Search

HF trimer, as the smallest and the lightest cyclic hydrogen-bonded (HB) cluster, has long been a favorite prototype system for spectroscopic and theoretical investigations of the structure, energetics, spectroscopy, and dynamics of hydrogen-bond networks. Recently, rigorous quantum 12D calculations of the coupled intra- and intermolecular vibrations of this fundamental HB trimer (J. Chem. Phys.2023, 158, 234109) were performed, employing an older ab initio-based many-body potential energy surface (PES). While the theoretical results were found to be in reasonably good agreement with the available spectroscopic data, it was also evident that it is highly desirable to develop a more accurate 12D PES of HF trimer. Motivated by this, here we report a new, and the first fully ab initio 12D PES of this paradigmatic system. Approximately 42,540 geometries were sampled and calculated at the level of CCSD(T)-F12a/AVTZ. The permutationally invariant polynomial-neural network based Δ-machine learning approach (J. Phys. Chem. Lett.2022, 13, 4729) was employed to perform cost-efficient calculations of the basis-set-superposition error (BSSE) correction. By strategically selecting data points, this approach facilitated the construction of a high-precision PES with BSSE correction, while requiring only a minimal number of BSSE value computations. The fitting error of the final PES is only 0.035 kcal/mol. To assess its performance, the 12D fully coupled quantum calculations of excited intra- and intermolecular vibrational states of HF trimer are carried out using the rigorous methodology developed by us earlier. The results are found to be in a significantly better agreement with the available spectroscopic data than those obtained with the previously existing semiempirical 12D PES.

Spiro-OMeTAD hole transport materials typically exhibit an amorphous state in perovskite solar cells. However, the lack of structural ordering leads to weak intermolecular interaction, inferior carrier transfer, and poor stability in devices. Herein, we developed a π-conjugation-induced short-range ordering strategy to modulate the stacking order of spiro-OMeTAD during film formation. A clear molecular ordering at the nanoscale is observed, which enhances intermolecular π–π stacking in spiro-OMeTAD and enables effective carrier extraction and favorable energy level alignment. The nanoscale-ordered spiro-OMeTAD allows the achievement of perovskite solar cells with a champion efficiency of 25.37%, surpassing devices utilizing amorphous spiro-OMeTAD (23.52%). The unencapsulated device demonstrates enhanced operational stability by retaining 98% of its initial efficiency under continuous 1 sun equivalent illumination at 60 °C for 840 h. This work establishes a significant and valid modulation concept for the stacking order of organic transport materials, paving the way for the development of efficient and stable perovskite solar cells.

The potential universality of chemical transformation principles makes it a powerful tool for nanocrystal (NC) synthesis. An example is the nanoscale Kirkendall effect, which serves as a guideline for the construction of hollow structures with different properties compared to their solid counterparts. However, even this general process is still limited in material scope, structural complexity, and, in particular, transformations beyond the conventional solid-to-hollow process. We demonstrate in this work an extension of the Kirkendall effect that drives reversible structural and phase transformations between metastable metal chalcogenides (MCs) and metal phosphides (MPs). Starting from Ni3S4/Cu1.94S NCs as the initial frameworks, ligand-regulated sequential extractions and diffusion of host/guest (S2–/P3–) anions between Ni3S4/Cu1.94S and Ni2P/Cu3P phases enable solid-to-hollow-to-solid structural motif evolution while retaining the overall morphology of the NC. An in-depth mechanistic study reveals that the transformation between metastable MCs and MPs occurs through a combination of ligand-dependent kinetic control and anion mixing-induced thermodynamic control. This strategy provides a robust platform for creating a library of reconfigurable NCs with tunable compositions, structures, and interfaces.

The microcephaly-capillary malformation (MIC-CAP) syndrome is a life-threatening disease caused by biallelic mutations of the STAMBPgene, which encodes an endosomal deubiquitinating enzyme. To establish a suitable preclinical animal model for clinical therapeutic practice, we generated a central nervous system (CNS)-specific Stambpknockout mouse model (Stambp Sox1−cKO) that phenocopies Stambpnull mice including progressive microcephaly, postnatal growth retardation and complete penetrance of preweaning death. In this MIC-CAP syndrome mouse model, early-onset neuronal death occurs specifically in the hippocampus and cortex, accompanied by aggregation of ubiquitinated proteins, and massive neuroinflammation. Importantly, neonatal AAV9-mediated gene supplementation of Stambpin the brain could significantly improve neurological defects, sustain growth, and prolong the lifespan of StambpSox1−cKOmice. Together, our findings reveal a central role of brain defects in the pathogenesis of STAMBPdeficiency and provide preclinical evidence that postnatal gene replacement is an effective approach to cure the disease.

