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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]

Helium (He) exerts significant influence on the physicochemical, structural, and electronic properties of pyrochlores. This paper reviews recent advancements in computer simulations aimed at stabilizing nuclear waste, focusing on disordered structures of pyrochlores, zirconate pyrochlores, and high‐entropy pyrochlores. Using Pu‐La2Zr2O7 as a case study, we demonstrate how a first‐principles approach facilitates the understanding of how He modifies the structural and electronic properties of this system. The incorporation of He interstitials in Pu‐La2Zr2O7 typically leads to an expansion in lattice constant and volume swelling. Analysis of the formation energies in this system reveals that octahedral interstitial sites or zirconium (Zr) vacancy sites are favored for He occupation, resulting in the formation of substitutional He atoms. The low concentration of He atoms in Pu‐La2Zr2O7 reduces the formation energy of cation antisite defects. Bader charge analysis indicates that the < Zr‐O > bond exerts a greater influence on the irradiation resistance of the He‐Pu‐La2Zr2O7 system compared to the < La‐O > bond. Moreover, the capacity for He interstitials increases with higher Pu concentration in the octahedrons. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANNs) with feedback loops known as recurrent neural networks (RNNs) are appropriate for handling temporal dependencies. The accuracy of the results in computational fluid dynamics (CFD) has gradually improved with the integration of artificial intelligence (AI) with CFD. This research article aims to decipher the dynamics of magneto‐hydro‐dynamic flow of second‐grade fluid with dissipation effect (MHD‐FSGF‐DE) using the Levenberg–Marquardt backpropagation (LMB) based on RNNs (LMB‐RNNs). The dataset is produced by the cutting‐edge homotopy analysis method for variation of different parameters including fluid parameter β, Marangoni parameter Ma, Hartmann number M, and Prandtl number Pr. RNNs are trained on the points of the dataset to maximize the outcome's accuracy and provide a comprehensive knowledge of the long‐term correlations between the input and output data points. The accuracy of the state‐of‐the‐art LMB‐RNNs approach is validated by performance graphs, error histograms, training estate analyses, regression plots, and input and output correlation plots. The profiles of physical properties like velocity, temperature, and concentration against β, Ma, M, and Pr are graphically shown to further highlight how these parameters affect physical properties. After 1000 iterations, the mean squared error (MSE) is 10−10 and the observed value of correlation coefficient R is 1 endorsing the worth of the LMB‐RNNs. The velocity of fluid upsurges for increasing β while declines for increasing M and Ma. The outcomes are comparable with the previously published findings. The core findings of this study have potential applications in various fields like polymer processing and cooling of electronic devices, specifically in the areas of electronic coolant system design and optimization. [ABSTRACT FROM AUTHOR]

Constructing an all‐in‐one wearable electronic system integrated with an energy‐harvesting, an energy‐storing, and a working unit can fundamentally solve the problems of sustainable energy supply, miniaturization, and lightweight for further commercialization. Here, an all‐in‐one wearable system consisting of solar cell, cathode‐free zinc ion micro‐battery (ZIMB) and piezoresistive pressure sensor is proposed, achieving an ultralong and stable power supply. Under the action of photocurrent, this integrated system is stimulated to in situ generate MnO2 on the initial cathode‐free substrate, meanwhile converts into chemical energy for powering the sensor, which eliminates prepreparation and treatment of the cathode for energy storage units. The facial cathode‐free ZIMB combining the all‐in‐one design enhances matching degree between different units and improves the integration. The working mechanism of the cathode‐free ZIMB is analyzed systematically through multiple ex situ characterizations and density functional theory (DFT) simulation. And the integrated sensing system illuminating for 12.0 h realizes the ultralong energy supply of the pressure sensor up to 150 000 cycles. As a concept, the integrated wearable electronic is used to detect human physiological signals, showcasing potential applications in activity monitoring, intelligent robotics, human–computer interaction, and other related fields. [ABSTRACT FROM AUTHOR]

