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Abstract In this article, a CMOS-compatible Pirani vacuum gauge was proposed featuring enhanced sensitivity, lower detection limit, and high-temperature stability, achieved through the implementation of a surface micromachining method coupled with a temperature compensation strategy. To improve performance, a T-type device with a 1 µm gap was fabricated resulting in an average sensitivity of 1.10 V/lgPa, which was 2.89 times larger than that (0.38 V/lgPa) of a L-type device with a 100 µm gap. Additionally, FEA simulations were conducted, analyzing the influence of heater temperature on sensitivity and the attenuation of sensitivity across varying ambient temperatures. A semi-empirical theoretical mode was derived for performance prediction, demonstrating strong alignment with experimental results, underscoring its effectiveness in compensating for sensitivity attenuation. Building on the foundation, the device’s performance under different ambient temperatures was characterized and effectively compensated in two distinct operational modes: constant temperature mode and constant temperature difference mode (the whole range temperature compensation error can be controlled within 2.5%). Finally, the short-time stability (variation level is approximately 1 mV), noise floor (Vrms=384 μV) and detection limit (0.07 Pa @1 Hz) of the device were characterized, confirming its suitability for practical implementation.

Understanding the structural similarity between genomes is pivotal in classification and phylogenetic analysis. As the number of known genomes rockets, alignment-free methods have gained considerable attention. Among these methods, the natural vector method stands out as it represents sequences as vectors using statistical moments, enabling effective clustering based on families in biological taxonomy. However, determining an optimal metric that combines different elements in natural vectors remains challenging due to the absence of a rigorous theoretical framework for weighting different k-mers and orders. In this study, we address this challenge by transforming the determination of optimal weights into an optimization problem and resolving it through gradient-based techniques. Our experimental results underscore the substantial improvement in classification accuracy achieved by employing these optimal weights, reaching an impressive 92.73% on the testing set, surpassing other alignment-free methods. On one hand, our method offers an outstanding metric for virus classification, and on the other hand, it provides valuable insights into feature integration within alignment-free methods.

Abstract The incidence rate of chronic heart failure has increased significantly in China and has a large impact on patients’ lives. The purpose of the study was to validate the Chronic Heart Failure Health-Related Quality of Life Questionnaire (CHFQOLQ-20) cross-culturally and test its reliability and validity in patients with chronic heart failure. This study was conducted by investigating 622 patients with chronic heart failure from August 2023 to January 2024, and the data were tested for validity using SPSS 25.0 and AMOS 23.0. The final psychometric validation of the CHFQOLQ-20 was performed. The Chinese version of the CHFQOLQ-20 had a Cronbach’s α of 0.908, a split-half reliability of 0.870, and a retest reliability of 0.892. An exploratory factor analysis yielded four common factors with a cumulative ANOVA of 59.355%, and the validated factor analysis with one correction resulted in a better-fitting model (χ2/df = 2.020, RMSEA = 0.057, CFI = 0.920, TLI = 0.907). The scale is a reliable assessment tool that can be used in future clinical practice.

Abstract Chromatin spatial organization plays a crucial role in gene regulation. Recently developed and prospering multiplexed DNA FISH technologies enable direct visualization of chromatin conformation in the nucleus. However, incomplete data caused by limited detection efficiency can substantially complicate and impair downstream analysis. Here, we present SnapFISH-IMPUTE that imputes missing values in multiplexed DNA FISH data. Analysis on multiple published datasets shows that the proposed method preserves the distribution of pairwise distances between imaging loci, and the imputed chromatin conformations are indistinguishable from the observed conformations. Additionally, imputation greatly improves downstream analyses such as identifying enhancer-promoter loops and clustering cells into distinct cell types. SnapFISH-IMPUTE is freely available at https://github.com/hyuyu104/SnapFISH-IMPUTE .

Abstract The flexibility and stability of transparent electrodes play a crucial role in the growing popularity of flexible devices, especially in potential wearable electronics. To date, various solution-coating techniques have been developed for fabricating silver nanowire (AgNW) flexible bioelectronics. However, achieving the orderly distributed patterns of AgNW without undesirable aggregations still poses a grand challenge. Here, an approach to realize regular patterned ultrathin AgNW networks on a freestanding electrospun PVDF-TrFE frame by evaporation-induced self-assembly is proposed. The patterning mechanism of evaporating AgNW colloidal suspension is investigated from experimental and theoretical analysis. The influence of evaporation-induced flow inside colloidal freestanding membranes on forming regular square hole-shaped arrays, selective deposition of AgNW, and aligning them along the artificial pinning array are addressed. Owing to the orderly arrangement of AgNW networks, the resultant flexible electrode achieves ultrathin thickness (about 5 μm), high optical transmittance (87.8%), and low sheet resistance (8.4 Ω·sq−1) with a relatively low dosage of AgNW (9 μg·cm−2). The electrode exhibits excellent durability during cyclic bending (50,000 times) and stretching (50% strain). The resistance remains virtually unchanged during 200 days in everyday environments. Furthermore, the excellent conformability and breathability of the flexible transparent electrode attached to the human skin demonstrates its potential application as an e-skin sensor. Our findings reliably urge a simple approach to underscore better outcomes with effective patterns by self-assembly of AgNW for highly conformal wearable electronics.

Abstract Background To analyze the effects and pathways of factors such as psychological capital, family functioning, and sources of meaning in life on the level of self-management in elderly patients with chronic diseases and to provide a basis for the development of relevant nursing interventions in the future. Methods Convenience sampling was used to select elderly patients with chronic diseases who underwent medical checkups and consultations at three community hospitals in Jinzhou city from March 2023 to October 2023, and the self-designed General Information Questionnaire (GIS), Psychological Capital of the Elderly Scale (PCE), Family Functioning Index Questionnaire (APGAR), Sources of Meaning of Life Scale for Older Adults(SMSE), and Self-Management Behavior of Chronic Patients Scale (SMCS) were used. SPSS 26.0 was used for data entry, one-way analysis, Pearson correlation analysis, and multiple linear regression were used to analyze the data, and Amos 17.0 was used to construct the structural equation model. Results A total of 355 elderly patients with chronic diseases were included, and their self-management score was 74.75 ± 12.93, which was moderate. The results of the influencing factor analysis showed that the influencing factors of the self-management level of elderly chronic disease patients were age, years of illness, psychological capital, family functioning, and sources of meaning in life (p

This study optimizes the CuOx/Ga2O3 heterojunction diodes (HJDs) by tailoring the structural parameters of CuOx layers. The hole concentration in the sputtered CuOx was precisely controlled by adjusting the Ar/O2 gas ratio. Experimental investigations and TCAD simulations were employed to systematically evaluate the impact of the CuOx layer dimension and hole concentration on the electrical performance of HJDs. The results indicate that increasing the diameter dimension of the CuOx layer or tuning the hole concentration to optimal values significantly enhances the breakdown voltage (VB) of single-layer HJDs by mitigating the electric field crowing effects. Additionally, a double-layer CuOx structure (p+ CuOx/p− CuOx) was designed and optimized to achieve an ideal balance between the VB and specific on-resistance (Ron,sp). This double-layer HJD demonstrated a high VB of 2780 V and a low Ron,sp of 6.46 mΩ·cm2, further yielding a power figure of merit of 1.2 GW/cm2. These findings present a promising strategy for advancing the performance of Ga2O3 devices in power electronics applications.

