Yuanyue Liu

Two-dimensional (2D) transition metal dichalcogenides (TMDs) typically degrade through atom-by-atom removal under chemical or electron beam stimuli. Here, we report a fundamentally different degradation pathway in CVD-grown monolayer rhenium disulfide (ReS 2 ), whereby the lattice fragments into stable, discrete molecular clusters under electron irradiation and when etched with a 1 M KOH solution. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy reveals the atomic arrangement of these clusters, while single-particle analysis reconstruction resolves their three-dimensional structure with near-atomic precision. Time-resolved imaging demonstrates that both the transfer process and beam-induced effects drive the lattice-to-cluster transformation. These findings reveal an unconventional degradation pathway in ReS 2, distinct from other 2D TMDs, where its molecular-like bonding drives the production of well-defined Re–S clusters, thereby providing a direct link between 2D materials science and transition-metal cluster chemistry.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) typically degrade through atom-by-atom removal under chemical or electron beam stimuli. Here, we report a fundamentally different degradation pathway in CVD-grown monolayer rhenium disulfide (ReS₂), whereby the lattice fragments into stable, discrete molecular clusters under electron irradiation and when etched with a 1 M KOH solution. Aberration-corrected high-angle annular dark-field scanning transmission electron microscopy reveals the atomic arrangement of these clusters, while single-particle analysis reconstruction resolves their three-dimensional structure with near-atomic precision. Time-resolved imaging demonstrates that both the transfer process and beam-induced effects drive the lattice-to-cluster transformation. These findings reveal an unconventional degradation pathway in ReS₂, distinct from other 2D TMDs, where its molecular-like bonding drives the production of well-defined Re–S clusters, thereby providing a direct link between 2D materials science and transition-metal cluster chemistry.

High Resolution Image Download MS PowerPoint Slide A major hurdle to the implementation of single-atom catalysts (SACs) in real-world systems is a poor understanding of their stability under operating conditions, which is particularly relevant due to the high surface free energy of SACs. Here, we evaluated the aggregation behavior of a suite of SACs varied by metal identity (Fe, Co, Ni, and Cu) during electrocatalytic nitrate reduction using in situ X-ray absorption spectroscopy. The metal center had significant influence on reconstruction, where under identical applied reductive potentials, SACs underwent varying levels of reconstruction, ranging from no discernible change to complete reduction into metallic nanoparticles. Such in situ experiments revealed Cu SACs to be the most susceptible to aggregation, prompting a deeper investigation into how coordination environment (O-, B-, and N-graphene) affected Cu SAC aggregation. We further conducted density functional theory calculations to elucidate the relationship between Cu SAC structure and stability. This work deconvolutes the relationship between SAC architecture and stability, which is essential to evaluate and explain for the realization of SACs for electrocatalysis.

Raw data of figures and AIMD/PIMD trajectories in the paper and corresponding supporting Information.

Raw data of figures and AIMD/PIMD trajectories in the paper and corresponding supporting Information.

While single-atom catalysts (SACs) are often touted for their maximal atomic efficiency and enhanced activity compared to nanoparticle counterparts, our understanding of SAC stability is severely lacking. The atomic dispersion of SACs leads to a high surface free energy, which can result in single-atom aggregation. Such instability can be further exacerbated by reaction conditions, such as temperature, gaseous atmosphere, or applied potential. Here, we investigated the stability of a series of SACs of various metal identities during electrocatalytic nitrate reduction by potential-resolved in situ X-ray absorption spectroscopy (XAS). We demonstrate the metal center to have significant influence on stability, where under an identical applied potential pattern, SACs underwent varying levels of reconstruction ranging from minimal change to complete reduction into metallic particles. The in situ XAS experiments revealed Cu SACs to be the most vulnerable to aggregation, prompting a deeper investigation into how the coordination environment surrounding Cu affected aggregation. We lastly conducted density functional theory calculations to determine the relationship between Cu SAC structure and stability. Determining the relationship between SAC structure and stability is essential to evaluate for the implementation of SACs to real-world electrocatalytic systems, as the line between stability and activity is not always clear.

Charged defect scattering of electrons plays a critical role in determining a wide range of material properties. However, there is a lack of an accurate method to calculate the scattering, as all the existing methods require assuming a specific distribution for unscreened (i.e., bare) excess charge carried by the defect, which limits their accuracy. Here we develop a first-principles method to determine the bare charge distribution, which thus enables accurate calculations of the scattering. Using this method, we accurately calculate the electron mobility of 2D MoS_{2} under the scattering of charged sulfur vacancies and compare with that of charge-neutral oxygen substitutes of sulfur. Interestingly, we find that the charged defect-limited mobility exhibits a strong temperature dependence at low temperature and carrier concentration, in contrast to the neutral defect and the conventional belief that the defect-limited mobility is less sensitive to the temperature. This behavior arises from the free carrier screening of the long-range scattering potential of the charged defect. Our work offers new insights into the transport mechanism, and opens access to accurate calculation, understanding, and prediction of charged defect scattering and a broad range of associated properties.

