Long-term effects of particulate matter on incident cardiovascular diseases in middle-aged and elder adults: The CHARLS cohort study.

BACKGROUND: Although there is evidence of long-term effects of particulate matter (PM) on cardiovascular diseases (CVD), researches about long-term effects of PM1 on CVD are limited. We aimed to examine the long-term effects and magnitude of PM, especially PM1, on incident CVD in China. METHODS: We included 6016 participants aged ≥ 45 years without CVD at baseline in 2011 from the China Health and Retirement Longitudinal Study. Personal PM (PM1, PM2.5, and PM10) concentrations were estimated using geocoded residential address. Generalized linear mixed models and SHapley Additive exPlanation were utilized to calculate the impacts and contributions of PM on CVD. Sensitivity analyses were used to check the robustness. RESULTS: After a follow up of 4-year, 481 (7.99 %) participants developed CVD. Per 10 µg/m3 uptick in 1-year average concentrations of PM1, PM2.5 and PM10 was associated with a 1.20 [95 % confidence interval (CI): 1.05-1.37], 1.13 (95 % CI: 1.11-1.15), and 1.10 (95 % CI: 1.06-1.13) fold risk of incident CVD, respectively. The 2-year average concentrations of PM1, PM2.5 and PM10 were associated with incident CVD, corresponding to a 1.03 (95 % CI: 0.96-1.10), 1.11 (95 % CI: 1.02-1.21), and 1.09 (95 % CI: 1.03-1.15) fold risk, respectively. The SHapley Additive exPlanation values of PM1, PM2.5, and PM10 were 0.170, 0.153, and 0.053, respectively, corresponding to the first, second, and fifth among all air pollutants. Effects of PM1, PM2.5 and PM10 on CVD remained statistically significant in two-pollutant models. The elderly, males, smokers and alcohol drinkers tended to have slightly higher effects, while the differences were not statistically significant (all P-values > 0.05) between subgroups. CONCLUSION: Long-term exposure to PM1, PM2.5, and PM10 was associated with an increased incidence of CVD. The smaller the particle size, the more important it was for incident CVD indicating that emphasis should be placed on small size of PM.

A Universal Descriptor for Complicated Interfacial Effects on Electrochemical Reduction Reactions.

Supported catalysts have exhibited excellent performance in various reactions. However, the rational design of supported catalysts with high activity and certain selectivity remains a great challenge because of the complicated interfacial effects. Using recently emerged two-dimensional materials supported dual-atom catalysts (DACs@2D) as a prototype, we propose a simple and universal descriptor based on inherent atomic properties (electronegativity, electron type, and number), which can well evaluate the complicated interfacial effects on the electrochemical reduction reactions (i.e., CO2, O2, and N2 reduction reactions). Based on this descriptor, activity and selectivity trends in CO2 reduction reaction are successfully elucidated, in good agreement with available experimental data. Moreover, several potential catalysts with superior activity and selectivity for target products are predicted, such as CuCr/g-C3N4 for CH4 and CuSn/N-BN for HCOOH. More importantly, this descriptor can also be extended to evaluate the activity of DACs@2D for O2 and N2 reduction reactions, with very small errors between the prediction and reported experimental/computational results. This work provides feasible principles for the rational design of advanced electrocatalysts and the construction of universal descriptors based on inherent atomic properties.

Unveiling chemical reactivity and oxidation of 1T-phased group VI disulfides.

Transition metal dichalcogenides (TMDs) are of particular interest because of their unique electrical and optical properties that evolve from the quantum confinement and surface effects. However, their long-term stability in air is proved to be a main concern for practical applications of the ultrathin materials, especially for TMDs with 1T phased structures. Here, we provide an in-depth understanding of the oxidation and degradation mechanisms of monolayers of group VIB disulfides, including TiS2, ZrS2, and HfS2. As the atomic radius of the transitional metals increases, their air stability significantly decreases and the oxidation mechanisms are quite different from one another. In particular, the oxygen induced oxidations initiated at both the surface vacancy sites and edges of ZrS2 and HfS2 are studied, while the oxidation of TiS2 starts at the edges and water plays a crucial role in the continuous oxidation process. Moreover, the defective sites expose the metals for activation and dissociation of either oxygen or water, causing the breakdown of the systems eventually. Meanwhile, these sites can be used as active centers for specific applications in catalysts and surface functionalized materials.

Nanosheet Supported Single-Metal Atom Bifunctional Catalyst for Overall Water Splitting.