Abstract Combinatorial optimization (CO) has a broad range of applications in various fields, including operations research, computer science, and artificial intelligence. However, many of these problems are classified as nondeterministic polynomial‐time (NP)‐complete or NP‐hard problems, which are known for their computational complexity and cannot be solved in polynomial time on traditional digital computers. To address this challenge, continuous‐time Ising machine solvers have been developed, utilizing different physical principles to map CO problems to ground state finding. However, most Ising machine prototypes operate at speeds comparable to digital hardware and rely on binarizing node states, resulting in increased system complexity and further limiting operating speed. To tackle these issues, a novel device‐algorithm co‐design method is proposed for fast sub‐optimal solution finding with low hardware complexity. On the device side, a piezoelectric lithium niobate (LiNbO3) microelectromechanical system (MEMS) oscillator network‐based Ising machine without second‐harmonic injection locking (SHIL) is devised to solve Max‐cut and graph coloring problems. The LiNbO3 oscillator operates at speeds greater than 9 GHz, making it one of the fastest oscillatory Ising machines. System‐wise, an innovative grouping method is used that achieves a performance guarantee of 0.878 for Max‐cut and 0.658 for graph coloring problems, which is comparable to Ising machines that utilize binarization.

Abstract Background Diabetic patients’ oral health concerns are a reality for every diabetic patient in China. The attitudes of diabetic patients toward early identification of oral literacy influence oral literacy in diabetes patients. Diabetes patients' oral health literacy is critical for providing focused education and therapies. However, no instrument exists to measure oral health literacy in Chinese diabetic patients. In this study, the English version of the oral health literacy among people living with diabetes (OHLD) scale was cross-culturally validated to provide a reliable tool for assessing the oral health literacy of diabetic patients in China. Objective The oral literacy among people living with diabetes (OHLD) scale was Chineseized and its reliability and validity tested, and the OHLD scale was revised to test the reliability and validity of the Chinese version of the OHLD scale and to provide a tool for assessing the oral health literacy of diabetic patients in China. Methods A modified version of the Brislin translation model was used, cross-cultural adaptation was performed through expert consultation and pre-survey, and expert opinion was used to assess content validity to form the Chinese version of the Oral Health Literacy Scale for Diabetic Patients, which was administered to 420 diabetic patients in two tertiary hospitals in Liaoning Province from March to August 2023. The reliability of the scale was tested. SPSS 25.0 and AMOS 23.0 were used to analyze the data. Results The Chinese version of the OHLD scale consisted of three dimensions and 10 entries. Structure of the validity analysis: three factors were extracted from the exploratory factors with a cumulative variance contribution of 79.794%; Content validity results:An item’s content validity index (I-CVI) was 0.857 to 1 at the entry level, and the content validity index of the scale (S-CVI) was 0.928 at the scale level. The results of the reliability analyses were: the Cronbach's alpha coefficient for the total scale was 0.908; the Cronbach's alpha coefficients for the factors and dimensions were 0.853 to 0.922; the split-half reliability was 0.827; and the test–retest reliability was 0.848. The results of the validation factor analysis showed that (χ2/df) was 1.430, the root mean square of the error of approximation (RMSEA) was 0.045, the comparative fit index (CFI) was 0.989, and the Tucker Lewis index (TLI) was 0.985, which showed that the model had an overall good fit. Conclusion The Chinese version of the OHLD scale has good reliability and validity and can be used as a valid tool for assessing diabetes mellitus patients in China.

Abstract Curved displays can adjust their shape to accommodate different objects and are used in electronics and decorative lighting. Due to the immutable pixel spacing, existing commercial curved displays are flexible but not compatible with undevelopable surfaces. Inspired by kirigami and auxetic structures, we propose an approach that combines luminescent elements and rotating square tessellations to create a stretchable, arbitrary curve adaptive display. We connect square islands by vertical interconnects to relieve the stress concentration and provide extra deformation patterns. The vertical interconnects are patterned on a flexible printed circuit board (FPCB) using laser cutting and folded up via specially designed molds. Further, the freed-up space by folded interconnects allows the structure to be compressed. A prototype stretchable display is demonstrated that it can maintain electrical performance under biaxial strain and adapt to different Gaussian curvature surfaces, including cylindrical, spherical, saddle and arbitrary surfaces. Theoretical models and finite element calculations are established to describe the tensile behavior of the structures under different boundary conditions and agree with the experimental results. This proposed technology paves a feasible solution of mass production of adaptive curved displays and sets the trend for the next-generation display.

This paper proposes a physical charge-based analytical MOSFET threshold voltage model that explicitly incorporates interface-trapped charges which have been identified as playing a dominant role in defining threshold voltage trends in deep cryogenic temperatures. The model retains standard threshold voltage definition by various charges across the MOSFET capacitor while being analytical in its form, therefore, suitable for cryogenic CMOS VLSI design. Consequently, a model covering each and all above characteristics is proposed for the first time. Excellent fit between the model and measurement data from 180-nm bulk foundry devices is shown from room temperature to 4 K.

This study investigates the DC and RF performance of RF GaN High Electron Mobility Transistors (HEMTs) subjected to surface pretreatments by N2 and N2O plasma. The filling of nitrogen vacancies or the passivation effect introduced by the thin GaON layer result in enhanced DC characteristics and RF performance for devices treated with nitrogen-based plasma. Compared to the untreated device, the device treated with N2 plasma exhibited a significant improvement in performance, i.e., the saturated current increased by approximately 16%, the characteristic frequency (fT) had an increase of 27.6 GHz, the maximum oscillating frequency (fmax) increased by 60.4 GHz. Furthermore, the breakdown voltage had a 10.7% increase, and the dynamic/static on-resistance ratio decreased from 1.34 to 1.18. These results highlight the potential of nitrogen-based plasma treatments in improving the performance of RF GaN HEMTs.