Better understanding and prediction of the electrochemical interface require large-scale atomistic simulations. Machine learning force fields (MLFFs) have proven to be an effective approach. However, current MLFFs typically do not account for the effect of electrode potential, which requires treating interface electrons with a grand canonical ensemble. Here, we develop a constant potential MLFF (CP-MLFF) based on an equivariant graph neural network and implement it into MACE. Specifically, we design an architecture that can take the number of electrons as the input and accurately predict the Fermi level. The CP-MLFF allows us to examine the convergency of the electrochemical barrier with respect to sampling, which we demonstrate through the example of CO 2 reduction on the Ni–N–C catalyst. Our work provides a useful method and tool enabling accurate and efficient large-scale simulation of the electrochemical interface.

BACKGROUND Previous research has established that physical activity (PA) benefits executive function (EF) in children and adolescents. However, the dose response relationship between PA and EF remains unclear. This study aimed to evaluate the impact of PA on EF and to characterize dose-response relationships across PA modalities. METHODS A comprehensive systematic search was conducted across five databases-PubMed, Web of Science, Embase, Scopus, and Cochrane Library-to identify randomized controlled trials (up to April 2025) assessing the effects of PA on EF in children and adolescents. A dose response model-based network meta-analysis was utilized to synthesize the evidence and estimate the effects of different types and doses of PA on EF. RESULTS PA had a small but statistically significant positive effect on EF (Hedges' g = 0.14, 95 % CrI [0.08, 0.19]), with more pronounced effects in children than in adolescents, and effects varied across EF subdomains. Among the PA modalities examined, aerobic exercise demonstrated the most substantial effect (Hedges' g = 0.22, 95 % CrI [0.13, 0.32]), followed by skill/coordination activities (Hedges' g = 0.17, 95 % CrI [0.07, 0.26]). High-intensity interval training and cognitively engaging PA also showed promising results, although further data were required to clarify their impact. CONCLUSION PA exerted a positive influence on EF in children, exhibiting dose-dependent effects. In particular, aerobic exercise, and skill/coordination activities at moderate levels of intensity are efficacious, demonstrating a distinct inverted U-shaped dose-response relationship. These findings offer actionable evidence for designing targeted PA interventions to optimize cognitive benefits.

The electrochemical reduction of carbon dioxide (CO2) to carbon monoxide (CO) is challenged by a selectivity decline at high current densities. Here we report a class of indigo-based molecular promoters with redox-active CO2 binding sites to enhance the high-rate conversion of CO2 to CO on silver (Ag) catalysts. Theoretical calculations and in situ spectroscopy analyses demonstrate that the synergistic effect at the interface of indigo-derived compounds and Ag nanoparticles could activate CO2 molecules and accelerate the formation of key intermediates (*CO2– and *COOH) in the CO pathway. Indigo derivatives with electron-withdrawing groups further reduce the overpotential for CO production upon optimizing the interfacial CO2 binding affinity. By integrating the molecular design of redox-active centres with the defect engineering of Ag structures, we achieve a Faradaic efficiency for CO exceeding 90% across a current density range of 0.10 − 1.20 A cm–2. The Ag mass activity toward CO increases to 174 A mg–1Ag. This work showcases that employing redox-active CO2 sorbents as surface modification agents is a highly effective strategy to intensify the reactivity of electrochemical CO2 reduction. It is challenging to maintain the CO selectivity under high current densities in CO2 electro-reduction process. Here the authors report the synergistic interface between redox active CO2 organic sorbents and defective Ag catalysts that can enable an ampere level CO2-to-CO conversion.