Nanosheet supported single-atom catalysts (SACs) can make full use of metal atoms and yet entail high selectivity and activity, and bifunctional catalysts can enable higher performance while lowering the cost than two separate unifunctional catalysts. Supported single-atom bifunctional catalysts are therefore of great economic interest and scientific importance. Here, on the basis of first-principles computations, we report a design of the first single-atom bifunctional eletrocatalyst, namely, isolated nickel atom supported on ß12 boron monolayer (Ni1/ß12-BM), to achieve overall water splitting. This nanosheet supported SAC exhibits remarkable electrocatalytic performance with the computed overpotential for oxygen/hydrogen evolution reaction being just 0.40/0.06 V. The ab initio molecular dynamics simulation shows that the SAC can survive up to 800 K elevated temperature, while enacting a high energy barrier of 1.68 eV to prevent isolated Ni atoms from clustering. A viable experimental route for the synthesis of Ni1/ß12-BM SAC is demonstrated from computer simulation. The desired nanosheet supported single-atom bifunctional catalysts not only show great potential for achieving overall water splitting but also offer cost-effective opportunities for advancing clean energy technology.

Mechanism of surface oxygen-containing species promoted electrocatalytic CO2 reduction.

Oxygen-containing species have been demonstrated to play a key role in facilitating electrocatalytic CO2 reduction (CO2RR), particularly in enhancing the selectivity towards multi-carbon (C2+) products. However, the underlying promotion mechanism is still under debate, which greatly limits the rational optimization of the catalytic performance of CO2RR. Herein, taking CO2 and O2 co-electrolysis over Cu as the prototype, we successfully clarified how O2 boosts CO2RR from a new perspective by employing comprehensive theoretical simulations. Our results demonstrated that O2 in feed gas can be rapidly reduced into *OH, leading to the partial oxidation of Cu surface under reduction conditions. Surface *OH accelerates the formation of quasi-specifically adsorbed K+ due to the electrostatic interaction between *OH and K+ ions, which significantly increases the concentration of K+ near the Cu surface. These quasi-specifically adsorbed K+ ions can not only lower the C-C coupling barriers but also promote the hydrogenation of CO2 to improve the CO yield rate, which are responsible for the remarkably enhanced efficiency of C2+ products. During the whole process, O2 co-electrolysis plays an indispensable role in stabilizing surface *OH. This mechanism can be also adopted to understand the effect of high pH of electrolyte and residual O in oxide-derived Cu (OD-Cu) on the catalytic efficiency towards C2+ products. Therefore, our work provides new insights into strategies for improving C2+ products on the Cu-based catalysts, i.e., maintaining partial oxidation of surface under reduction conditions.

Machine Learning Assisted Simulations of Electrochemical Interfaces: Recent Progress and Challenges.

The electrochemical interface, where the adsorption of reactants and electrocatalytic reactions take place, has long been a focus of attention. Some of the important processes on it tend to possess relatively slow kinetic characteristics, which are usually beyond the scope of ab initio molecular dynamics. The newly emerging technique, machine learning methods, provides an alternative approach to achieve thousands of atoms and nanosecond time scale while ensuring precision and efficiency. In this Perspective, we summarize in detail the recent progress and achievements made by the introduction of machine learning to simulate electrochemical interfaces, and focus on the limitations of current machine learning models, such as accurate descriptions of long-range electrostatic interactions and the kinetics of the electrochemical reactions occurring at the interface. Finally, we further point out the future directions for machine learning to expand in the field of electrochemical interfaces.

Identification of key degraders for controlling toxicity risks of disguised toxic pollutants with division of labor mechanisms in activated sludge microbiomes: Using nonylphenol ethoxylate as an example.

Efficient management of disguised toxic pollutants (DTPs), which can undergo microbial degradation and convert into more toxic substances, necessitates the collaboration of diverse microbial populations in wastewater treatment plants. However, the identification of key bacterial degraders capable of controlling the toxicity risks of DTPs through division of labor mechanisms in activated sludge microbiomes has received limited attention. In this study, we investigated the key degraders capable of controlling the risk of estrogenicity associated with nonylphenol ethoxylate (NPEO), a representative DTP, in textile activated sludge microbiomes. The results of our batch experiments revealed that the transformation of NPEO into NP and subsequent NP degradation were the rate-limiting processes for controlling the risk of estrogenicity, resulting in an inverted V-shaped curve of estrogenicity in water samples during the biodegradation of NPEO by textile activated sludge. By utilizing enrichment sludge microbiomes treated with NPEO or NP as the sole carbon and energy source, a total of 15 bacterial degraders, including Sphingbium, Pseudomonas, Dokdonella, Comamonas, and Hyphomicrobium, were identified as capable of participating in these processes, Among them, Sphingobium and Pseudomonas were the two key degraders that could cooperatively interact in the degradation of NPEO with division of labor mechanisms. Co-culturing Sphingobium and Pseudomonas isolates exhibited a synergistic effect in degrading NPEO and reducing estrogenicity. Our study underscores the potential of the identified functional bacteria for controlling estrogenicity associated with NPEO and provides a methodological framework for identifying key cooperators engaged in labor division, contributing to the management of risks associated with DTPs by leveraging intrinsic microbial metabolic interactions.