In this work, we present the novel application of SiNx stress-engineering techniques for the suppression of short-channel effects in AlGaN/GaN high-electron-mobility transistors (HEMTs), accompanied by a comprehensive analysis of the underlying mechanisms. The compressive stress SiNx passivation significantly enhances the barrier height at the heterojunction beneath the gate, maintaining it above the quasi-Fermi level even as Vds rises to 20 V. As a result, in GaN devices with a gate length of 160 nm, the devices with compressive stress SiNx passivation exhibit significantly lower drain-induced barrier lowering (DIBL) factors of 2.25 mV/V, 2.56 mV/V, 4.71 mV/V, and 3.84 mV/V corresponding to drain bias voltages of 5 V, 10 V, 15 V, and 20 V, respectively. Furthermore, as Vds increases, there is an insignificant degradation in transconductance, subthreshold swing, leakage current, or output conductance. In contrast, the devices with stress-free passivation show relatively higher DIBL factors (greater than 20 mV/V) and substantial degradation in pinch-off performance and output characteristics. These results demonstrate that the SiNx stress-engineering technique is an attractive technique to facilitate high-performance and high-reliability GaN-based HEMTs for radio frequency (RF) electronics applications.

In this work, the DC performance and RF characteristics of GaN-based high-electron-mobility transistors (HEMTs) using the SiNx stress-engineered technique were systematically investigated. It was observed that a significant reduction in the peak electric field and an increase in the effective barrier thickness in the devices with compressive SiNx passivation contributed to the suppression of Fowler–Nordheim (FN) tunneling. As a result, the gate leakage decreased by more than an order of magnitude, and the breakdown voltage (BV) increased from 44 V to 84 V. Moreover, benefiting from enhanced gate control capability, the devices with compressive stress SiNx passivation showed improved peak transconductance from 315 mS/mm to 366 mS/mm, along with a higher cutoff frequency (ft) and maximum oscillation frequency (fmax) of 21.15 GHz and 35.66 GHz, respectively. Due to its enhanced frequency performance and improved pinch-off characteristics, the power performance of the devices with compressive stress SiNx passivation was markedly superior to that of the devices with stress-free SiNx passivation. These results confirm the substantial potential of the SiNx stress-engineered technique for high-frequency and high-output power applications, which are crucial for future communication systems.

Abstract Stretchable and curved electronic devices are a promising technology trend due to their remarkable advantages. Many approaches have been developed to manufacture stretchable and curved electronics. Here, to allow such electronics to better serve practical applications, ranging from wearable devices to soft robotics, we propose a novel vertical serpentine conductor (VSC) with superior electrical stability to interconnect functional devices through a silicon-based microfabrication process. Conformal vacuum transfer printing (CVTP) technology was developed to transfer the networked platform onto complex curved surfaces to demonstrate feasibility. The mechanical and electrical performance were investigated numerically and experimentally. The VSC interconnected network provides a new approach for stretchable and curved electronics with high stretchability and reliability.

Abstract This work presents an E(3) equivariant graph neural network called HamGNN, which can fit the electronic Hamiltonian matrix of molecules and solids by a complete data-driven method. Unlike invariant models that achieve equivariance approximately through data augmentation, HamGNN employs E(3) equivariant convolutions to construct the Hamiltonian matrix, ensuring strict adherence to all equivariant constraints inherent in the physical system. In contrast to previous models with limited transferability, HamGNN demonstrates exceptional accuracy on various datasets, including QM9 molecular datasets, carbon allotropes, silicon allotropes, SiO2 isomers, and BixSey compounds. The trained HamGNN models exhibit accurate predictions of electronic structures for large crystals beyond the training set, including the Moiré twisted bilayer MoS2 and silicon supercells with dislocation defects, showcasing remarkable transferability and generalization capabilities. The HamGNN model, trained on small systems, can serve as an efficient alternative to density functional theory (DFT) for accurately computing the electronic structures of large systems.

Abstract With the annual increases in the morbidity and mortality rates of tumors, the use of biomarkers for early diagnosis and real-time monitoring of tumor cells is of great importance. Biomarkers used for tumor cell detection in body fluids include circulating tumor cells, nucleic acids, protein markers, and extracellular vesicles. Among them, circulating tumor cells, circulating tumor DNA, and exosomes have high potential for the prediction, diagnosis, and prognosis of tumor diseases due to the large amount of valuable information on tumor characteristics and evolution; in addition, in situ monitoring of telomerase and miRNA in living cells has been the topic of extensive research to understand tumor development in real time. Various techniques, such as enzyme-linked immunosorbent assays, immunoblotting, and mass spectrometry, have been widely used for the detection of these markers. Among them, the detection of tumor cell markers in body fluids based on electrochemical biosensors and fluorescence signal analysis is highly preferred because of its high sensitivity, rapid detection and portable operation. Herein, we summarize recent research progress in the detection of tumor cell biomarkers in body fluids using electrochemical and fluorescence biosensors, outline the current research status of in situ fluorescence monitoring and the analysis of tumor markers in living cells, and discuss the technical challenges for their practical clinical application to provide a reference for the development of new tumor marker detection methods.

Abstract The development of high-performance oxide-based transistors is critical to enable very large-scale integration (VLSI) of monolithic 3-D integrated circuit (IC) in complementary metal oxide semiconductor (CMOS) backend-of-line (BEOL). Atomic layer deposition (ALD) deposited ZnO is an attractive candidate due to its excellent electrical properties, low processing temperature below copper interconnect thermal budget, and conformal sidewall deposition for novel 3D architecture. An optimized ALD deposited ZnO thin-film transistor achieving a record field-effect and intrinsic mobility (µ FE /µ o ) of 85/140 cm2/V·s is presented here. The ZnO TFT was integrated with HfO2 RRAM in a 1 kbit (32 × 32) 1T1R array, demonstrating functionalities in RRAM switching. In order to co-design for future technology requiring high performance BEOL circuitries implementation, a spice-compatible model of the ZnO TFTs was developed. We then present designs of various ZnO TFT-based inverters, and 5-stage ring oscillators through simulations and experiments with working frequency exceeding 10’s of MHz.

Abstract Doped‐metal oxide‐based memristors, with the potential for improved switching performance and capability for multi‐bit information storage, are attractive candidates in the implementation of artificial neural network (ANN) hardware systems. However, performance and process considerations such as switching behavior and complementary‐metal‐oxide‐semiconductor (CMOS) process compatibility remain a challenge. This study shows that amorphous Zr‐doped HfO2 (HZO) memristors fabricated via a co‐sputtering approach improve the switching performance by providing a controllable knob to modulate defects in the switching layer. At the same time, it satisfies the CMOS process compatibility requirements for industry adoption. HZO memristors with optimized stoichiometry exhibit 30% reduced switching voltages and 50% faster switching as compared to control HfO2 memristors. Concurrently, this study shows that high linearity analog states tuning is achievable via a programming scheme that utilizes voltage pulses with increasing amplitudes. This study further shows via simulation evaluation that HZO memristors implemented in a self‐organizing‐map (SOM) network for Fashion MNIST database classification, achieve an accuracy of 92% with short training cycles. The results thus pave a potential pathway for further development of CMOS process compatible HZO memristors for use in future storage and computing applications.