Due to their radiation hardness and thermal resistance properties, silicon carbide (SiC) detectors have received much attention for neutron detection. To solve the problem of low detection efficiency in thin-film-coated planar neutron detectors, a $1\times 1$ cm microstructured neutron detector (MSND) based on 500- $\mu $ m high-purity semi-insulating (HPSI) 4H-SiC is fabricated. By utilizing inductively coupled plasma (ICP) etching technique, deep trenches are etched on the SiC wafer, with a trench depth of $\sim 51~\mu $ m and an aspect ratio $\ge 5$ . Nanoscale 6LiF powder, serving as the neutron conversion material, is dissolved in alcohol and filled into the trenches using a liquid centrifugation method. When the reverse bias voltage is up to −800 V, its dark current is lower than 6 nA. Experimental results show that the maximum value of the neutron detection efficiency is 3.28%. In the subsequent research, we will continue to optimize the deep etching process of SiC materials and the filling process of 6LiF powder, which should improve the detection efficiency further.

This article presents a novel method for monitoring leakage in buried natural gas pipelines. The method is based on phase-sensitive time-domain distributed reflection detection ( $\Phi $ -OTDR) technology, which can classify and identify small leakage signals under different pressures. The article compares and evaluates three time-frequency analysis methods for leakage signals: horizontal synchrosqueezing transform (HST), time-reassigned synchrosqueezing transform (TSST), and synchronous wavelet transform (SST). It also applies you only look once (YOLO) to classify small leakage events under different pressures. The experimental results demonstrate that the HST method outperforms other methods in both feature extraction and event classification. It can effectively distinguish small leakage signals under different pressures, achieving a classification accuracy of 89.87%. Therefore, this article offers an effective technical solution for monitoring and early warning of leaks in buried natural gas pipelines.

Integrated sensing and communication (ISAC) systems traditionally presuppose that sensing and communication (S&C) channels remain approximately constant during their coherence time. However, a “DISCO” reconfigurable intelligent surface (DRIS), i.e., an illegitimate RIS with random, time-varying reflection properties that acts like a “disco ball,” introduces a paradigm shift that enables active channel aging more rapidly during the channel coherence time. In this letter, we investigate the impact of DISCO jamming attacks launched by a DRIS-based fully-passive jammer (FPJ) on an ISAC system. Specifically, an ISAC problem formulation and a corresponding waveform optimization are presented in which the ISAC waveform design considers the trade-off between the S&C performance and is formulated as a Pareto optimization problem. Moreover, a theoretical analysis is conducted to quantify the impact of DISCO jamming attacks. Numerical results are presented to evaluate the S&C performance under DISCO jamming attacks and to validate the derived theoretical analysis.

Although the majority of recent autonomous driving systems concentrate on developing perception methods based on ego-vehicle sensors, there is an overlooked alternative approach that involves leveraging intelligent roadside cameras to help extend the ego-vehicle perception ability beyond the visual range. We discover that most existing monocular 3D object detectors rely on the ego-vehicle prior assumption that the optical axis of the camera is parallel to the ground. However, the roadside camera is installed on a pole with a pitched angle, which makes the existing methods not optimal for roadside scenes. In this paper, we introduce a novel framework for Roadside Monocular 3D object detection with ground-aware embeddings, named MonoGAE. Specifically, the ground plane is a stable and strong prior knowledge due to the fixed installation of cameras in roadside scenarios. In order to reduce the domain gap between the ground geometry information and high-dimensional image features, we employ a supervised training paradigm with a ground plane to predict high-dimensional ground-aware embeddings. These embeddings are subsequently integrated with image features through cross-attention mechanisms. Furthermore, to improve the detector’s robustness to the divergences in cameras’ installation poses, we replace the ground plane depth map with a novel pixel-level refined ground plane equation map. Our approach demonstrates a substantial performance advantage over all previous monocular 3D object detectors on widely recognized 3D detection benchmarks for roadside cameras. The code and pre-trained models will be released soon.

