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Abstract Hydrocarbons and carbon oxides are typical dissolved gases in transformer oil that reflect the latent pitfalls, on‐line monitoring of their concentrations can effectively evaluate the operating status of the power transformer. However, these low‐concentration targets (especially for CH4) show high chemical inertness at room temperature, challenging the sensitive performance of current commonly used chemiresistive gas sensors. Herein, a strategy by combining traditional inorganic semiconductors to carbon nanofiber (CNF) via electrospinning–annealing route is described. Three optimized 3D mosaic films, CNFs scaffold incorporated with WO3, SnO2 and MoS2 nanoparticles, are obtained. Due to the large specific surface area of the 3D network, and the synergic and heterojunction effects between nanoparticles and CNFs, all three sensors exhibit high response to CH4 at room temperature, and also record distinguishable signals toward H2, C2H4, CO and CO2, revealing the three sensors are cross‐sensitive to the five analytes. Accordingly, preliminary discrimination of five dissolved gases is realized by principle component analysis. This study provides an effective and extendable solution of preparing room‐temperature chemiresistive sensors for the detection of CH4 and other gases, and offers a strategy for the construction of sensor array to achieve a high discrimination capability.

Electric vertical takeoff and landing (eVTOL) aircraft have attracted tremendous attention nowadays due to their flexible maneuverability, precise control, cost efficiency, and low noise. The optimal takeoff trajectory design is a key component of cost-effective and passenger-friendly eVTOL systems. However, conventional design optimization is typically computationally prohibitive due to the adoption of high-fidelity simulation models in an iterative manner. Machine learning (ML) allows rapid decision making; however, new ML surrogate modeling architectures and strategies are still desired to address large-scale problems. Therefore, we showcase a novel regression generative adversarial network (regGAN) surrogate for fast interactive optimal takeoff trajectory predictions of eVTOL aircraft. The regGAN leverages generative adversarial network architectures for regression tasks with a combined loss function of a mean squared error (MSE) loss and an adversarial binary cross-entropy (BC) loss. Moreover, we introduce a surrogate-based inverse mapping concept into eVTOL optimal trajectory designs for the first time. In particular, an inverse-mapping surrogate takes design requirements (including design constraints and flight condition parameters) as input and directly predicts optimal trajectory designs, with no need to run design optimizations once trained. We demonstrated the regGAN on optimal takeoff trajectory designs for the Airbus A3 Vahana. The results revealed that regGAN outperformed reference surrogate strategies, including multi-output Gaussian processes and conditional generative adversarial network surrogates, by matching simulation-based ground truth with 99.6% relative testing accuracy using 1000 training samples. A parametric study showed that a regGAN surrogate with an MSE weight of one and a BC weight of 0.01 consistently achieved over 99.5% accuracy (denoting negligible predictive errors) using 400 training samples, while other regGAN models require at least 800 samples.

With the innovation of wearable technology and the rapid development of biosensors, wearable biosensors based on flexible textile materials have become a hot topic. Such textile-based wearable biosensors promote the development of health monitoring, motion detection and medical management, and they have become an important support tool for human healthcare monitoring. Textile-based wearable biosensors not only non-invasively monitor various physiological indicators of the human body in real time, but they also provide accurate feedback of individual health information. This review examines the recent research progress of fabric-based wearable biosensors. Moreover, materials, detection principles and fabrication methods for textile-based wearable biosensors are introduced. In addition, the applications of biosensors in monitoring vital signs and detecting body fluids are also presented. Finally, we also discuss several challenges faced by textile-based wearable biosensors and the direction of future development.

Biodegradable electronics have great potential to reduce the environmental footprint of electronic devices and to avoid secondary removal of implantable health monitors and therapeutic electronics. Benefiting from the intensive innovation on biodegradable nanomaterials, current transient electronics can realize full components’ degradability. However, design of materials with tissue-comparable flexibility, desired dielectric properties, suitable biocompatibility and programmable biodegradability will always be a challenge to explore the subtle trade-offs between these parameters. In this review, we firstly discuss the general chemical structure and degradation behavior of polymeric biodegradable materials that have been widely studied for various applications. Then, specific properties of different degradable polymer materials such as biocompatibility, biodegradability, and flexibility were compared and evaluated for real-life applications. Complex biodegradable electronics and related strategies with enhanced functionality aimed for different components including substrates, insulators, conductors and semiconductors in complex biodegradable electronics are further researched and discussed. Finally, typical applications of biodegradable electronics in sensing, therapeutic drug delivery, energy storage and integrated electronic systems are highlighted. This paper critically reviews the significant progress made in the field and highlights the future prospects.