Abstract Thermoelectric devices (TEDs) show great potential for waste heat energy recycling and sensing. However, existing TEDs cannot be self‐adapted to the complex quadratic surface, leading to significant heat loss and restricting their working scenario. Here, surface‐conformable origami‐TEDs (o‐TEGs) are developed through programmable crease‐designed origami substrates and the screen‐printing TE legs. Compared with “π” structured TEDs, the origami design (with heat conductive materials) changed the heat‐transferring direction of the laminated TE legs, resulting in an enhancement in enlarging ΔT/THot and Vout by 5.02 and 3.51 times. Four o‐TEDs with different creases designs are fabricated to verify the heat recycling ability on plane and central quadratic surfaces. Demonstrating a high Vout density (up to 0.98 −2at ΔT of 50 K) and good surface conformability, o‐TEDs are further used in thermal touch panels attached to multiple surfaces, allowing information to be wirelessly transferred on a remote display via finger‐writing.

Chromosomal fusion is a significant form of structural variation, but research into algorithms for its identification has been limited. Most existing methods rely on synteny analysis, which necessitates manual annotations and always involves inefficient sequence alignments. In this paper, we present a novel alignment-free algorithm for chromosomal fusion recognition. Our method transforms the problem into a series of assignment problems using natural vectors and efficiently solves them with the Kuhn-Munkres algorithm. When applied to the human/gorilla and swamp buffalo/river buffalo datasets, our algorithm successfully and efficiently identifies chromosomal fusion events. Notably, our approach offers several advantages, including higher processing speeds by eliminating time-consuming alignments and removing the need for manual annotations. By an alignment-free perspective, our algorithm initially considers entire chromosomes instead of fragments to identify chromosomal structural variations, offering substantial potential to advance research in this field.

Abstract Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometers and up to several kilobases in resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at https://github.com/HuMingLab/SnapFISH .

Background: The rupture of intracranial aneurysms (IAs) would result in subarachnoid hemorrhage with high mortality and disability. Predicting the risk of IAs rupture remains a challenge. Methods: This paper proposed an effective method for classifying IAs rupture status by integrating a PointNet-based model and machine learning algorithms. First, medical image segmentation and reconstruction algorithms were applied to 3D Digital Subtraction Angiography (DSA) imaging data to construct three-dimensional IAs geometric models. Geometrical parameters of IAs were then acquired using Geomagic, followed by the computation of hemodynamic clouds and hemodynamic parameters using Computational Fluid Dynamics (CFD). A PointNet-based model was developed to extract different dimensional hemodynamic cloud features. Finally, five types of machine learning algorithms were applied on geometrical parameters, hemodynamic parameters, and hemodynamic cloud features to classify and recognize IAs rupture status. The classification performance of different dimensional hemodynamic cloud features was also compared. Results: The 16-, 32-, 64-, and 1024-dimensional hemodynamic cloud features were extracted with the PointNet-based model, respectively, and the four types of cloud features in combination with the geometrical parameters and hemodynamic parameters were respectively applied to classify the rupture status of IAs. The best classification outcomes were achieved in the case of 16-dimensional hemodynamic cloud features, the accuracy of XGBoost, CatBoost, SVM, LightGBM, and LR algorithms was 0.887, 0.857, 0.854, 0.857, and 0.908, respectively, and the AUCs were 0.917, 0.934, 0.946, 0.920, and 0.944. In contrast, when only utilizing geometrical parameters and hemodynamic parameters, the accuracies were 0.836, 0.816, 0.826, 0.832, and 0.885, respectively, with AUC values of 0.908, 0.922, 0.930, 0.884, and 0.921. Conclusion: In this paper, classification models for IAs rupture status were constructed by integrating a PointNet-based model and machine learning algorithms. Experiments demonstrated that hemodynamic cloud features had a certain contribution weight to the classification of IAs rupture status. When 16-dimensional hemodynamic cloud features were added to the morphological and hemodynamic features, the models achieved the highest classification accuracies and AUCs. Our models and algorithms would provide valuable insights for the clinical diagnosis and treatment of IAs.

Abstract Background Apatinib (YN968D1) is the first small-molecule-targeting drug with anti-tumor activity created in China for the treatment of advanced gastric cancer (GC) and hepatocellular carcinoma (HCC). It showed significant variation in the efficacy for treating cancers, including advanced non-squamous non-small-cell lung cancer (NSCLC). Whether its efficacy could be optimized by subgrouping patients with certain genetic variation remains elusive. Methods Here, we firstly used kinase screening to identify any possible target of apatinib against 138 kinases. The effects of apatinib on proliferation rates, cell cycle, cell apoptosis, and cell migration on cancer cell lines were analyzed; the in vitro potential pathways of apatinib on cancer cell lines were screened. The effect of apatinib on mouse cancer models in vivo was also analyzed. Results Based on HCC364 cells with BRAF V600E mutation, we have shown that apatinib could inhibit their growth, migration, cell cycle, and induce their apoptosis. Based on mice with transplanted HCC364 cells, we have also shown that apatinib could inhibit the tumor growth. Based on immunohistochemistry, we have demonstrated that apatinib could suppress the phosphorylation of mitogen-activated protein kinase/extracellular signal-regulated kinase and extracellular regulated protein kinases. This may account at least part of the apatinib’s inhibitory effect on HCC364 cancer cells. Conclusions BRAF V600E protein kinase is a target of apatinib by kinase screening. We have demonstrated that apatinib can effectively inhibit tumor cells with BRAF V600E mutation by in vitro and in vivo experiments. Our results have demonstrated that targeting BRAF V600E mutation, apatinib appears to be effective and safe for treating NSCLC and possibly other cancers with the same mutation.

Background The media play an important role in health promotion and disease prevention, while at the same time, a variety of mixed health messages in the media are beginning to pose new challenges to them. However, there is a lack of media health literacy (MHL) assessment tools in China. Therefore, the purpose of this study was to translate the Media Health Literacy (MeHLit) questionnaire into Chinese and to assess its psychometric properties. Methods This cross-sectional study was conducted from October to December 2022, and a methodological study of the translation and validation of the MeHLit questionnaire was conducted. Results As a result of an extensive translation and cultural adaptation process, the final MeHLit questionnaire was developed, which includes five dimensions and 21 items. Cronbach's α value of the questionnaire was 0.859, and Cronbach's α value of the dimensions ranged from 0.776 to 0.911, which is fairly good. As a result, the test–retest reliability coefficient and the split-half reliability coefficient of the questionnaire are both equal to 0.907. Its content validity index was 0.946, suggesting a reasonable level of content validity. Through exploratory factor analysis, a five-factor structure was identified based on the eigenvalues, total variance explained, and scree plot. As a result of the validation factor analysis, all recommended fit indicators were appropriate. Conclusion The Chinese version of the MeHLit questionnaire has been successfully introduced in China. It has shown good psychometric properties among the Chinese public and can be used as a tool to evaluate MHL in health screening.