In this article, the reinforcement learning-based distributed robust bipartite consensus control of multispacecraft systems with dynamic uncertainties is investigated. The developed control structure includes two parts, i.e., integral sliding mode control and distributed optimal bipartite consensus control. In the first step, an integral sliding mode controller is designed for each following spacecraft to address matched uncertainties such that the dynamics of nominal spacecraft is obtained. In the second step, a novel performance index function, which contains consensus errors and their derivatives, is designed for each nominal spacecraft. As a result, the system assumption of zero equilibrium and the discount factor in performance index function are not required, which simplifies the controller design process and improves the practicability of the developed control method. Moreover, in order to solve the coupled Hamilton–Jacobi–Bellman equation of each following spacecraft, a novel policy iteration algorithm is designed and its properties are analyzed. Finally, a group of spacecraft is employed to verify the effectiveness of the present control scheme.

Full-sequence program (FSP) can program multiple bits simultaneously, and thus complete a multiple-page write at one time for naturally enhancing write performance of high density 3-D solid-state drives (SSDs). This article proposes an FSP scheduling approach for the 3-D quad-level cell (QLC) SSDs, to further boost their read responsiveness. Considering each FSP operation in QLC SSDs spans four different types of QLC pages having dissimilar read latency, we introduce matching four pages of application data to the suited QLC pages and flush them together with the one-shot program of FSP. To this end, we employ reinforcement learning to classify the (cached) application data into four categories on the basis of their historical access frequency and the associating request size. Thus, the frequently read data can be mapped to the QLC pages having less access latency, meanwhile the other data can be flushed onto the slow QLC pages. Then, we can group four different categories of data pages and flush them together into a four-page unit of 3-D QLC SSDs with an FSP operation. In addition, a proactive rewrite method is also triggered for grouping the hot read data with the cached data to form an FSP unit. Through a series of emulation tests on several realistic disk traces, we show that the proposed mechanisms yields notable performance improvement on the read responsiveness.

Metal-organic frameworks (MOFs) hold immense promise for low-temperature denitrification (de-NOx) owing to their tunable pore size and active sites, nevertheless, their practical application is impeded by low yields. In this investigation, we introduce a synergistic modulated hydrothermal (SMHT) method designed to cooperatively control pre-cluster and solution pH using acetic acid and N, N-dimethylformamide, with the aim of enhancing MOFs yields. The TEOS&Mn-BTC-HY catalyst synthesized by the method of SMHT successfully increased the yield from 21 % of the input to 63 % compared with the TEOS&Mn-BTC catalyst synthesized by the hydrothermal method. Characterization analysis and performance testing reveal that the structure of TEOS&Mn-BTC-HY is minimally affected by the SMHT method, and its performance remains excellent. The de-NOxefficiency remained above 90 % in the temperature range of 90–300 ℃, and even under challenging conditions such as 6 % H2O or 100 ppm SO2at 150 ℃ for 10 h, the performance still exceeded 90 %. The designed SMHT process offers valuable insights for expanding MOFs production and further advancing the application of MOFs in the realm of de-NOx.

Surface electromyography (sEMG) signals are crucial bioelectrical signals that offer valuable insights into muscle activity and motor control. However, sEMG signals are susceptible to interference from various sources, including environmental factors and physiological crosstalk, power noise, and motion artifacts. These interferences can compromise the quality and accuracy of the sEMG signals. The challenge remains to achieve high temporal and spatial resolution for detecting sEMG signals. In this study, novel active electrodes with a high-gain pixel-level amplifier were developed using amorphous indium gallium zinc oxide (a-IGZO) thin-film transistor (TFT) technology to collect sEMG signals. To achieve high signal gain, a wide input voltage range, and low noise, we designed a bootstrap negative feedback amplifier circuit based on a-IGZO TFTs. The active amplifier circuit exhibited a signal gain of approximately 21.9 dB at a driving voltage of 15 V and a gain bandwidth of 1.5 kHz. Compared with the traditional passive electrode, the signal-to-noise ratio (SNR) of the signal collected by the active electrode is 194% of the passive electrode, and the signal reliability is significantly improved. As a result, the active electrodes present distinct advantages in terms of stability, flexibility, and high gain. This innovation paves the way for high-quality acquisition of surface EMG signals.