ETHNOPHARMACOLOGICAL RELEVANCE Post-stroke depression (PSD) is common among stroke survivors and negatively impacts recovery. Chaihu-Shugan-San (CSS), a traditional Chinese medicine, has shown therapeutic potential for mood disorders, particularly PSD. Recent studies suggest that CSS's effects may be mediated by exosomes, but the mechanisms remain unclear. AIM OF STUDY This study aimed to evaluate the therapeutic effects of CSS on PSD in mice and investigate the underlying mechanisms, particularly the role of exosomes. MATERIALS AND METHODS Active compounds in CSS were identified from rat serum using liquid chromatography-mass spectrometry (LC-MS) and analyzed through network pharmacology. In vitro, an oxygen-glucose deprivation/reperfusion (OGD/R) BV2 microglia model was used to assess the effects of CSS-containing serum (CSS-S). Exosomes from OGD/R-treated BV2 microglia were isolated, labeled with PKH26, and analyzed using transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). In vivo, a photothrombotic stroke (PT) model combined with chronic unpredictable mild stress (CUMS) was used to induce PSD in mice. Behavioral assessments and histological analysis were performed, along with immunofluorescence (IF), ELISA and q-PCR to measure key protein and miR-146 expression in the hippocampus. RESULTS CSS treatment significantly alleviated depressive-like behaviors in the PSD mouse model. Mice treated with high-dose CSS (4.2 g/kg) exhibited increased sucrose preference, reduced immobility in the tail suspension test (TST) and forced swimming test (FST), and enhanced exploratory activity in the open field test (OFT). Histological analysis demonstrated that CSS treatment improved brain tissue integrity, alleviating neuronal damage and reducing neuroinflammation. Exosome analysis revealed that CSS increased the expression of microglia-derived exosomes in the hippocampus, which were shown to carry miR-146. Further examination of miR-146 isoforms in the hippocampal tissue revealed significant changes: miR-146b-3p and miR-146a-5p were upregulated, while miR-146a-3p and miR-146b-5p were downregulated in PSD mice. Treatment with CSS reversed the altered miRNA expression, indicating a potential mechanism for its neuroprotective effects. Additionally, CSS treatment reduced the expression of inflammatory cytokines such as S100A8, IL1β, IL6, and TNF-α, while restoring the levels of angiogenic factors VEGFC and VEGFR3. ELISA measurements showed significant decreases in cyclic AMP response element-binding protein (CREB), brain-derived neurotrophic factor (BDNF), 5-hydroxytryptamine (5-HT), dopamine (DA), and noradrenaline (NE) in PSD mice; high-dose CSS notably elevated CREB and BDNF levels and showed comparable effects to fluoxetine in restoring 5-HT and DA levels. Additionally, the calcium signaling pathway was implicated, with altered mRNA expressions of CaMKIIα, CREB, phosphorylated CREB (p-CREB), PDE4D, and BDNF, although fluoxetine demonstrated stronger modulatory effects than CSS. CONCLUSIONS CSS alleviates PSD in mice by modulating exosome-mediated signaling, particularly through the regulation of miR-146. The treatment reversed abnormal miRNA expression, reduced neuroinflammation, and improved synaptic function. These findings highlight CSS's potential as an effective therapeutic strategy for PSD by targeting exosome-mediated neuroprotection and miR-146 regulation.

OBJECTIVE: This study investigates the relationship between movement behaviors and physical fitness (PF) in university students, and based on the top 5% of model-predicted outcomes for PF to determine the optimal movement behaviors balance. METHODS: A total of 463 university students aged 15-24 years from Jinhua City wore accelerometers to measure moderate-to-vigorous physical activity (MVPA), light-intensity physical activity (LPA), and sedentary behavior (SB). Sleep (SLP) was self-reported. The body mass index (BMI), forced vital capacity (FVC), 50-meter dash, standing long jump, sit-and-reach, sit-ups (female), pull-ups (male), 800-meter run (female), and 1000-meter run (male) were used as indicators to assess the physical fitness of university students. Regression analysis was used to examine the relationship between movement behaviors and PF. All possible movement component combinations were investigated to determine the best correlation (top 5%) with each outcome. RESULTS: For males, SB (β = 5.05, p < 0.05) was significantly correlated with an increase in BMI. MVPA was significantly correlated with improvements in BMI (β = -1.75, p < 0.05), FVC (β = 494.21, p < 0.05), and endurance qualities (β = -25.77, p < 0.05). For females, MVPA was significantly correlated with improvements in BMI (β = -1.03, p < 0.05), FVC (β = 176.05, p < 0.05), speed capability (β = -0.26, p < 0.05), and endurance qualities (β = -16.38, p < 0.05). LPA was associated with improvements in endurance qualities (β = -24.10, p < 0.05). SB was significantly correlated with a decline in endurance qualities (β = 24.25, p < 0.05). The average (range) optimal combination of time use was as follows: For males, MVPA = 142 min/day, SB = 534 min/day, LPA = 295 min/day, and SLP = 469 min/day. For females, MVPA = 115 min/day, SB = 536 min/day, LPA = 306 min/day, and SLP = 482 min/day. CONCLUSION: For both males and females, increased MVPA and reduced sedentary time were associated with improved endurance and strength, while optimal sleep duration contributed to overall fitness. These findings highlight the importance of a balanced daily movement schedule for university students.