Abstract Wearable strain sensors have been widely used for human activity monitoring. Most reported strain sensors have mainly focused on material engineering, high stretchability and large gauge factors. Few works have focused on strain sensor’s robustness and reliability, including low hysteresis, good long-term stability, good electrode material stability, and low coupling effects under multi-input signals, which are the factors that limit practical strain sensor applications. To develop a high-performance strain sensor, we propose a flexible capacitive sensor structure with three-dimensional (3D) interdigital electrodes fabricated by vertically aligned carbon nanotubes. Compared with a traditional resistive strain sensor and a capacitive strain sensor with vertical sandwich electrodes, a strain sensor with horizontal parallel interdigital electrodes can benefit from low cross talk in terms of the normal force and improve substrate transparency. Additionally, embedding 3D electrodes into the substrate improves ultrahigh robustness with a low-pressure coupling effect under normal force. Moreover, compared with other reported works, the electrode variation under strain is small (less than 1.6%), which means that the perturbation of inert properties on device performance is small. Finally, the fabricated strain sensor achieves an ultralow hysteresis (0.35%), excellent pressure-insensitive performance (less than 0.8%), fast response (60 ms), good long-term stability, and good transparency. As an application example, a flexible strain sensor was successfully demonstrated as a wearable device for the precise monitoring of different types of human activities, including bending of the finger, knee, elbow, wrist, and neck with large strain signals and small strain signals generated by a mouth-opening activity. This excellent performance indicates that the flexible strain sensor is a promising candidate for human motion detection, soft robotics, and medical care.

Abstract Intrinsic plasticity of neurons, such as spontaneous threshold lowering (STL) to modulate neuronal excitability, is key to spatial attention of biological neural systems. In‐memory computing with emerging memristors is expected to solve the memory bottleneck of the von Neumann architecture commonly used in conventional digital computers and is deemed a promising solution to this bioinspired computing paradigm. Nonetheless, conventional memristors are incapable of implementing the STL plasticity of neurons due to their first‐order dynamics. Here, a second‐order memristor is experimentally demonstrated using yttria‐stabilized zirconia with Ag doping (YSZ:Ag) that exhibits STL functionality. The physical origin of the second‐order dynamics, i.e., the size evolution of Ag nanoclusters, is uncovered through transmission electron microscopy (TEM), which is leveraged to model the STL neuron. STL‐based spatial attention in a spiking convolutional neural network (SCNN) is demonstrated, improving the accuracy of a multiobject detection task from 70% (20%) to 90% (80%) for the object within (outside) the area receiving attention. This second‐order memristor with intrinsic STL dynamics paves the way for future machine intelligence, enabling high‐efficiency, compact footprint, and hardware‐encoded plasticity.

The piezoelectric thin film composed of single-crystal lithium niobate (LiNbO3) exhibits a remarkably high electromechanical coupling coefficient and minimal intrinsic losses, making it an optimal material for fabricating bulk acoustic wave resonators. However, contemporary first-order antisymmetric (A1) Lamb mode resonators based on LiNbO3 thin films face specific challenges, such as inadequate mechanical stability, limited power capacity, and the presence of multiple spurious modes, which restrict their applicability in a broader context. In this paper, we present an innovative design for A1 Lamb mode resonators that incorporates a support-pillar structure. Integration of support pillars enables the dissipation of spurious wave energy to the substrate, effectively mitigating unwanted spurious modes. Additionally, this novel approach involves anchoring the piezoelectric thin film to a supportive framework, consequently enhancing mechanical stability while simultaneously improving the heat dissipation capabilities of the core.

Abstract Background The effect of depressive symptoms on hip fracture (HF) and falls among the Chinese population is unclear. This study aims to examine the prospective association between depressive symptoms and HF as well as fall accidents in a nationally representative Chinese population. Methods We used data from 10,596 participants in the Chinese Health and Retirement Longitudinal Study (from 2011 to 2018) who were aged ≥45 years and had no HFs at baseline. Depressive symptoms were assessed using the 10-item version of the Center for Epidemiological Studied Depression scale (cutoff for distinguishing high versus low at ≥12). Logistic regression analyses adjusted for demographic characteristics, lifestyle factors and physical comorbidities were performed. Results For the analysis of baseline depressive symptoms and HF, 399 (3.8%) participants reported HF accidents in the following 7-year period. Individuals with elevated depressive symptoms at baseline experienced a markedly higher HF risk (odds ratio [OR] = 1.33, 95% confidence interval [CI] = 1.06–1.67) than those without elevated depressive symptoms, after adjusting for a wide range of potential confounders. For the analysis of baseline depressive symptoms and falls, 3974 (37.5%) experienced fall accidents during the follow-up. The presence of elevated depressive symptoms was independently associated with an increased risk of fall events (OR = 1.21, 95% CI = 1.10–1.33). These associations were consistent across multiple characteristics. Conclusions In conclusion, elevated depressive symptoms were associated with an increased risk of HF and falls, which may have considerable clinical and preventive implications.

Abstract Autonomous one‐shot on‐the‐fly learning copes with the high privacy, small dataset, and in‐stream data at the edge. Implementing such learning on digital hardware suffers from the well‐known von‐Neumann and scaling bottlenecks. The optical neural networks featuring large parallelism, low latency, and high efficiency offer a promising solution. However, ex‐situ training of conventional optical networks, where optical path configuration and deep learning model optimization are separated, incurs hardware, energy and time overheads, and defeats the advantages in edge learning. Here, we introduced a bio‐inspired material‐algorithm co‐design to construct a hydrogel‐based optical Willshaw model (HOWM), manifesting Hebbian‐rule‐based structural plasticity for simultaneous optical path configuration and deep learning model optimization thanks to the underlying opto‐chemical reactions. We first employed the HOWM as an all optical in‐sensor AI processor for one‐shot pattern classification, association and denoising. We then leveraged HOWM to function as a ternary content addressable memory (TCAM) of an optical memory augmented neural network (MANN) for one‐shot learning the Omniglot dataset. The HOWM empowered one‐shot on‐the‐fly edge learning leads to 1000× boost of energy efficiency and 10× boost of speed, which paves the way for the next‐generation autonomous, efficient, and affordable smart edge systems.