Objective: To develop and validate a radiomics predictive model based on multiparameter MR imaging features and clinical features to predict lymph node metastasis (LNM) in patients with cervical cancer.Material and Methods: A total of 168 consecutive patients with cervical cancer from two centers were enrolled in our retrospective study. A total of 3,930 imaging features were extracted from T2-weighted (T2W), ADC, and contrast-enhanced T1-weighted (cT1W) images for each patient. Four-step procedures, mainly minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) regression, were applied for feature selection and radiomics signature building in the training set from center I (n = 115). Combining clinical risk factors, a radiomics nomogram was then constructed. The models were then validated in the external validation set comprising 53 patients from center II. The predictive performance was determined by its calibration, discrimination, and clinical usefulness.Results: The radiomics signature derived from the combination of T2W, ADC, and cT1W images, composed of six LN-status-related features, was significantly associated with LNM and showed better predictive performance than signatures derived from either of them alone in both sets. Encouragingly, the radiomics signature also showed good discrimination in the MRI-reported LN-negative subgroup, with AUC of 0.825 (95% CI: 0.732–0.919). The radiomics nomogram that incorporated radiomics signature and MRI-reported LN status also showed good calibration and discrimination in both sets, with AUCs of 0.865 (95% CI: 0.794–0.936) and 0.861 (95% CI: 0.733–0.990), respectively. Decision curve analysis confirmed its clinical usefulness.Conclusion: The proposed MRI-based radiomics nomogram has good performance for predicting LN metastasis in cervical cancer and may be useful for improving clinical decision making.

Abstract Polyvinylidene fluoride (PVDF) films possess multifunctional ability for piezo/pyro/ferroelectronic applications. One critical challenge of the traditional techniques is the complicated fabrication process for obtaining the poled films. In this work, the PVDF film is facilely prepared by the solution cast on hydrophilically treated substrates. The obtained PVDF films exhibit fairly good pyroelectricity comparable to those fabricated by thermal poling, indicating the film is self-polarized. This result is attributed to the hydrogen-bonding-induced orderly arrangement of the first sub-nanolayer at the bottom, which serves as a “seed layer” and triggered alignment of the rest of the film in a layer-by-layer approach. Additionally, to suppress the piezoelectric noise, a pyroelectric sensor with a novel bilayer structure is developed using the as-prepared PVDF film. Compared with the conventional monolayer sensor, the signal-to-noise ratio of the bilayer one is drastically improved to 38 dB from 18 dB. The above results provide great possibilities for achieving a high-performance wearable pyroelectric sensor with reduced cost and simple procedures.

The monitoring of ethylene is of great importance to fruit and vegetable quality, yet routine techniques rely on manual and complex operation. Herein, a chemiresistive ethylene sensor based on reduced graphene oxide (rGO)/tungsten diselenide (WSe2)/Pd heterojunctions was designed for room-temperature (RT) ethylene detection. The sensor exhibited high sensitivity and quick p-type response/recovery (33/13 s) to 10–100 ppm ethylene at RT, and full reversibility and excellent selectivity to ethylene were also achieved. Such excellent ethylene sensing behaviors could be attributed to the synergistic effects of ethylene adsorption abilities derived from the negative adsorption energy and the promoted electron transfer across the WSe2/Pd and rGO/WSe2 interfaces through band energy alignment. Furthermore, its application feasibility to banana ripeness detection was verified by comparison with routine technique through simulation experiments. This work provides a feasible methodology toward designing and fabricating RT ethylene sensors, and may greatly push forward the development of modernized intelligent agriculture.

