore. Publications not describing pure ACMGs, review papers, publications not related to the questions, and papers describing work that did not meet a quality assessment were excluded, resulting in 34 articles being included in this review. Results show: (1) the energy sources and AC bus nature of microgrids over five years, (2) the identification and quantification of cited standards for microgrids, (3) the pros and cons of different schemes for connecting an AC microgrid to the main grid, (4) the control schemes, classified in a hierarchical control structure, and (5) the simulation tools and experimental benches used in microgrids. Most studies considered a generic energy source and a low-voltage three-phase AC bus, 16 standards were found, and the most cited standard was IEEE Standard 1547. The most common connection scheme to the utility grid was a direct connection, most of the works proposed a modification to a hierarchical control system scheme, and the most common simulation tool was MATLAB. The preferred experimental setup consisted of parallel inverters for testing a control scheme, a prototype when proposing a power electronic system, and a laboratory microgrid for testing fault detection methods. [ABSTRACT FROM AUTHOR]

The integrity of electronic voting systems is critical in safeguarding the democratic process worldwide. This study addresses the twin challenges of bribery and coercion that undermine most existing electronic voting systems. Recognizing the limitations of current security measures, which fail to protect voter autonomy even after the disclosure of voting secrets, we propose an innovative level-five secure e-voting system. By integrating an additional setup phase, our system maintains voter volition, ensuring security even when key secrets are compromised. Utilizing cryptographic techniques, blind signatures, and subliminal channels in conjunction with smart card PIN mechanisms, our approach not only bolsters system security but also enhances its potential for widespread adoption. This work underscores the importance of advanced cryptographic methods in developing coercion-resistant electronic voting systems that prioritize voter privacy and choice. [ABSTRACT FROM AUTHOR]

With the rapid development of electronic power systems, DC-DC converters are widely used, including the Four-Switch Buck–Boost (FSBB) converter, which has a unique advantage in scenarios with a wide range of voltage inputs. To improve the response speed and anti-interference capability of the FSBB converter, this paper proposes an adaptive global fast integral terminal sliding mode control method. Through an in-depth analysis of the fundamental characteristics of the FSBB converter, this study employed a global fast integral terminal sliding mode controller combined with an adaptive algorithm to significantly improve the dynamic performance and robustness of the FSBB converter. The simulation and experimental results show that the proposed method could track the reference voltage quickly and accurately in different modes, exhibiting excellent system robustness compared to conventional sliding mode control, terminal sliding mode control, and PID control methods. [ABSTRACT FROM AUTHOR]

Brain‐inspired parallel computing is increasingly considered a solution to overcome memory bottlenecks, driven by the surge in data volume. Extensive research has focused on developing memristor arrays, energy‐efficient computing strategies, and varied operational mechanisms for synaptic devices to enable this. However, to realize truly biologically plausible neuromorphic computing, it is essential to consider temporal and spatial aspects of input signals, particularly for systems based on the leaky integrate‐and‐fire model. This review highlights the significance of neuromorphic computing and outlines the fundamental components of hardware‐based neural networks. Traditionally, neuromorphic computing has relied on two‐terminal devices such as artificial synapses. However, these suffer from significant drawbacks, such as current leakage and the lack of a third terminal for precise synaptic weight adjustment. As alternatives, three‐terminal synaptic devices, including memtransistors, ferroelectric, floating‐gate, and charge‐trapped synaptic devices, as well as optoelectronic options, are explored. For an accurate replication of biological neural networks, it is vital to integrate artificial neurons and synapses, implement neurobiological functions in hardware, and develop sensory neuromorphic computing systems. This study delves into the operational mechanisms of these artificial components and discusses the integration process necessary for realizing biologically plausible neuromorphic computing, paving the way for future brain‐inspired electronic systems. [ABSTRACT FROM AUTHOR]

Polymeric composites with boron nitride nanosheets (BNNs), which are thermally conductive yet electrically insulating, have been pursued for a variety of technological applications, especially those for thermal management in electronic devices and systems. Highlighted in this review are recent advances in the effort to improve in-plane thermal transport performance in polymer/BNNs composites and also the growing research activities aimed at composites of enhanced cross-plane or isotropic thermal conductivity, for which various filler alignment strategies during composite fabrication have been explored. Also highlighted and discussed are some significant challenges and major opportunities for further advances in the development of thermally conductive composite materials and their mechanistic understandings. [ABSTRACT FROM AUTHOR]