Abstract Curved displays have recently become very popular, with wide applications for both industry and consumers. However, built upon initially flat films, most flexible displays are often incompatible with general nondevelopable surfaces. In this paper, we report a method for producing curved displays of nondevelopable shapes by using a structure-mechanics-inspired functional optimization method to design tessellation patterns that fold into the desired shapes. Representative displays in spherical and saddle shapes are demonstrated. The microfabrication process is employed for manufacturing 2D flexible foldable circuit boards, pick-and-place technology is used for placing illuminant elements onto the boards, and mold guidance is used for folding 2-D sheets into curved 3D display prototypes. The proposed technology is feasible for mass production and advances the application of next-generation curved displays.

BackgroundIn China, some patients avoid seeking medical care and are highly sensitive to subsequent medical care because of fear of possible hospitalization after a diagnosis has been established. Early identification of fear of hospitalization is essential for clinical staff to develop targeted education and interventions. However, there are currently no tools to assess outpatients’ fear of hospitalization in mainland China. This study aimed to translate the Fear of Hospitalization (FH) scale into Chinese and verify its reliability and validity in outpatients.MethodsThrough convenience sampling, 664 outpatients who required hospitalization were recruited from two cities in Liaoning Province, China. The reliability of the translated scale was measured by internal consistency, split-half reliability, and test–retest reliability. The validity of the translated scale was evaluated by expert consultation, exploratory factor analysis, and confirmatory factor analysis. Data were analyzed using SPSS 25.0 (IBM Corp., Armonk, NY, United States) and AMOS 23.0 (IBM Corp., Armonk, NY, United States).ResultsThe Cronbach’s α value of the Chinese version of the FH scale was 0.849, and the Cronbach’s α value of the dimensions ranged from 0.857 to 0.902. The test–retest reliability value of 0.868 shows good temporal stability. The split-half reliability value of 0.910 indicates a high degree of measuring the same content. The content validity index of the scale (S-CVI) was 0.924, indicating a good level of content validity. The 3-factor structure supported by eigenvalues, total variance explained, and scree plot was obtained using exploratory factor analysis. In addition, all recommended fit indicators were within the acceptable range by confirmatory factor analysis.ConclusionThe Chinese version of the FH scale is valid and reliable in outpatients. The developed three-factor structured scale will help identify outpatients with a high fear of hospitalization and can inform the development of educational intervention plans for care managers, physicians, and nurses. In addition, it helps clinicians and nurses take action to reduce this fear of hospitalization in patients and prevent avoidance of using health care services due to fear of hospitalization.

BackgroundIn China, clinical deterioration events present a real problem for every clinical nurse. Patient deterioration is determined in part by nurses’ attitudes toward early recognition of clinical deterioration. However, research on attitudes toward the early identification of clinical deterioration is still in its infancy, and even less research has been done on ward nurses’ attitudes toward the early identification of clinical deterioration. To drive behavioral change and improve the care of deteriorating patients, nurses need comprehensive, valid, and reliable tools to assess their attitudes toward early identification of deterioration.ObjectiveIn this study, we aimed to translate the Attitudes Toward Recognizing Early and Noticeable Deterioration (ATREND) scale into Chinese and to assess its validity and reliability tests.MethodsFrom March 2022 to July 2022, the ATREND scale was translated, back-translated, and cross-culturally adapted into the Chinese version using a modified Brislin translation model. Then, 460 ward nurses were recruited from tertiary Grade A general hospitals in two cities: Shenyang and Jinzhou in Liaoning Province, China. Reliability analyses were conducted using internal consistency, split-half, and test–retest reliability. We convened a committee of experts to determine the validity of the content. Tests of the structural validity of the scale were conducted using exploratory and validation factor analyses.ResultsThe Cronbach’s α value of the Chinese version of the ATREND scale was 0.804, and the Cronbach’s α value of the dimensions ranged from 0.782 to 0.863. The split-half reliability and test–retest reliability were 0.846 and 0.711, respectively. Furthermore, the scale has an index of content validity of 0.922, indicating a high level of content validity. In exploratory factor analysis, eigenvalues, total variance explained, and scree plot supported a three-factor structure. The three-factor model supported by this study was confirmed by confirmatory factor analysis (CFA). Moreover, the model fitting indexes (e.g., χ2/DF = 1.498, GFI = 0.954, RMSEA = 0.047) were all within acceptable limits based on the CFA.ConclusionThe Chinese version of the scale is reliable and valid among ward nurses. Nursing educators and clinicians will be able to develop targeted educational programs to enhance the competence and behaviors of Chinese ward nurses in recognizing clinical deterioration. It will be based on the developed scale to assess Chinese nurses’ attitudes and practices regarding early recognition of clinical deterioration. As a result, it is necessary to consider the Chinese scale’s three-factor structure. The developed three-factor structured scale will assess Chinese ward nurses’ attitudes and practices toward patient observation and vital sign-monitoring empowerment, enlightening them on the importance of patient observation, encouraging ward nurses to use a wider range of patient assessment techniques to capture early signs of clinical deterioration, and helping ward nurses to develop clinical confidence to monitor clinical deterioration.

Yu et al. report a new type of induced earthquake signal characterized by hybrid-frequency waveforms (EHW). The low-frequency source features of the EHWs suggest they may represent slow ruptures transitioning from aseismic to seismic slip.

Abstract The humidity sensor is an essential sensing node in medical diagnosis and industrial processing control. To date, most of the reported relative humidity sensors have a long response time of several seconds or even hundreds of seconds, which would limit their real application for certain critical areas with fast-varying signals. In this paper, we propose a flexible and low-cost humidity sensor using vertically aligned carbon nanotubes (VACNTs) as electrodes, a PDMS-Parylene C double layer as the flexible substrate, and graphene oxide as the sensing material. The humidity sensor has an ultrafast response of ~20 ms, which is more than two orders faster than most of the previously reported flexible humidity sensors. Moreover, the sensor has a high sensitivity (16.7 pF/% RH), low hysteresis (

Background: Hepatic fibrosis (HF) is characterized by activation of hepatic stellate cells (HSCs) and extensive deposition of extracellular matrix components, especially collagens. However, effective antifibrotic therapies are still lacking. Recently, circular RNAs (circRNAs) have been identified as novel regulators of HF.Methods: circRNAs profile was screened by RNA sequencing and the location of circ_0008494 was confirmed by fluorescence in situ hybridization assay in human HF tissues. Bioinformatics analysis was used for result prediction and dual-luciferase reporter, together with AGO-RIP and biotin-coupled miRNA capture assays, were used to determine miR-185-3p/collagen type I alpha 1 chain (Col1a1) as the target of circ_0008494. A stable circ_0008494-interfering human HSCs cell line was constructed and used to determine the regulatory mechanism of circ_0008494/miR-185-3p/Col1a1 axis.Results: circ_0008494 was abundantly and significantly over-expressed in human HF tissues and located at the cytoplasm of HSCs. Together, dual-luciferase reporter, AGO-RIP and biotin-coupled miRNA capture assays confirmed that circ_0008494 acted as a sponge of miR-185-3p. Cell functional experiments and rescue assays demonstrated suppressing circ_0008494 could inhibit activation, proliferation, migration of HSCs and promote their apoptosis through miR-185-3p. In particular, the HF indicator, Col1a1, was validated as the direct target of miR-185-3p and the suppression of circ_0008494 inhibited the expression of Col1a1 by releasing miR-185-3p.Conclusion: Knocking down circ_0008494 inhibited HSCs activation through the miR-185-3p/Col1a1 axis. circ_0008494 could be a promising treatment target for HF.