A linear hydrogen-bond acidic (HBA) linear functionalized polymer (PLF), was deposited onto a bare surface acoustic wave (SAW) device to fabricate a chemical sensor. Real-time responses of the sensor to a series of compounds including sarin (GB), dimethyl methylphosphonate (DMMP), mustard gas (HD), chloroethyl ethyl sulphide (2-CEES), 1,5-dichloropentane (DCP) and some organic solvents were studied. The results show that the sensor is highly sensitive to GB and DMMP, and has low sensitivity to HD and DCP, as expected. However, the sensor possesses an unexpected high sensitivity toward 2-CEES. This good sensing performance can’t be solely or mainly attributed to the dipole-dipole interaction since the sensor is not sensitive to some high polarity solvents. We believe the lone pair electrons around the sulphur atom of 2-CEES provide an electron-rich site, which facilitates the formation of hydrogen bonding between PLF and 2-CEES. On the contrary, the electron cloud on the sulphur atom of the HD molecule is offset or depleted by its two neighbouring strong electron-withdrawing groups, hence, hydrogen bonding can hardly be formed.

A thin-film transistor (TFT) having an organic–inorganic hybrid thin film combines the advantage of TFT sensors and the enhanced sensing performance of hybrid materials. In this work, poly(3-hexylthiophene) (P3HT)-zinc oxide (ZnO) nanoparticles’ hybrid thin film was fabricated by a spraying process as the active layer of TFT for the employment of a room temperature operated formaldehyde (HCHO) gas sensor. The effects of ZnO nanoparticles on morphological and compositional features, electronic and HCHO-sensing properties of P3HT-ZnO thin film were systematically investigated. The results showed that P3HT-ZnO hybrid thin film sensor exhibited considerable improvement of sensing response (more than two times) and reversibility compared to the pristine P3HT film sensor. An accumulation p-n heterojunction mechanism model was developed to understand the mechanism of enhanced sensing properties by incorporation of ZnO nanoparticles. X-ray photoelectron spectroscope (XPS) and atomic force microscopy (AFM) characterizations were used to investigate the stability of the sensor in-depth, which reveals the performance deterioration was due to the changes of element composition and the chemical state of hybrid thin film surface induced by light and oxygen. Our study demonstrated that P3HT-ZnO hybrid thin film TFT sensor is beneficial in the advancement of novel room temperature HCHO sensing technology.

Increasing light absorption is of crucial importance for optimizing light-activated gas detection. However, the relevant research is still far from sufficient. Herein, a high performance visible light-activated NO _2 gas sensor is developed relied on the localized surface plasmon resonance (LSPR) and increased surface oxygen vacancies. Au NPs decorated ZnO nanorod array as sensitive materials was synthesized via a two-step low temperature hydrothermal process. The influences of Au decoration and light wavelength on the sensing behaviors were systematically investigated. It is found that the Au NPs decoration can largely promote the visible light-activated gas sensing properties in comparison with pure ZnO film. In addition, the as-prepared sensors demonstrate excellent repeatability and selectivity as well as moisture stability. Moreover, the sensing mechanism based on LSPR was discussed in detail. This work not only sheds some lights on the fundamental understanding for the LSPR enhanced gas sensing mechanism, but also offers an approach in constructing high-performance light-activated gas sensor.

An reduced graphene oxide (RGO) resistive gas sensor was prepared to detect ammonia at room temperature, the result indicated that the desorption of gas (NH 3 ) molecules from a graphene-based sensor was difficult, which lead to a baseline drift. The responses of different concentrations were compared and studied. It was found that both the response rate and its acceleration were affected by the gas concentration. An Intermolecular Forces Based Model was established to explain the adsorption and desorption dynamic response curves. A new method was proposed based on this model. The first and second derivative extrema (FSDE) of the response curve can be attained quickly to calibrate the gas concentrations. The experiment results demonstrated that this new method could eliminate the baseline drift and was capable of increasing the efficiency of gas calibration significantly.

3-nitro-1,2,4-triazol-5-one (NTO) is the main component of insensitive munitions (IM) formulation because of its outstanding insensitive properties. In this paper, a series of NTO/HMX-based composite explosives were prepared and characterized. The study focuses on the effect of NTO on the performance of the formulations, especially the safety performance. The results revealed that the mechanical sensitivity of formulations was associated with NTO content, as well as the thermal conductivity, specific heat capacity and Arrhenius parameters. Then, the high amount of NTO using in formulation was proved to be helpful for NTO/HMX-based formulation to exhibit good thermal safety. Besides, by accelerating rate calorimeter (ARC) and a modified cook-off equipment, the pressure and pressure rise rate were proved as the important indicator for judging the thermal safety performance in confined spaces. Finally, the numerical simulation was used as a credible method for predicting the respond temperature of cook-off experiment.