ABSTRACT A three‐level bidirectional buck/boost converter (TLBBBC) is suitable for power electronic systems with a high‐voltage DC link for its switches with half voltage. In order to achieve higher efficiency, a novel zero‐voltage switching (ZVS) TLBBBC is proposed in this paper to enable operation with higher switching frequencies. In the proposed ZVS TLBBBC, two identical ZVS cells, each composed of a resonant inductor, two snubber capacitors, and two resonant capacitors, are integrated with the conventional three‐level (TL) topology to enable soft switching in all four switches in both buck and boost modes. Here, one advantage is that soft‐switching conditions are ensured under conventional control methods without using the auxiliary switch or complex control methods. In addition, the soft‐switching region is derived, clearly illustrating the relationship between the duty cycle ratio and the power inductor current that ensures the soft‐switching condition. Hence, the soft‐switching region is beneficial for assisting in ZVS cell design and guiding the converter in running in ZVS. Then, the operation and design considerations of the proposed topology are analyzed in detail. Finally, the experimental results of an 800‐W prototype for both the boost and buck modes are presented to confirm the theoretical analysis. [ABSTRACT FROM AUTHOR]

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]

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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]

• The paper discusses methodological shortcomings of studies on the effects of electronic stability control (ESC) for passenger cars. • A meta -analysis investigated whether the strong heterogeneity of the data could be explained by various methodological factors. • Only some samples yielded results which were consistent with the hypothesis of inflated effects. • It was concluded that some important methodological aspects of the studies have not been reported, and it is thus not possible to fully test the proposed hypotheses in a meta -analysis. Objective : Electronic Stability Control (ESC) is a standard feature on most modern cars, due to its reported efficiency to reduce the number of crashes of several types. However, empirical studies of safety effects of ESC for passenger vehicles have not considered some methodological problems that might have inflated the effects. This includes self-selection of drivers who buy/use ESC and behavioral adaptation to the system over long time periods, but also the dominant method of induced exposure. This study aimed to investigate whether such methodological problems might have influenced the results. Method: A meta -analysis was undertaken to investigate whether there are systematic differences between published studies. Moderators tested included when the study was undertaken, the type of vehicle studied, the percent ESC in the sample, size of sample, the length of the study, whether matched or un-matched vehicles were studied, whether induced exposure was used, and two variants of types of crashes used as controls. Results: The effects found ranged from 38% to 75% reduction of crashes for the main targets of singles, running off road and rollover crashes. However, these effects were heterogeneous, and differed depending on the methods used. Most importantly, information that could have allowed more precise analyses of the moderators were missing in most publications. Conclusions: Although average effects were large and in agreement with previous meta -analyses, heterogeneity of the data was large, and lack of information about important moderators means that firm conclusions about what kind of mechanisms were influencing the effects cannot be drawn. The available data on ESC efficiency are not unanimous, and further investigations into the effects of ESC on safety using different methodologies are warranted. [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]

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]

NaNbO 3 ceramics have broad application prospects in ultra-high power electronic systems, electromagnetic pulses, and other applications. In this study, (1- y)[(1- x)NaNbO 3 - x SmMg 0.5 Zr 0.5 O 3 ]- y (Bi 0.5 Na 0.5) 0.7 Sr 0.3 TiO 3 (x = 0.06, 0.08 and 0.10)(y = 0.30, 0.35, 0.40 and 0.45) ceramics were fabricated. The effects of the incorporation of SmMg 0.5 Zr 0.5 O 3 (SMZ) and (Bi 0.5 Na 0.5) 0.7 Sr 0.3 TiO 3 (BNST) on the energy storage performance, impedance, actual charge and discharge capacity, phase structure and microstructure of the ceramic samples were analyzed. Finally, when x = 0.08, and y = 0.35, the recoverable energy storage density of the sample was 5.8 J/cm3 and a high energy storage efficiency of 88 % was obtained at 545 kV/cm. In addition, the ceramic maintains a stable actual charge and discharge capacity and an extremely fast discharge time (16.1 ns) in a wide temperature range (20–160 °C). These excellent energy-storage performances may be due to the fine grain size and large relaxation and activation energies. [Display omitted] [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]

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]