Aim:To explore the complex relationship between gut microbiota, obesity-related male reproductive impairments, and the NLRP3 inflammasome.Methods:A high-fat diet was administered to induce obesity in a mouse model, fecal microbiota transplantation or a high-dietary fiber diet (HDFD) was administered for 5 weeks to evaluate changes in parameters related to reproductive capacity, NLRP3, gut microbiota composition and metabolites in mice.Results:A high-fat diet induces obesity and decreases reproductive capacity in male mice. Fecal microbiota transplantation and HDFD can improve reproductive capacity in obese mice by adjusting the gut microbiota population to suppress the NLRP3/ASC/caspase-1 axis, thereby reducing IL-1β levels.Conclusion:This study offers a potential treatment for obesity-induced reproductive dysfunction by targeting the gut microbiota and the NLRP3 inflammasome pathway.

Nanolayered Zr/Nb metals are considered promising for advanced nuclear reactors due to their superior resistance to irradiation. In this study, Zr/Nb multilayers were irradiated with 50 keV He+ions to a fluence of 1 × 1017ions/cm2at temperatures of room temperature, 350 °C, and 500 °C to investigate irradiation-induced structural changes. X-ray diffraction (XRD) analysis indicated low-angle shifts of 0.08–0.54° and high-angle shifts of 0.08–0.42° in the irradiated Zr and Nb layers, suggesting tensile and compressive strains, respectively. At 500 °C, the selected-area electron diffraction (SAED) observed a 9.2% lattice expansion in Zr and a 0.13% contraction in Nb. Geometric phase analysis (GPA) revealed varying strain distributions, transitioning from incoherent to coherent interfaces with increasing irradiation damage. Transmission electron microscopy (TEM) identified the presence of He bubbles in the Zr layer as one of the reasons for strain differences. Nanoindentation tests showed an increase at a depth of 150 nm hardness of 0.831 GPa at 500 °C compared to 350 °C. These results are attributed to differences in crystal structure, vacancy dynamics, interfacial effects, and lattice strain influences. Stability of Zr/Nb interfaces after He irradiation was studied. This study provides insights into the radiation behavior of Zr/Nb nanoscale metallic materials, enhancing our understanding of their potential as structural materials in nuclear energy systems.

In the absence of an official statement about a rumor, people may expose the truth behind such rumor through their responses on social media. Due to the varying relevance of responses in exposing hidden suspicious points within a rumor claim, it is crucial to prioritize those with higher relevance, rather than considering every responding tweets. As for the multi-modal rumor detection, an effective approach for evaluating relevance is aligning responses with the different modalities of the rumor claim in a fine-grained manner. However, owing to the substantial volume of response tweets, it is both costly and redundant to align all responses with the multi-modal claim. In this paper, we propose a novel two-stage model, termed Focal Reasoning Model (FoRM), to select critical responses for multi-modal rumor detection. More specifically, our FoRM consists of two primary elements: coarse-grained selection and fine-grained reasoning. The coarse-grained selection component employs post-level features of responses to initialize a relevant score for each. Based on these scores, we preserve the responses with higher scores as the candidate ones for subsequent reasoning. Within the fine-grained reasoning component, we develop a relation attention module to investigate fine-grained relationships, specifically token-to-token and token-to-object connections, between the preserved responses and the multi-modal claim, with the goal of discovering valuable clues. Extensive experiments have been conducted on three real-world datasets, and the results demonstrate that our proposed model outperforms all the baselines.

