High-κ monocrystalline dielectrics for low-power two-dimensional electronics.

The downscaling of complementary metal-oxide-semiconductor technology has produced breakthroughs in electronics, but more extreme scaling has hit a wall of device performance degradation. One key challenge is the development of insulators with high dielectric constant, wide bandgap and high tunnel masses. Here, we show that two-dimensional monocrystalline gadolinium pentoxide, which is devised through combining particle swarm optimization algorithm and theoretical calculations and synthesized via van der Waals epitaxy, could exhibit a high dielectric constant of ~25.

Cd indirectly affects the structure and function of plankton ecosystems by affecting trophic interactions at environmental concentrations.

The toxic effects of potentially toxic elements have been observed at low concentrations; however, many studies have focused on single-species toxicity testing. Consequently, it is imperative to quantify toxicity at the community level at environmental concentrations. A microcosm approach was employed in conjunction with the Lotka-Volterra model to ascertain the impact of environmentally relevant concentrations of cadmium (Cd) on plankton abundance, community function, and stability.

Relative prevalence of top-down versus bottom-up control in planktonic ecosystem under eutrophication and climate change: A comparative study of typical bay and estuary.

Eutrophication and climate change may affect the top-down versus bottom-up controls in aquatic ecosystems. However, the relative prevalence of the two controls in planktonic ecosystems along the eutrophication and climate gradients has rarely been addressed. Here, using the field surveys of 17 years in a typical bay and estuary, we test two opposite patterns of trophic control dominance and their response to regional temporal eutrophication and climate fluctuations.

Temperature and nutrients alter the relative importance of stochastic and deterministic processes in the coastal macroinvertebrates biodiversity assembly on long-time scales.

Macroinvertebrates play a vital role in coastal ecosystems and are an important indicator of ecosystem quality. Both anthropogenic activity and environmental changes may lead to significant changes in the marine macroinvertebrate community. However, the assembly process of benthic biodiversity and its mechanism driven by environmental factors at large scales remains unclear.

Active Learning the High-Dimensional Transferable Hubbard and Parameters in the DFT + + Scheme.

Density functional theory (DFT) is a powerful quantum mechanical computational tool to perform electronic structure calculations for materials. Few DFT methods can ensure accuracy and efficiency simultaneously. DFT + + is an alternative effective approach to overcome this drawback.

Machine Learning Paves the Way for High Entropy Compounds Exploration: Challenges, Progress, and Outlook.

Machine learning (ML) has emerged as a powerful tool in the research field of high entropy compounds (HECs), which have gained worldwide attention due to their vast compositional space and abundant regulatability. However, the complex structure space of HEC poses challenges to traditional experimental and computational approaches, necessitating the adoption of machine learning. Microscopically, machine learning can model the Hamiltonian of the HEC system, enabling atomic-level property investigations, while macroscopically, it can analyze macroscopic material characteristics such as hardness, melting point, and ductility.

MTA1, a Novel ATP Synthase Complex Modulator, Enhances Colon Cancer Liver Metastasis by Driving Mitochondrial Metabolism Reprogramming.

Liver metastasis is the most fatal event of colon cancer patients. Warburg effect has been long challenged by the fact of upregulated oxidative phosphorylation (OXPHOS), while its mechanism remains unclear. Here, metastasis-associated antigen 1 (MTA1) is identified as a newly identified adenosine triphosphate (ATP) synthase modulator by interacting with ATP synthase F1 subunit alpha (ATP5A), facilitates colon cancer liver metastasis by driving mitochondrial bioenergetic metabolism reprogramming, enhancing OXPHOS; therefore, modulating ATP synthase activity and downstream mTOR pathways.

Liquid metal for high-entropy alloy nanoparticles synthesis.

High-entropy alloy nanoparticles (HEA-NPs) show great potential as functional materials. However, thus far, the realized high-entropy alloys have been restricted to palettes of similar elements, which greatly hinders the material design, property optimization and mechanistic exploration for different applications. Herein, we discovered that liquid metal endowing negative mixing enthalpy with other elements could provide a stable thermodynamic condition and act as a desirable dynamic mixing reservoir, thus realizing the synthesis of HEA-NPs with a diverse range of metal elements in mild reaction conditions.

High-Throughput Screening of Gas Sensor Materials for Decomposition Products of Eco-Friendly Insulation Medium by Machine Learning.

Nowadays, trifluoromethyl sulfonyl fluoride (CFSOF) has shown great potential to replace SF as an eco-friendly insulation medium in the power industry. In this work, an effective and low-cost design strategy toward ideal gas sensors for the decomposed gas products of CFSOF was proposed. The strategy achieved high-throughput screening from a large candidate space based on first-principle calculation and machine learning (ML).

Quantifying hydrological-ecological response relationships based on zooplankton index of biotic integrity and comprehensive habitat quality index - A case study of typical rivers in Xi'an, China.

With the accelerated development of urbanization, rivers in urban areas have become the most closely synergized water ecosystem between human activities and natural processes. To achieve the restoration goal of using hydrological regime change-ecological response relationship to advance the sustainable development of regulated river ecosystems, this study collected ecohydrological data at four tributaries of the Wei River system (Ba, Chan, Feng, and Hei Rivers) at a total of 24 stations in October 2020 and June 2021. Taking ecological flow as hydrological parameter and zooplankton as indicator organism, combined with habitat data scored on-site, the indicator system of zooplankton index of biological integrity and comprehensive habitat quality index was established to explore the hydrological-ecological response relationship in a multi-dimensional way.