Abstract During MEMS device fabrication process, the residual stress of thin film caused by thermal expansion coefficient mismatch and lattice mismatch is an important factor that will deteriorate the properties of thin film and bring yield losses to MEMS devices. In this work, a method to release the residual stress by using a folded structure with V‐shaped grooves is proposed. The folded structures with different groove width and groove interval are fabricated and relative Raman frequency shift is adopted to calculate the residual stress. The minimum residual thermal stress of 11.6 MPa can be obtained in the folded structure models by simulation, which is about five times lower than the residual thermal stress of the flat structure. The minimum residual stress of 40 MPa can be obtained in the folded structure by experiment results, which is about 20 times lower than the residual stress of the flat structure. The simulation results and experimental analysis confirms that introducing a folded structure with groove into the design of MEMS device is an effective way to suppress the generation of residual stress, thus enhancing the reliability of MEMS devices.

Abstract Highly reliable signal recording with low electrode-skin impedance makes the microneedle array electrode (MAE) a promising candidate for biosignal sensing. However, when used in long-term health monitoring for some incidental diseases, flexible microneedles with perfectly skin-tight fit substrates lead to sweat accumulation inside, which will not only affect the signal output but also trigger some skin allergic reactions. In this paper, a flexible MAE on a Miura-ori structured substrate is proposed and fabricated with two-directional in-plane bendability. The results from the comparison tests show enhanced performance in terms of (1) the device reliability by resisting peeling off of the metal layer from the substrate during the operation and (2) air ventilation, achieved from the air-circulating channels, to remove sweat. Bio-signal recordings of electrocardiography (ECG), as well as electromyography (EMG) of the biceps brachii, in both static and dynamic states, are successfully demonstrated with superior accuracy and long-term stability, demonstrating the great potential in health monitoring applications.

Performance of perovskite photovoltaics is greatly affected by undesirable defects that contribute to non-radiative losses. Here, the authors mitigate these losses by doping perovskite with KI to alter the dielectric response, thus defect capturing probability, resulting in inverted device with PCE of 22.3% and low voltage loss.

The unprecedented development of Internet of Things results in the explosion of spatiotemporal signals generated by smart edge devices, leading to a surge of interest in real‐time learning of such data. This imposes a big challenge to conventional digital hardware because of physically separated memory and processing units and the transistor scaling limit. Memristors are deemed a solution for efficient and portable deep learning. However, their ionic resistive switching incurs large programming stochasticity and energy, compromising their advantages in real‐time learning spatiotemporal signals. To address the aforementioned issues, we propose a novel hardware–software codesign. Hardware‐wise, the stochasticity in memristor programming is leveraged to produce random matrices for efficient in‐memory computing. Software‐wise, random convolutional‐pooling architectures are integrated with echo‐state networks that compute with the hardware random matrices and make real‐time learning affordable. The synergy of the hardware and software not only improves the performance over conventional echo‐state networks, that is, 90.94% and 91.67% (compared to baselines 88.33% and 62.50%), but also retains 187.79× and 93.66× improvement of energy efficiency compared to the digital alternatives on the representative Human Activity Recognition Using Smartphones (HAR) and CRICKET datasets, respectively. These advantages make random convolutional echo‐state network (RCESN) a promising solution for the future smart edge hardware.

Abstract Origami, an ancient form of papercraft, provides a way to develop functional structures for engineering applications. In this paper, we report an approach to design and manufacture a stretchable circuit board (SCB) with origami structures. The benefits of developable, flat-foldable, and rigid-foldable origami-based structures as SCBs are discussed, and a representative structure, Miura fold (or Miura-ori), is chosen to be investigated. Under the constraints induced by the mounted components’ dimensions, the Miura-ori structures for specific applications can be defined. We propose three methods for better fabrication, including direct folding, stiffness modification, and kirigami enhancement, to improve a planar sheet’s foldability. A wearable ECG (electrocardiogram) system based on MO-SCB (Miura-ori enabled SCB) technology is built, and the stretchable portion is made of commercial FPCBs (flexible printed circuit board), providing desired stretchability and reliability. The proposed technology routine is compatible with industrial production and may pave the application of stretchable electronics.

Abstract As an optical material, Y2O3 transparent ceramics are desirable for application as laser host materials. However, it is difficult to sinter and dense of Y2O3 hinders the preparation of high-quality optical ceramics via traditional processes. In this work, we use La2O3 as a sintering aid for fabricating high-transparency Y2O3 ceramics using a vacuum sintering process. It is demonstrated that the in-line optical transmittance of 15.0 at% La-doped Y2O3 at a wavelength of 1100 nm achieves a transmittance of 81.2%. A sintering kinetics analysis reveals that a grain-boundary-diffusion-controlled mechanism dominates the faster densification at high La3+ concentrations. It is also shown that both the mechanical and thermal properties of Y2O3 transparent ceramics are significantly improved upon the increase of La2O3 sintering additives. The results indicate that a La-doped Y2O3 transparent ceramic is a promising candidate for a laser host material.

Achieving low conduction loss and good channel mobility is crucial for SiC MOSFETs. However, basic planar SiC MOSFETs provide challenges due to their high density of interface traps and significant gate-to-drain capacitance. In order to enhance the reverse recovery property of the device, a Schottky barrier diode (SBD) was added to the source contact area, the top of the current spreading region, of a trench-etched double-diffused SiC MOS (TED MOS). Two types of SBD structures were optimized to improve the electrical properties using 3D simulation software, “TCAD Silvaco”. During reverse recovery simulation, the carriers of the device were withdrawn from the SBD, indicating that the new design was effective. It also showed that the recovery properties of the new design depended on temperature, carrier lifetime, and the work functions of metals. All the new designs were evaluated in various circumstances to determine the trend. Ultimately, in high-speed switching circuits, the SiC TED MOS with SBD structure efficiently boosted switching speed, while reducing switching loss.