This study presents methods to handle deep learning regressions with input and output sequences of different lengths. We discuss the Autoregressive one-step prediction framework and introduce an innovative one-time multi-step (OTMS) prediction approach, based on a custom loss function, that predicts all future steps in a single shot. The presented methodologies are then applied to simultaneously predict the State of Health (SoH) trajectory and estimate the Remaining Useful Life (RUL) of lithium-ion battery cells. Accurate estimates of SoH trajectory and RUL are essential for Battery Management Systems (BMSs), electronic systems that guarantee safety while maximizing performance and extending battery lifespan. In this context, the studied methodologies were compared using a rigorous cross-validation approach. The OTMS model showed better predictions in early cycles, while the Autoregressive model performed better in later cycles, suggesting a hybrid approach between these two methodologies as an optimal solution. [ABSTRACT FROM AUTHOR]

Copyright of Bodenkultur: Journal for Land Management, Food & Environment is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Heterogeneous integration is a key driver within the field of advanced electronic packaging. The realization of tomorrow's highly integrated electronic systems depends on the combination and compatibility of various integration technologies at the same hierarchy level. The adoption of novel bonding technologies for a cost-effective realization of multi-chiplet systems is a key aspect. Cu nanowire (NW) interconnects exhibit distinct advantages in terms of their scalability down to a few micrometers, the resulting joint properties and moderate demands with respect to the surface preparation, and the cleanliness of the bonding environment. No solder or flux is required for the bonding process, but the NW bumps still can compensate low height differences. The bonding process can be carried out near room temperature under ambient conditions. We demonstrate the technological possibility to integrate the Cu-NWs for a bump processing scheme including the Cu seed etching on 300 mm wafer for the first time. This paper focuses on the microstructure evaluation and the shear test of the formed Cu-NW interconnects fabricated under ambient conditions within a few seconds. The microstructure analysis shows the intact bonded interconnects and reveals high-resolution details of Cu-NWs. The shear strength of the formed interconnects varies between 4.6 MPa and 90.5 MPa depending on the bonding and annealing conditions. Overall, the results of this study highlight the potential of Cu-NW interconnects for future 3D heterogeneous system integration. [ABSTRACT FROM AUTHOR]

For confidential and sensitive electronic documents within enterprises and organizations, failure to conduct proper checks before sending can easily lead to incidents such as security degradation. Sensitive information transmission has become one of the main ways of internal data leakage. However, existing methods or systems cannot extract hidden data and do not support mining the binary structure of hidden information in files. In this paper, an expert system for mining electronic document hidden information is designed for various office documents, compressed files, and image files. This system can quickly mine various forms of concealment in more than 40 common types of electronic documents and extract hidden information, such as file type tampering, encryption concealment, structure concealment, redundant data concealment, etc. Additionally, feature information in the binary structure of the document is extracted to form a feature information base. Subsequently, an expert knowledge base is constructed. Finally, a hidden information mining engine is designed using the knowledge base to realize the security control of corresponding outgoing files with good expansibility and integration. By controlling the exit of documents through scanning for sensitive information contained within them, the security level contents can be obtained effectively, avoiding data leakage by technical means while also facilitating forensics. The actual test result proves that this system can quickly mine various means used to conceal information, extract their respective information, and provide a fast, practical diagnostic way for outgoing control over these electronic documents. [ABSTRACT FROM AUTHOR]

α particles must be monitored to be managed as radioactive diagnostic agents or nuclear activity indicators. The new generation of perovskite detectors suffer from limited energy resolution, which affects spectroscopy and imaging applications. Here, we report that the solution-grown CsPbBr3 crystal exhibits a low and stable dark current (34.6 nA·cm−2 at 200 V) by thinning the as-grown crystal to decrease the high concentration CsPb2Br5 phase near the surface. The introduction of the Schottky electrode for the CsPbBr3 detector further reduces the dark current and improves the high-temperature stability. An energy resolution of 6.9% is achieved with the commercial electronic system, while the effects of air scattering and absorption are investigated. Moreover, 1.1% energy resolution is recognized by a full-customized readout application-specific integrated circuit without any additional signal processing, which matches well with the given parameters of the CsPbBr3 detector by reducing the parasitic capacitance and electronic noise. By developing a synergistic strategy of thinning the perovskite crystal, employing Schottky electrode and full-customised readout application specific integrated circuit to supress dark current and electronic noise, the authors report an energy resolution of 1.1% for perovskite α-particle detector. [ABSTRACT FROM AUTHOR]

Integrated photonics is a cutting-edge field that merges optics and electronics on a single microchip, revolutionizing how we manipulate and transmit light. Imagine traditional bulky optical systems condensed onto a chip smaller than a fingernail, enabling faster communication, more efficient sensors, and advanced computing. At its core, integrated photonics relies on guiding light through waveguides etched onto semiconductor substrates, analogous to how wires conduct electricity in traditional electric circuits. These waveguides can route, modulate, and detect light signals with unprecedented precision and speed. This technology holds immense promise across various domains. Despite its immense potential, integrated photonics faces challenges, including manufacturing complexities and integration with existing electronic systems. However, ongoing research and advancements continue to push the boundaries, promising a future where light-based technologies seamlessly integrate into our everyday lives, powering a new era of innovation and connectivity. [ABSTRACT FROM AUTHOR]