Colorectal cancer (CRC) is one of the leading causes of cancer-related mortality worldwide. In recent years, circular RNAs (circRNAs), a novel class of non-coding RNA molecules, have emerged as a research focus due to their unique stability and functional roles. CircRNAs regulate tumor-related signaling pathways through interactions with microRNAs (miRNAs) and proteins, playing key roles in tumorigenesis, progression, invasion, metastasis, and chemoresistance. This review summarizes the role of circRNAs in CRC, particularly their mechanisms in cell proliferation, migration, apoptosis, tumor microenvironment (TME) remodeling, and immune evasion. Aberrant expression of circRNAs holds great potential as diagnostic and prognostic biomarkers as well as therapeutic targets for CRC. Additionally, natural products such as flavonoids and glycosides, by modulating circRNA-miRNA-mRNA networks, offer promising therapeutic strategies. The article also discusses the current technical challenges in circRNA research and its future application prospects in CRC, highlighting the need for further investigation into the role of circRNAs in tumor immune microenvironments and drug resistance mechanisms.

Electrochemical CO 2 reduction to ethanol faces challenges such as low selectivity, a product mixture with liquid electrolyte, and poor catalyst/reactor stability. Here, we developed a grain-rich zinc-doped Cu 2 O precatalyst that presented a high ethanol Faradaic efficiency of over 40% under a current density of 350 mA·cm –2 . Our density functional theory (DFT) simulation suggested that Zn atoms inside the structure have a greater carbophilicity than the Cu atoms to help facilitate *CHCHO formation, a key reaction intermediate toward ethanol instead of other C 2 products. A high Faradaic efficiency ratio between ethanol and ethylene (FE EtOH /FE C2H4 ) reached 2.34 in the zinc-doped Cu 2 O precatalyst, representing an over 4-fold improvement compared to bare Cu 2 O precatalyst. By integrating this Cu-based catalyst into a porous solid electrolyte (PSE) reactor with a salt-managing design, we achieved stable ethanol production for over 180 h under a current density of 250 mA·cm –2 while maintaining ethanol selectivity at ∼30%.

Recent studies have revealed that photoreceptor-like cells derived from human induced pluripotent stem-cells (hiPSCs) were a potential approach for reversing lost vision. To make the hiPSC application in a clinical setting more accessible and efficient, we have developed a two-step method to differentiate an adequate number of chemically-induced photoreceptor-like cells (CiPCs) cells from hiPSCs in a shorter period (three weeks) through chemical reprogramming. The CiPCs were verified through cell morphology and flow cytometry methods for the expression of photoreceptor markers. The electrical signal detection of calcium, potassium, and sodium channels was performed with an <italic>in vitro</italic> model to determine the function of CiPCs. ERG recording was utilized for the <italic>in vivo</italic> evaluation. Photoreceptor markers, including recoverin and rhodopsin, were expressed in the CiPCs. Calcium, potassium, and sodium signals were detected in CiPCs. Clear ERG responses were observed in the retina of four out of six CiPCs transplanted mice (MNU-injured model), while none was observed in the control group. Moreover, classic symptoms of immune rejection were unobserved in the eyes of mice. Consequently, our hiPSC-derived photoreceptor-like cells successfully restored photosensitivity in photoreceptor-degenerated mice, indicating a potential clinical application for etiologically treating retinal degenerative diseases and restoring lost vision with less, or even no need for immunosuppressants.

Single metal atoms embedded in nitrogen-doped graphene (M-N-C) have emerged as a promising catalyst for a wide variety of reactions. In addition to the pyridinic site, there is another site responsible for the catalytic activity, but its structure is under debate. Here, we resolve its structure using first-principles calculations. Using Fe-N-C as a representative example, we systematically explore numerous possible structures and discover a new moiety with comparable energy to the pyridinic. This moiety features a hybrid coordination environment between pyridinic and porphyrinic and is located at the edge of graphene sheets or pores. We further calculate its X-ray absorption spectrum, catalytic thermodynamics for oxygen reduction reaction (ORR), and stability under ORR conditions, all of which support its existence. Lastly, we show that this site also exists in other M-N-C with different M elements. This study uncovers a new and important structure in M-N-C and paves a critical step toward site engineering for improved catalytic performance.

Electron-defect interaction is an important effect limiting the electronic properties of 2D transition metal dichalcogenides (TMD), especially to the low charge carrier mobility. We employ first-principles methods and develop scientific computation software "EDI" (Electron-Defect Interaction), which is used to accurately calculate the scatterings by some common defect types and study the mobility of various TMD systems. Our results indicate that traditional metric of effective mass is not enough to characterize the mobility. But the electron-defect coupling is the most important factor in the systems we research. In addition, we also identify good candidates with high mobility, and provide a potential annealing method to improve the electron transport in TMDs with common vacancy defects.