Abstract Flexible thermoelectric generators (f‐TEGs) have demonstrated great potential in wearable self‐powered health monitoring devices. However, the existing wearable f‐TEGs are neither flexible enough to bend and stretch while maintaining the device's integrity with a good TE performance nor directly compatible with clothes materials. Here, ultraflexible fabric‐based thermoelectric generators (uf‐TEGs) are proposed with conductive cloth electrodes and elastic fabric substrate. The patterned elastic fabric substrate fits the rigid cuboids well, together with serpentine structured cloth electrodes, rendering uf‐TEG with excellent integrity and flexibility, thereby achieving a highly functional TE performance when strain reaches 30% or on arbitrarily shaped heat sources. The uf‐TEGs show a large peak power of 64.10 μW for a temperature difference of 33.24 K with a high voltage output of 111.49 mV, which is superior compared to previously reported fabric‐based TEG devices, and it is still functional after the water immersion test. Besides the energy harvesting function, with both the temperature sensing ability and the touch perception, this uf‐TEG is demonstrated as the electrical skin when mounted on a robot. Moreover, due to the wind‐sensitive performance and self‐power ability, the uf‐TEGs are assembled on cloth as wearable health and motion monitoring devices.

In this paper, DC, transient, and RF performances among AlGaN/GaN HEMTs with a no field plate structure (basic), a conventional gate field plate structure (GFP), and a double floating field plate structure (2FFP) were studied by utilizing SILVACO ATLAS 2D device technology computer-aided design (TCAD). The peak electric fields under the gate in drain-side can be alleviated effectively in 2FFP devices, compared with basic and GFP devices, which promotes the breakdown voltage (BV) and suppresses the current collapse phenomenon. As a result, the ON-resistance increase caused by the current collapse phenomena is dramatically suppressed in 2FFP ~19.9% compared with GFP ~49.8% when a 1 ms duration pre-stress was applied with Vds = 300 V in the OFF-state. Because of the discontinuous FP structure, more electric field peaks appear at the edge of the FFP stacks, which leads to a higher BV of ~454.4 V compared to the GFP ~394.3 V and the basic devices ~57.6 V. Moreover, the 2FFP structure performs lower a parasitic capacitance of Cgs = 1.03 pF and Cgd = 0.13 pF than those of the GFP structure (i.e., Cgs = 1.89 pF and Cgd = 0.18 pF). Lower parasitic capacitances lead to a much higher cut-off frequency (ft) of 46 GHz and a maximum oscillation frequency (fmax) of 130 GHz than those of the GFP structure (i.e., ft = 27 GHz and fmax = 93 GHz). These results illustrate the superiority of the 2FFP structure for RF GaN HEMT and open up enormous opportunities for integrated RF GaN devices.

Recess processes for the fabrication of normally-off GaN HEMTs generally compromise devices' on-state performance. In this work, recess-free quasi-normally-off GaN HEMTs with a threshold voltage of 0.24 V is realized by local control of two-dimensional electron gas (2DEG) density. The devices feature a 0.1 μm gate length, SiNx stress liner, and comb gate. SiNx liner can provide significant stress to AlGaN/GaN heterostructure in the scaled gate region. The additional stress translates to the additional electric field and depletes the 2DEG in the gate region. As a result, the quasi-normally-off operation is achieved. Furthermore, the comb gate structure is introduced to suppress the short channel effects, supported by TCAD simulation. The quasi-normally-off devices' excellent on-state performances are benchmarked against the normally-off devices reported recently and a p-GaN HEMT purchased from a commercial foundry. The results support strain engineering as a promising technique to pursue the normally-off operation of GaN HEMTs.

Harvesting the potential performance of GaN-based devices in terms of the areal power density and reliability, relies on the efficiency of their thermal management. Integration of extremely high thermal conductivity Single-crystalline CVD-diamond serves as an efficient solution to their strict thermal requirements. However, the major challenge lies in the Thermal Boundary Resistance (TBR) at the interface of GaN/Diamond or SiC/Diamond. Junction temperature of the device shows a sensitivity of 1.28°C for every unit of TBR for GaN-on-Diamond compared to 0.43°C for every 10 units of TBR for GaN/SiC-on-Diamond. Finite Volume Thermal Analysis has shown a limit of around 22 m2K/GW beyond which the merit of proximity to the heat-source for GaN-on-Diamond can no more outperform GaN/SiC-on-Diamond. Besides, due to the temperature dependency of the thermal conductivity K, an increase in the temperature causes an increase in the thermal resistivity of the device which is more significant in high power operations. Simplified assumption of constant K overestimates the device performance by resulting in 17.4°C lower junction temperature for the areal power density of 10W/mm. Other part of the project regarding the in-house growth of CVD-diamond to be bonded to the GaN device has been simultaneously in progress.

We report a dramatic current reduction, or a resistance increase, by a few orders of magnitude of two common-anode Au/Ti/p-GaN Schottky junctions annealed within a certain annealing condition window (600–700 °C, 1–4 min). Results from similar common-anode Schottky junctions made of Au/p-GaN, Al/Ti/p-GaN, and Au/Ti/graphene/p-GaN junctions demonstrated that all three layers (Au, Ti, and p-GaN) are essential for the increased resistance. Scanning-transmission electron microscopy, Hall, and Raman measurements have been performed to investigate the mechanisms. Moreover, this high-resistance junction structure was employed in p-GaN gate AlGaN/GaN high electron mobility transistors. It was shown to be an effective gate technology that was capable of boosting the gate breakdown voltage from 9.9 to 12.1 V with a negligible effect on the threshold voltage or the sub-threshold slope.

This paper presents the principle, design, fabrication, and characterization of Molecular Electronic Transducer (MET) dual-axis tilt sensors. The proposed sensor has a 3D-printed cylindrical channel inserted with four double-band electrodes and partially filled with a liquid electrolyte. The double-band electrodes were fabricated by wire winding with a ~0.1 mm anode-cathode distance under controlled tension. It allows the electrode to become any 3D coil rather than a 2D structure by microfabrication and exhibits good repeatability (±10%). The tilting changes the electrolyte level and electrode-electrolyte contact area, resulting in Faradaic current changes. The x-axis and the y-axis sensitivity reach 0.121 V/° and 0.154 V/°, respectively.

With the slowdown of Moore’s law, many emerging electronic devices and computing architectures have been proposed to sustain the performance advancement of computing. Among them, the Ising machine is a non-von-Neumann solver that has received wide attention in recent years. It is capable of solving intractable combinatorial optimization (CO) problems, which are difficult to be solve using conventional digital computers. In fact, many CO problems can be mapped to finding the corresponding ground states of Ising model. At present, Ising machine prototypes based on different physical principles, such as emerging memristive oscillators, have been demonstrated, among which the Ising Hamiltonian solver based on the coupled oscillator network simultaneously holds the advantages of room-temperature operation, compact footprint, low power consumption, and fast speed to solution. This paper comprehensively surveys the recent developments in this important field, including the types of oscillators, the implementation principle of the Ising model, and the solver’s performance. Finally, methods to further improve the performance have also been suggested.