Ni‐CeO2 nanoparticles (NPs) are promising nanocatalysts for water splitting and water gas shift reactions due to the ability of ceria to temporarily donate oxygen to the catalytic reaction and accept oxygen after the reaction is completed. Therefore, elucidating how different properties of the Ni‐Ceria NPs relate to the activity and selectivity of the catalytic reaction, is of crucial importance for the development of novel catalysts. In this work the active learning (AL) method based on machine learning regression and its uncertainty is used for the global optimization of Ce(4‐x)NixO(8‐x) (x = 1, 2, 3) nanoparticles, employing density functional theory calculations. Additionally, further investigation of the NPs by mass‐scaled parallel‐tempering Born‐Oppenheimer molecular dynamics resulted in the same putative global minimum structures found by AL, demonstrating the robustness of our AL search to learn from small datasets and assist in the global optimization of complex electronic structure systems. [ABSTRACT FROM AUTHOR]

Self-healing (SH) in metallized polypropylene film capacitors (MPPFCs) can lead to irreversible damage to electrode and dielectric structures, resulting in capacitance loss and significant stability degradation, especially under cumulative SH conditions. To enhance the reliability assessment of MPPFCs post-SH, this study conducted SH experiments on MPPFCs, examined the damage patterns of the electrodes and dielectric films, and proposed a novel capacitance evaluation method for MPPFCs under cumulative SH conditions. The results reveal that with increasing SH voltage, the number of dielectric layers experiencing single SH breakdowns rises, SH energy significantly escalates, and the loss area of the electrode due to high-temperature evaporation expands. Under cumulative SH conditions, the number of SH events is linearly correlated with the total number of SH-breakdown film layers and shows an exponential decay with the average single SH energy. By utilizing a Support Vector Machine (SVM) to classify the SH condition and damage features within the capacitor based on the correlation and distribution patterns of SH feature parameters, this study introduces an advanced method for evaluating the capacitance of MPPFCs under cumulative SH conditions. This method promises to improve the predictive maintenance and reliability of power electronic systems utilizing MPPFCs. [ABSTRACT FROM AUTHOR]

Organic–inorganic 2D heterostructures combine the high optical absorption of organic molecules with exciton‐dominated optical properties in layered transition metal dichalcogenides (TMDs) such as MoS2. Critical to the interaction and the optical response in such hybrid systems is the electronic band alignment at the interface between the two species. Here, the coupling of monolayers of perylene derivatives is investigated with bilayer MoS2. In particular, variation in the perylene orientation on the MoS2 surface is identified using Raman spectroscopy and scanning probe microscopy. Low‐temperature optical spectroscopy reveals orientation‐dependent interlayer exciton formation. Furthermore, power‐dependent photoluminescence measurements provide insight into the modified interlayer charge transfer in these heterostructures. A saturation of interlayer states is found under high excitation power when the perylene molecules are in a perpendicular orientation to the surface that leads to electron accumulation in the MoS2, whereas parallel alignment of the perylene molecules leads to enhanced populations of organic–inorganic interlayer excitons. This work provides insights into the optimization of organic–inorganic heterostructures, with particular relevance to applications for optoelectronic and excitonic devices. [ABSTRACT FROM AUTHOR]

Lightweight electronic packaging that provides mechanical protection, cooling ability, and customizable electromagnetic interference (EMI) shielding effectiveness (SE) is needed for next-generation electronics. Although electronic packaging solutions with excellent EMI SE exist, there is limited research on how hierarchical design can modulate the EMI SE of an electronic packaging material on demand. In this study, the deliberate precise micro/macrostructure design of graphite-based materials using magnetically assisted 3D printing allows tuning of the EMI SE in the X band (8–12 GHz), leading to a maximum total shielding performance of 90 dB. Aligning high-density graphite microplatelets during 3D printing also remarkably amplified the total SE by 200%. Subsequently, rationally designing the oriented microstructure within a geometrical shape increases the reflection and improves the EMI SE from 40 to 60 dB in a specific direction. Our proof-of-concept samples demonstrate the potential of precise micro/macrostructure design for customizing and enhancing electronic packaging's EMI SE while achieving good heat dissipation and mechanical protection using a versatile 3D printing method. These advances pave the way for more reliable and safer electronic systems. Magnetically assisted 3D printing allows customizable electromagnetic interference (EMI) shielding effectiveness (SE). Aligning high-density graphite microplatelets during the 3D printing parallel or perpendicularly to incident waves leads to their tailored reflection and transmission. Designing the micro/macrostructure of materials allows customization and enhancement of electronic packaging's EMI SE while achieving good heat dissipation and mechanical protection. These advances pave the way for more reliable and safer electronic systems. [ABSTRACT FROM AUTHOR]