Electron-surface scattering is important for many transport phenomena and practical applications. Particularly, the downscaling of microelectronics demands higher electrical conductivity for interconnects, which are currently based on Cu, which suffers from strong surface scattering. However, much is still unclear, such as which surface orientation causes stronger scattering. Existing theories require phenomenological parameters whose values are unknown unless fitted to experimental data or based on assumptions, thereby limiting their accuracy and predictive power. Here we present an accurate, parameter-free approach that enables an accurate calculation of electronic transport with surface scattering. Then we apply it to study the conductivities of Cu films with different surface orientations. Contrary to the common belief that a more compact surface should have higher conductivity, we find that (111) is less conductive than (001). This can be explained by the symmetry of the electronic structure. Furthermore, we propose a phenomenological model that has a better fit to the first-principles results than the conventional one. Our work offers insights into electronic transport and enables accurate calculation, understanding, and prediction for a broad range of systems where surface scattering matters.

Electrocatalytic CO 2 reduction is garnering significant interest due to its potential applications in mitigating CO 2 and producing fuel. However, the scaling up of related catalysis is still hindered by several challenges, including the cost of the catalytic materials, low selectivity, small current densities to maintain desirable selectivity. In this study, Fluorine (F) atoms were introduced into an N-doped carbon-supported single nickel (Ni) atom catalyst via facile polymer-assisted pyrolysis. This method not only maintains the high atom utilization efficiency of Ni in a cost-effective and sustainable manner but also effectively manipulates the electronic structure of the active Ni–N 4 site through F doping. The catalyst has also been further optimized by controlling the F states, including convalent and semi-ionic states, by adjusting the fluorine sources involved. Consequently, this catalyst with unique structure exhibited comparable electrocatalytic performance for CO 2 -to-CO conversion, achieving a Faradaic efficiency (FE) of over 99% across a wide potential range and an exceptional CO evolution rate of 9.5 × 10 4 h –1 at −1.16 V vs reversible hydrogen electrode (RHE). It also delivered a practical current of 400 mA cm –2 while maintaining more than 95% CO FE. Experimental analysis combined with density functional theory (DFT) calculations have also shown that F-doping modifies the electron configuration at the central Ni–N 4 sites. This modification lowers the energy barrier for CO 2 activation, thereby facilitating the production of the crucial *COOH intermediate.

Given the growing emphasis on energy efficiency, environmental sustainability, and agricultural demand, there’s a pressing need for decentralized and scalable ammonia production. Converting nitrate ions electrochemically, which are commonly found in industrial wastewater and polluted groundwater, into ammonia offers a viable approach for both wastewater treatment and ammonia production yet limited by low producibility and scalability. Here we report a versatile and scalable solution-phase synthesis of high-entropy single-atom nanocages (HESA NCs) in which Fe and other five metals-Co, Cu, Zn, Cd, and In-are isolated via cyano-bridges and coordinated with C and N, respectively. Incorporating and isolating the five metals into the matrix of Fe resulted in Fe-C5 active sites with a minimized symmetry of lattice as well as facilitated water dissociation and thus hydrogenation process. As a result, the Fe-HESA NCs exhibited a high selectivity toward NH3 from the electrocatalytic reduction of nitrate with a Faradaic efficiency of 93.4% while maintaining a high yield rate of 81.4 mg h−1 mg−1. Converting nitrate from waste sources into ammonia provides an effective method for both wastewater treatment and ammonia production. Here the authors report a scalable solution-phase synthesis of high-entropy single-atom nanocage catalysts for efficient nitrate-to-ammonia conversion.

Abstract A comprehensive understanding of atomic fracture mechanisms in 2D materials is essential for their practical applications, yet this knowledge is currently limited. To address this gap, an aberration‐corrected scanning transmission electron microscope (STEM) to induce new cracks in suspended monolayer transition metal dichalcogenides (TMDs) using broad electron beam illumination, is employed. During characterization, a low‐dose electron beam to avoid irradiation damage, allowing to observe the atomic fracture behavior in these materials, is utilized. The STEM experiments reveal a novel atomic fracture pattern along the zigzag direction, resulting in a distribution where half of the chalcogen atoms (S or Se) adhered to the molybdenum‐terminated (Mo‐T) edge and the other half to the chalcogen‐terminated (S‐T or Se‐T) edge. Density functional theory (DFT) calculations suggest that this fracture mode produces a pair of edges with the lowest formation energy. Additionally, molecular dynamics (MD) simulations support the observed fracture behavior under a mixed mechanical loading mode of “I+III” with both in‐plane and out‐of‐plane stress, originating from the ultrathin nature and nonplanar deformation in suspended 2D materials. This research offers new insights for the development of 2D fracture mechanics and is pivotal for designing devices incorporating 2D materials.

Abstract There is great interest in developing advanced electrical conductors with higher conductivity, lighter weight, and higher mechanical strength than copper (Cu). One promising candidate is copper‐graphene (Cu‐Gr) composite, which is hypothesized to have a higher electrical conductivity than Cu. In this work, it is shown that this is not true, supported by state‐of‐the‐art first‐principles calculations of electron transport. Particularly, contrary to the belief that graphene in the composite is more conductive than pristine Cu, it is less conductive due to increased scattering despite increased carrier concentration. On the other hand, it is found that compressive strain along the (111) plane increases the conductivity, which is confirmed experimentally, while tensile strain has little effect. The work offers new insights into understanding and developing advanced conductors.

Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Here, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.

Remote phonons from dielectrics are typically believed to degrade carrier mobility in adjacent semiconductors through Fröhlich scattering of polar-optical phonons (POPs). Here, we challenge this conventional view by demonstrating that in van der Waals (vdW) heterostructures, remote POPs can instead enhance the mobility. To this end, we developed a first-principles computational framework to evaluate these remote phonon effects. Applying our approach to an example of monolayer InSe semiconductor encapsulated by h-BN dielectric layers, we show that electron mobility is enhanced due to coupling between POPs in InSe and h-BN, which gives rise to a new collective phonon mode where their individual Fröhlich potentials partially cancel each other. Based on this insight, we further identified additional dielectrics that display similar mobility enhancement, demonstrating universality of mobility enhancement due to remote phonons. This work offers not only an effective computational method to evaluate the remote phonon effects but also new insights into mobility engineering in next-generation electronics.

Two-dimensional (2D) crystalline semiconductors hold promise for next-generation electronic devices due to its atomical thickness and consequent properties. Despite years of search, literature-reported 2D semiconductors commonly suffered from low room-temperature charge mobility (&lt; 200 cm2V-1s-1), due to the dimensionality-increased 'density of scattering', undesirable defects during fabrication and/or strong electron-phonon scattering. Therefore, understanding charge scatterings in 2D semiconductors via computational tools and discovering new 2D semiconductors with high mobility (&gt; 1000 cm2V-1s-1) are both desirable. Here we review the accurate ab initio approaches for electron-phonon/defect/boundary scattering developed these years, and the efforts made in high-mobility 2D semiconductor high throughput screening. Starting from these studies, the common genome of high-mobility 2D semiconductor are summarized and discussed, which would contribute to further discovering of high mobility in 2D semiconductors.

2D transition metal dichalcogenide (MX 2 ) semiconductors are promising candidates for electronic and optoelectronic applications. However, they have relatively low charge carrier mobility at room temperature. Defects are important scattering sources, while their quantitative roles remain unclear. Here we employ first-principles methods to accurately calculate the scatterings by different types of defects (chalcogen vacancies, antisites, and oxygen substitutes) and the resulting carrier mobilities for various MX 2 (M = Mo/W and X = S/Se). We find that for the same X, WX 2 always has a higher mobility than MoX 2, regardless of defect type and carrier type. Further analyses attribute this to the universally weaker electron-defect coupling in WX 2 . Moreover, we find filling the chalcogen vacancy with O always improves the mobility, while filling by a metal atom decreases the mobility except for WSe2. Finally, we identify the critical defect concentrations where the defect- and phonon-limited mobilities cross, providing guidelines for experimental optimization.

Abstract Efficient CO 2 separation technologies are essential for mitigating climate change. Compared to traditional thermochemical methods, electrochemically mediated carbon capture using redox-tunable sorbents emerges as a promising alternative due to its versatility and energy efficiency. However, the undesirable linear free-energy relationship between redox potential and CO 2 binding affinity in existing chemistry makes it fundamentally challenging to optimise key sorbent properties independently via chemical modifications. Here, we demonstrate a design paradigm for electrochemically mediated carbon capture sorbents, which breaks the undesirable scaling relationship by leveraging intramolecular hydrogen bonding in isoindigo derivatives. The redox potentials of isoindigos can be anodically shifted by &gt;350 mV to impart sorbents with high oxygen stability without compromising CO 2 binding, culminating in a system with minimised parasitic reactions. With the synthetic space presented, our effort provides a generalisable strategy to finetune interactions between redox-active organic molecules and CO 2 , addressing a longstanding challenge in developing effective carbon capture methods driven by non-conventional stimuli.

Electroreduction of CO 2 into liquid fuels is a compelling strategy for storing intermittent renewable energy. Here, we introduce a family of facet-defined dilute copper alloy nanocrystals as catalysts to improve the electrosynthesis of n -propanol from CO 2 and H 2 O. We show that substituting a dilute amount of weak-CO-binding metals into the Cu(100) surface improves CO 2 -to- n -propanol activity and selectivity by modifying the electronic structure of catalysts to facilitate C 1 –C 2 coupling while preserving the (100)-like 4-fold Cu ensembles which favor C 1 –C 1 coupling. With the Au 0.02 Cu 0.98 champion catalyst, we achieve an n -propanol Faradaic efficiency of 18.2 ± 0.3% at a low potential of −0.41 V versus the reversible hydrogen electrode and a peak production rate of 16.6 mA·cm –2 . This study demonstrates that shape-controlled dilute-metal-alloy nanocrystals represent a new frontier in electrocatalyst design, and precise control of the host and minority metal distributions is crucial for elucidating structure–composition–property relationships and attaining superior catalytic performance.