Demand-side mitigation relies on individuals’ and households’ willingness to alter their consumption habits and daily routines to reduce their carbon footprint. Despite optimistic forecasts for well-being improvements, broad adoption of these behavioural changes remains elusive. Our study analyses 12 behaviours in Beijing, China, using a cost–benefit approach that includes both tangible (pecuniary) and intangible (non-pecuniary) benefits. Our findings indicate that eight behaviours result in individual-level welfare loss. Even after accounting for mitigation benefits, seven behaviours still incur social-welfare loss. Monte Carlo simulations unveil substantial variability in welfare impacts, highlighting opportunities for targeted policy interventions. Depending on the perspective (individual versus societal) and the goal (welfare versus mitigation), we recommend four demand-side practices for Beijing policymakers. In addition, we propose actionable steps on the basis of sensitivity analyses. This study underscores the need for an objective and universally applicable framework to evaluate demand-side behaviours and optimize emissions reduction potential.

The microstructure and properties of Cu66.6(FeCo)33.4and Cu60(FeCo)40alloys were investigated. Microstructural observations show that CuFeCo alloys have formed dual-phase heterostructures comprising face-centered cubic (FCC) and body-centered cubic (BCC) phases. The average grain size of the CuFeCo alloys after cold rolling and aging is less than 10 μm. Cu66.6(FeCo)33.4has better elongation and electrical conductivity, while Cu60(FeCo)40has better tensile strength, hardness, saturation magnetization, and electromagnetic interference shielding effectiveness. An increased FeCo content in a finer second phase with a larger volume fraction, leading to more phase boundaries. This enhances the strength of the CuFeCo alloys while simultaneously reducing their elongation. The obtained results can be used for further development of alloys with FCC/BCC dual-phase heterostructures.

To ensure safer drilling and to prevent kicks and blowouts, Managed Pressure Drilling (MPD) technology has been proposed. However, conventional MPD necessitates manual operation of the choke within the choke manifolds by engineers, a task heavily reliant on their experience. This paper proposes a PID controller tuned using the Dung Beetle Optimizer (DBO) and details several laboratory experiments on automatic choke control utilising DBO-PID alongside a modified hydraulic control box. The experimental results demonstrate that DBO-PID can quickly and stably control the surface back pressure (SBP) to the desired level. Following extensive laboratory experiments validation, a field experiment implementing DBO-PID with a hydraulic control box was conducted on an offshore platform. The field experiment results indicate that DBO-PID is 29 % faster than manual control by an engineer in stabilising the SBP, with an overshoot of less than 4 % when nearing the target SBP. Additionally, during the control processes for both constant and variably targeted SBP, pressure fluctuation was 72 % and 63 % less, respectively, compared to manual operation. Both laboratory and field experiments have conclusively demonstrated that the automatic choke control system, comprising DBO-PID and a hydraulic control box, can efficiently manage SBP, thereby preventing kicks and blowouts. Furthermore, this system could replace manual operations in MPD, enhancing the safety of oil and gas resource development, protecting engineers' lives, and safeguarding the natural environment.

Water-soluble binders for electrode preparation offer advantages over traditional PVDF, including environmental benefits, improved electrochemical performance, and improved mechanical properties. The trend is to find environmentally friendly binders that are compatible with water-based processes. In this context, we designed and synthesized aqueous binders with three-dimensional crosslinked structures. These structures are based on highly branched, hydrophilic polyvinyl alcohol and lithium carboxymethyl cellulose, which facilitates Li+transport. Furthermore, LiMn2O4/C/PVA-c-CMCLi film electrodes were prepared through covalent crosslinking. The film electrode was superior to the LiMn2O4/C/PVDF film electrode in terms of adsorption capacity (25.53 mg·g−1), but comparable to the LiMn2O4/C/PVDF film electrode in terms of cyclic stability (96.38 % capacity retention after 50 CV cycles). They also showed a shorter time to reach the adsorption equilibrium (2 h) and high selectivity for Li+in simulated brine with a high Mg2+/Li+ratio (40) from East Taijiner. This is attributed to the synergistic effects of the improved electrolyte wettability, enhanced adhesion strength through covalent crosslinking, and increased Li+transport rate facilitated by -COOLi in CMCLi. These results indicate that this binder has the potential to replace PVDF in the preparation of film electrodes for extracting Li+from brine with high Mg2+/Li+ratios.

Single-crystal Ni-rich cathode with surface-to-bulk high-valence W6+modification was achieved, featuring W-doped bulk and Li2WO4surface layer. The W-modified sample delivers excellent cycling stability, which has 89.8% capacity retention after 300 cycles at 0.5 C.