Machine-learning-assisted discovery of highly efficient high-entropy alloy catalysts for the oxygen reduction reaction.

High-entropy alloys (HEAs) have recently been applied in the field of heterogeneous catalysis benefiting from vast chemical space. However, huge chemical space also brings extreme challenges for the comprehensive study of HEAs by traditional trial-and-error experiments. Therefore, the machine learning (ML) method is presented to investigate the oxygen reduction reaction (ORR) catalytic activity of millions of reactive sites on HEA surfaces.

Strain-promoted conductive metal-benzenhexathiolate frameworks for overall water splitting.

Designing efficient catalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is a desirable strategy for overall water splitting and the generation of clean and renewable energies. Herein, the electrocatalytic HER and OER activity of the conductive metal-benzenhexathiolate (M-BHT) frameworks has been evaluated utilizing first-principles calculations. The in-plane π-d conjugation of M-BHT guarantees fast electron transfer during electrocatalytic reactions.

A Feasible Strategy for Identifying Single-Atom Catalysts Toward Electrochemical NO-to-NH Conversion.

Combining NO removal and NH synthesis, electrochemical NO reduction reaction (NORR) toward NH is considered as a novel and attractive approach. However, exploring suitable catalysts for NO-to-NH conversion is still a formidable task due to the lack of a feasible method. Herein, utilizing systematic first-principles calculations, a rational strategy for screening efficient single-atom catalysts (SACs) for NO-to-NH conversion is reported.

Machine-Learning-Accelerated Catalytic Activity Predictions of Transition Metal Phthalocyanine Dual-Metal-Site Catalysts for CO Reduction.

The highly active and selective carbon dioxide reduction reaction (CORR) can generate valuable products such as fuels and chemicals and reduce the emission of greenhouse gases. Single-atom catalysts (SACs) and dual-metal-sites catalysts (DMSCs) with high activity and selectivity are superior electrocatalysts for the CORR as they have higher active site utilization and lower cost than traditional noble metals. Herein, we explore a rational and creative density-functional-theory-based, machine-learning-accelerated (DFT-ML) method to investigate the CORR catalytic activity of hundreds of transition metal phthalocyanine (Pc) DMSCs.

The Electrophilicity of Surface Carbon Species in the Redox Reactions of CuO-CeO Catalysts.

Electronic metal-support interactions (EMSI) describe the electron flow between metal sites and a metal oxide support. It is generally used to follow the mechanism of redox reactions. In this study of CuO-CeO redox, an additional flow of electrons from metallic Cu to surface carbon species is observed via a combination of operando X-ray absorption spectroscopy, synchrotron X-ray powder diffraction, near ambient pressure near edge X-ray absorption fine structure spectroscopy, and diffuse reflectance infrared Fourier transform spectroscopy.

A novel comprehensive model of set pair analysis with extenics for river health evaluation and prediction of semi-arid basin - A case study of Wei River Basin, China.

The accelerated development of urbanization in semi-arid areas is easy to cause varying degrees of disturbance to its fragile aquatic ecosystem. To find a general method for assessing the health status in semi-arid basins in China, and to provide theoretical basis for river health management and sustainable development, this study is that health evaluation index system is established in the Wei River Basin, covering a huge semi-arid area, and analyzed the biological structure of plankton obtained by field sampling and identified in laboratory, chemical conditions including dissolved oxygen, water temperature, ammonia nitrogen, pH, chlorophyll and other water physical and chemical factors determined by field instruments and sediment heavy metals analyzed in laboratory, physical habitat scored on site and social factors including water resource utilization rate and water consumption per 10,000 yuan of GDP collected in local water resource bulletin. Based on the idea of game theory, an improved coupling model of set pair analysis with extenics is established to assess and predict health.

Tellurium Nanowire Gate-All-Around MOSFETs for Sub-5 nm Applications.

The nanowire (NW) and gate-all-around (GAA) technologies are regarded as the ultimate solutions to sustain Moore's law benefitting from the exceptional gate control ability. Herein, we conduct a comprehensive ab initio quantum transportation calculation at different diameters (single trigonal-tellurium NW (1Te) and three trigonal-tellrium NW (3Te)) sub-5 nm tellurium (Te) GAA NW metal-oxide-semiconductor field-effect transistors (MOSFETs). The results claim that the performance of 1Te FETs is superior to that of 3Te FETs.

Comprehensive ecological risk assessment for semi-arid basin based on conceptual model of risk response and improved TOPSIS model-a case study of Wei River Basin, China.

Comprehensive ecological risk assessment is of great significance for the restoration of watershed ecosystem health, and the appropriate and effective assessment method is the premise of ecological risk assessment. In this study, the conceptual model of risk response was developed by identification of ecological risk sources, stressors, endpoints and the corresponding response mechanism as well as the improved TOPSIS model based on Canberra distance and the combinatorial weighting method based on AHP and Critic were combined for the assessment. According to the three aspects of agriculture, industrial and urbanization, the occurrence mechanism of comprehensive ecological risk of rivers in semi-arid areas was analyzed.