Heterogeneous electrochemistry is important for various applications. However, currently, there is limited information about activation energies. In this invited review, we review the challenges associated with calculating these activation energies. Specifically, we highlight three key difficulties in atomistic modeling: liquid structure, electrode potential, and electrolyte ions, along with state-of-the-art methods to address them. We aim to inspire more studies in the field of activation energies to better understand and design heterogeneous electrocatalysts.

Two-dimensional materials, such as transition metal dichalcogenides (TMDCs), have the potential to revolutionize the field of electronics and photonics due to their unique physical and structural properties. This research presents a novel method for synthesizing crystalline TMDCs crystals with <10 nm size using ultrafast migration of vacancies at elevated temperatures. Through in situ and ex situ processing and using atomic-level characterization techniques, we analyzed the shape, size, crystallinity, composition, and strain distribution of these nanocrystals. These nanocrystals exhibit electronic structure signatures that differ from the 2D bulk: i.e., uniform mono- and multilayers. Further, our in situ, vacuum-based synthesis technique allows observation and comparison of defect and phase evolution in these crystals formed under van der Waals heterostructure confinement versus unconfined conditions. Overall, this research demonstrates a solid-state route to synthesizing uniform nanocrystals of TMDCs and lays the foundation for materials science in confined 2D spaces under extreme conditions.

Extracting the sea area of Marine floating raft culture is contributed to the rational use of aquaculture resources. The availability of remote sensing technology can dynamically detect aquaculture rafts. As a classical semantic segmentation model, U - net can also be beneficial to extract the synthetic aperture radar images of marine cultivation. However, the parameters of U - net are customarily set by experts based on experience and cannot be changed dynamically. In this paper, a method for flexibly designing U - net model parameters by particle swarm optimization is presented. Treat individuals with diverse parameters as a swarm and randomly initialize the encoded information, allowing each individual to apply appraisal indi-cators for fitness evaluation. Implementing particle updates and iteratively improving model parameters in interactive learning between individuals and populations. The experimental results demonstrate that the model can obtain competitive outcomes on multiple evaluation indicators after parameter optimization.

Oxygen reduction reaction (ORR) is essential to various renewable energy technologies. An important catalyst for ORR is single iron atoms embedded in nitrogen-doped graphene (Fe–N–C). However, the rate-limiting step of the ORR on Fe–N–C is unknown, significantly impeding understanding and improvement. Here, we report the activation energies of all of the steps, calculated by ab initio molecular dynamics simulations under constant electrode potential. In contrast to the common belief that a hydrogenation step limits the reaction rate, we find that the rate-limiting step is oxygen molecule replacing adsorbed water on Fe. This occurs through concerted motion of H 2 O desorption and O 2 adsorption, without leaving the site bare. Interestingly, despite being an apparent “thermal” process that is often considered to be potential-independent, the barrier reduces with the electrode potential. This can be explained by stronger Fe–O 2 binding and weaker Fe–H 2 O binding at a lower potential, due to O 2 gaining electrons and H 2 O donating electrons to the catalyst. Our study offers new insights into the ORR on Fe–N–C and highlights the importance of kinetic studies in heterogeneous electrochemistry.

Alzheimer's Disease (AD) is a global public health priority characterized by high mortality rates in adults and an increasing prevalence in aging populations worldwide. Despite significant advancements in comprehending the pathogenesis of AD since its initial report in 1907, there remains a lack of effective curative or preventive measures for the disease. In recent years, natural compounds sourced from diverse origins have garnered considerable attention as potential therapeutic agents for AD, owing to their anti-inflammatory, antioxidant, and neuroprotective properties. This review aims to consolidate the therapeutic effects of natural compounds on AD, specifically targeting the reduction of β-amyloid (Aβ) overproduction, anti-apoptosis, autophagy, neuroinflammation, oxidative stress, endoplasmic reticulum (ER) stress, and mitochondrial dysfunction. Notably, the identified compounds exhibiting these effects predominantly originate from plants. This review provides valuable insights into the potential of natural compounds as a reservoir of novel therapeutic agents for AD, thereby stimulating further research and contributing to the development of efficacious treatments for this devastating disease.