Copyright of Çalışma ve Toplum is the property of Calisma ve Toplum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the advancements in electronic systems, efficient cooling has become an exciting task in thermal grounds. For optimum working conditions of electronic systems energy-efficient a heat sink is used. In the present paper, thermal simulation is carried out on two different profiles of existing heat sinks used in the processor. Six different cases were studied and compared namely natural and forced convection on circular and rectangular heat sinks with and without FGM (Functionally Graded Materials.) Conventional material aluminium alloy 6061 and functionally graded material AlSi10Mg are used to understand the variation of temperature of the heat sink by applying the necessary boundary conditions for the heat sink profile. The energy model and finite volume method have been used for investigation using ANSYS software. In comparison between the two heat sink profiles, it is witnessed that the circular heat sink dissipates more heat. From the thermal analysis, it is found that using FGM will improve the heat transfer rate, and the temperature variation is found to be 3oC in comparison with conventional material because FGM is inhomogeneous materials consisting of two or more materials. [ABSTRACT FROM AUTHOR]

Electrical isolation devices are essential components for safeguarding the reliability of electronic systems under harsh conditions. Digital isolators are widely used in low-power circuits due to their high immunity to disturbances. In this paper, a capacitive digital isolator for high-efficiency power supply scenarios is proposed with a high common-mode transient immunity (CMTI) and high data transmission rate. The on–off keying (OOK) modulation technique is used to ensure a high speed and accurate signal transmission. A fully integrated high-voltage level-shift driver with an ns-scale delay is proposed for increasing the drive capacity. Post-simulation results in Cadence IC 6.1.7 with the standard 0.18 μm CMOS process show that the proposed architecture achieves a 25 Mbps data transmission rate and 15 ns typical propagation delay with output peak currents of 2 A/4 A, respectively. Meanwhile, a CMTI of more than 150 kV/μs is realized. [ABSTRACT FROM AUTHOR]

This publication presents the effect of hypochlorous acid dry mist as a disinfectant on selected bacteria, viruses, spores, and fungi as well as on portable Microlife OXY 300 finger pulse oximeters and electronic systems of Raspberry Pi Zero microcomputers. The impact of hypochlorous acid on microbiological agents was assessed at concentrations of 300, 500, and 2000 ppm of HClO according to PN-EN 17272 (Variant I). Studies of the impact of hypochlorous acid fog on electronic components were carried out in an aerosol chamber at concentrations of 500 ppm and 2000 ppm according to two models consisting of 30 (Variant II) and 90 fogging cycles (Variant III). Each cycle included the process of generating a dry mist of hypochlorous acid (25 mL/m3), decontamination of the test elements, as well as cleaning the chamber of the disinfectant agent. The exposure of the materials examined on hypochlorous acid dry mist in all variants resulted in a decrease in the number of viruses, bacteria, spores, and fungi tested. In addition, the research showed that in the variants of hypochlorous acid fogging cycles analyzed, no changes in performance parameters and no penetration of dry fog of hypochlorous acid into the interior of the tested medical devices and electronic systems were observed. [ABSTRACT FROM AUTHOR]

Pistachio is market appealing due to its high nutritional value, low calorie and fat content, high anti-oxidant properties, and special aroma and flavor. However, this fruit is prone to various pathogenic factors, including fungi. This may lead to the production of highly toxic Aflatoxins. In this respect, the detection of fungal pathogens infection in the early stages of pistachio production is a major challenge in food security to mitigate losses as much as possible. In this study, an electronic nose (E-nose) was employed as a non-destructive and fast method for early detection of fungal infection on pistachio by Aspergillus Flavus fungus synthetically. To prepare experimental treatments, three treatments of 102, 104, and 106 spores were considered. An electronic nose system consisting of eight metal semiconductor sensors was developed to assess the odor of the samples. Three methods of principal component analysis (PCA), linear discriminant analysis (LDA), and support vector machine (SVM) were applied for classifications. The results showed that the electronic nose system was able to separate different concentrations of contamination from each other with an accuracy of 100%. In addition, the obtained results represented that infected pistachio samples can be successfully differentiated starting from the third day of the infection period. Notably, LDA and SVM performed better than the PCA method with 100% accuracy. Therefore, the electronic nose is a practical and beneficial tool for diagnosing the pistachio aflatoxin fungal infection. Therefore, the electronic nose can be a practical and beneficial tool that replaces traditional methods for diagnosing pistachio aflatoxin fungal infection. Highlights: • Electronic nose (E-nose) was used for early detection of fungal infection on pistachio. • The machine learning techniques descriminated infection levels on pistachio. • The E-nose system separates different contamination levels with an accuracy of 100%. • Infected pistachios can be discriminated from the third day of the infection period. [ABSTRACT FROM AUTHOR]