Background Method Results Conclusions Samples for transfusion rejected due to mislabelling can lead to harm when a patient has to be re‐bled or has a transfusion or procedure delayed. Electronic labelling systems which scan the patient's identification band and generate a label at their side aim to reduce mislabelling and misidentification leading to wrong blood in tube (WBIT) errors. The 2022 National Comparative audit of sample collection aimed to compare national rates of sample mislabelling and WBIT to the 2012 audit and to examine the impact of electronic systems.All UK hospitals were invited to provide data on rejected transfusion samples and WBIT incidents in 1 month (October 2022) and were asked if they had electronic labelling.Twenty‐three thousand five hundred and eighty‐four rejected samples were reported by 179 sites in 1 month. The rejection rate of 4.4% represents a 47% increase compared to 2012 (2.99%). There were 92 WBIT incidents, an incidence of 1 in 5882 samples—a 45% increase compared to 1 in 8547 in 2012. Twenty‐three percent of sites can print a sample label at the patient's side, up by 224%. The six sites using only electronic sample labelling had a 46.9% lower rejection rate than sites using only hand‐labelling but still reported WBIT.The increase in sample rejection and WBIT may reflect pressures facing clinical staff, zero tolerance policies and the two‐sample rule. A human factors approach to understanding and tackling underlying reasons locally is recommended. Electronic systems are associated with fewer labelling errors, but careful implementation and training is needed to maximise their safety benefits. [ABSTRACT FROM AUTHOR]

Flexible tactile sensors play important roles in many areas, like human-machine interface, robotic manipulation, and biomedicine. However, their flexible form factor poses challenges in their integration with wafer-based devices, commercial chips, or circuit boards. Here, we introduce manufacturing approaches, device designs, integration strategies, and biomedical applications of a set of flexible, modular tactile sensors, which overcome the above challenges and achieve cooperation with commercial electronics. The sensors exploit lithographically defined thin wires of metal or alloy as the sensing elements. Arranging these elements across three-dimensional space enables accurate, hysteresis-free, and decoupled measurements of temperature, normal force, and shear force. Assembly of such sensors on flexible printed circuit boards together with commercial electronics forms various flexible electronic systems with capabilities in wireless measurements at the skin interface, continuous monitoring of biomechanical signals, and spatial mapping of tactile information. The flexible, modular tactile sensors expand the portfolio of functional components in both microelectronics and macroelectronics. [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]

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]

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]

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]

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]

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]

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]

E-waste has one of the greatest impacts on the environment and is the fastest-growing waste stream globally. The ever-ongoing growth in our economy and unsustainable consumption patterns ask for a change. Use-oriented product-service systems (u-PSS) are a promising business model to address this change by acting toward a circular economy. However, the implementation of u-PSS can face various challenges because it requires a fundamental shift in how companies interact with consumers as well as consumers' preferences. Therefore, this study aims to identify factors of acceptance for adopting u-PSS for electronic devices in Austria. To gather specific data, an online survey was conducted with 287 participants. The hypotheses were tested using multiple regression analysis. The results reveal that out of the tested factors, environmental awareness and information are the most important factors of acceptance. For a successful implementation, key determinants include service provision, device durability, and comprehensive information about u-PSS. [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]

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]

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]

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]

Electronic voting is an efficient way of conducting the voting process, which has the characteristics of real-time data and massive data and demands high security. In this paper, we propose a novel approach for electronic voting that utilizes decentralized network architecture with Blockchain and Hybrid cryptography techniques. Our system aims to address the challenges faced in administering EVMs and ensuring high security in strong rooms, which can lead to privacy and security flaws in the voting system. Our proposed model utilizes a wireless mesh topology to enlist vote details and modernize the chain of blocks, resulting in improved data confidentiality and reduced human resources. A customized UDP packet structure is designed to avoid port scanning and network traces, while the use of port numbers is eliminated for increased security. We also incorporate a three-layer encryption stack for secure key exchanges, which ensures perfect forward secrecy and an uncompromised state of the packet. By reducing the number of threads needed for Transport layer Protocol (TCP) connections; our proposed model improves the speed and security of the existing architecture. Overall, our approach offers a highly secure and efficient electronic voting system that meets the demands of secrecy, accuracy, and neutrality in the process of voting and counting. Our proposed system has the potential to prevent poll rigging by trespassers, ensuring a fair and trustworthy electoral process. [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]