Abstract Ethylene glycol is a widely utilized commodity chemical, the production of which accounts for over 46 million tons of CO 2 emission annually. Here we report a paired electrocatalytic approach for ethylene glycol production from methanol. Carbon catalysts are effective in reducing formaldehyde into ethylene glycol with a 92% Faradaic efficiency, whereas Pt catalysts at the anode enable formaldehyde production through methanol partial oxidation with a 75% Faradaic efficiency. With a membrane-electrode assembly configuration, we show the feasibility of ethylene glycol electrosynthesis from methanol in a single electrolyzer. The electrolyzer operates a full cell voltage of 3.2 V at a current density of 100 mA cm −2 , with a 60% reduction in energy consumption. Further investigations, using operando flow electrolyzer mass spectroscopy, isotopic labeling, and density functional theory (DFT) calculations, indicate that the desorption of a *CH 2 OH intermediate is the crucial step in determining the selectively towards ethylene glycol over methanol.

Two-dimensional materials, such as transition metal dichalcogenides (TMDCs), have the potential to revolutionize the field of electronics and photonics due to their unique physical and structural properties. This research presents a novel method for synthesizing crystalline TMDCs crystals with &lt; 10 nm size using ultra-fast migration of vacancies at elevated temperatures. Through in-situ and ex-situ processing and using atomic-level characterization techniques, we analyze the shape, size, crystallinity, composition, and strain distribution of these nanocrystals. These nanocrystals exhibit electronic structure signatures that differ from the 2D bulk i.e., uniform mono and multilayers. Further, our in-situ, vacuum-based synthesis technique allows observation and comparison of defect and phase evolution in these crystals formed under van der Waals heterostructure confinement versus unconfined conditions. Overall, this research demonstrates a solid-state route to synthesizing uniform nanocrystals of TMDCs and lays the foundation for materials science in confined 2D spaces under extreme conditions.

CO 2 reduction (CO 2 R) catalyzed by an efficient, stable, and earth-abundant electrocatalyst offers an attractive means to store energy derived from renewable sources. Here, we describe the synthesis of facet-defined Cu 2 SnS 3 nanoplates and the ligand-controlled CO 2 R property. We show that thiocyanate-capped Cu 2 SnS 3 nanoplates possess excellent selectivity toward formate over a wide range of potentials and current densities, attaining a maximum formate Faradaic efficiency of 92% and partial current densities as high as 181 mA cm –2 when tested using a flow cell with gas-diffusion electrode. In situ spectroscopic measurements and theoretical calculations reveal that the high formate selectivity originates from favorable adsorption of HCOO* intermediates on cationic Sn sites that are electronically modulated by thiocyanates bound to adjacent Cu sites. Our work illustrates that well-defined multimetallic sulfide nanocrystals with tailored surface chemistries could provide a new avenue for future CO 2 R electrocatalyst design.

Two-dimensional semiconductors have demonstrated great potential for next-generation electronics and optoelectronics, however, the current 2D semiconductors suffer from intrinsically low carrier mobility at room temperature, which significantly limits their applications. Here we discover a variety of new 2D semiconductors with mobility 1 order of magnitude higher than the current ones and even higher than bulk silicon. The discovery was made by developing effective descriptors for computational screening of the 2D materials database, followed by high-throughput accurate calculation of the mobility using a state-of-the-art first-principles method that includes quadrupole scattering. The exceptional mobilities are explained by several basic physical features; particularly, we find a new feature: carrier-lattice distance, which is easy to calculate and correlates well with mobility. Our Letter opens up new materials for high performance device performance and/or exotic physics, and improves the understanding of the carrier transport mechanism.

Post-stroke depression (PSD) is one of the most common neuropsychiatric consequence of stroke, affecting cognitive function, recovery of somatic function, and patient survival. The aim of this study was to evaluate whether Chaihu-Shugan-San, a traditional Chinese medicine formula used clinically to treat depression, could improve symptoms in a rat model for PSD, to investigate the potential mechanisms, and to validate the findings in an in vitro oxygen and glucose deprivation (OGD) model. Male rats were subjected to middle cerebral artery occlusion (MCAO) and to chronic unpredictable mild stress (CUMS). The rats were then allocated to experimental groups (n = 15) that were treated with Chaihu-Shugan-San, a JAK-STAT3 inhibitor, a GSK3β overexpressing virus, or an empty virus (control). The subjects allocated to each group, as well as those that received no treatment and rats that did not undergo MCAO/CUMS, were then subjected to forced swimming, tail suspension, and sugar water preference tests, and their neurological deficit score was determined. Inflammatory factor levels and the expression of proteins related to the JAK/STAT3-GSK3β/PTEN/Akt pathway were measured, and the synaptic ultrastructure was observed using transmission electron microscopy. Flow cytometry showed microglia polarization towards the M1 phenotype in an in vitro PSD model, which was reversed after treatment with a GSK3β overexpression virus, Chaihu-Shugan-San, or a JAK-STAT3 inhibitor. The results showed that Chaihu-Shugan-San has a therapeutic effect on an in vivo model for PSD and can regulate microglia polarization through the activation of the JAK/STAT3-GSK3β/PTEN/Akt pathway, suggesting that it exerts its effect via the inhibition of neuroinflammation.