In-situ constructed Cu/CuNC interfaces for low-overpotential reduction of CO2 to ethanol.

Electrochemical CO2 reduction (ECR) to high-value multi-carbon (C2+) products is critical to sustainable energy conversion, yet the high energy barrier of C-C coupling causes catalysts to suffer high overpotential and low selectivity toward specific liquid C2+ products. Here, the electronically asymmetric Cu-Cu/Cu-N-C (Cu/CuNC) interface site is found, by theoretical calculations, to enhance the adsorption of *CO intermediates and decrease the reaction barrier of C-C coupling in ECR, enabling efficient C-C coupling at low overpotential. The catalyst consisting of high-density Cu/CuNC interface sites (noted as ER-Cu/CuNC) is then accordingly designed and constructed in situ on the high-loading Cu-N-C single atomic catalysts. Systematical experiments corroborate the theoretical prediction that the ER-Cu/CuNC boosts electrocatalytic CO2-to-ethanol conversion with a Faradaic efficiency toward C2+ of 60.3% (FEethanol of 55%) at a low overpotential of -0.35 V. These findings provide new insights and an attractive approach to creating electronically asymmetric dual sites for efficient conversion of CO2 to C2+ products.

Toward Low-Symmetry Systems: An Adaptive Differential Evolution Algorithm for Global Structure Searching.

The reduction in the symmetry of nanomaterials can produce unexpected properties, while the determination of atomic structures is a sizable challenge in related fields, including low-dimensional materials, surface science, defects, etc. Herein, we develop an adaptive algorithm based on the differential evolution algorithm, which provides benefits for structure searching on low-symmetry systems. The dynamic strategy pool and the island concept are proposed to accelerate the efficiency in the full search space. With several test examples, the designed program not only locates reported structures but also affords new stable configurations that were not located by previous structure search algorithms. Moreover, we provide frameworks and interfaces for stable structure searching on complex systems like grain boundaries, supported clusters, surfaces, and edges. The success in repeatable structure searching with high efficiency demonstrates the reliability and practicability of our algorithm and ensures its potential applications as an advanced technology in many newly arising fields.

Selective visible-light driven highly efficient photocatalytic reduction of CO2 to C2H5OH by two-dimensional Cu2S monolayers.

Solar-driven highly-efficient photocatalytic reduction of CO2 into value-added fuels has been regarded as a promising strategy to assuage the current global warming and energy crisis, but developing highly product-selective, long-term stable and low-cost photocatalysts for C2 production remains a grand challenge. Herein, we demonstrate that two-dimensional ß- and δ-phase Cu2S monolayers are promising photocatalysts for the reduction of CO2 into C2H5OH. The calculated potential-limiting steps for the CO2 reduction reaction (CO2RR) are less than 0.50 eV, while those for the hydrogen evolution reaction are as high as 1.53 and 0.87 eV. Most strikingly, the C-C coupling only needs to overcome an ultra-low kinetic barrier of ∼0.30 eV, half of that on the Cu surface, indicating that they can boost the C2H5OH conversion efficiency greatly. Besides, these catalysts also exhibit satisfactory band edge positions and suitable visible light absorption, rendering them ideal for the visible light driven CO2RR. Our work not only provides a promising photocatalyst for achieving the efficient and selective CO2RR, but also brings new opportunities for advanced sustainable C2H5OH product.

Induced Autophagy of Macrophages and the Regulation of Inflammatory Effects by Perovskite Nanomaterial LaNiO3.

Perovskite nanomaterials (NMs) possess excellent physicochemical properties and have promising applications in light-emitting diodes (LEDs), lasers, photodetectors, and artificial synapse electronics. Potential exposure to these NMs happens in the manufacture and application of the perovskite-based products, however, the biological safety of these NMs is still unknown. Here, we used the LaNiO3 NM (LNO), a typical kind of perovskite nanostructures to study the interaction with macrophages (J774A.1) and to explore its biological effects at the cellular level. Firstly, we characterized the properties of LNO including the size, shape, and crystal structure using Transmission electronic microscope (TEM), Dynamic lighting scattering (DLS), and X-ray diffraction (XRD). Secondly, to gain a better understanding of the biological effect, we evaluated the effect of LNO on cell viability and found that LNO induced cell autophagy at a concentration of 5 µg/ml and influenced the inflammatory response based on RT-PCR result. Finally, we demonstrated the mechanism that LNO causes cell autophagy and immune response is probably due to the metal ions released from LNO in acidic lysosomes, which triggered ROS and increased lysosomal membrane permeation. This study indicates the safety aspect of perovskite NMs and may guide the rational design of perovskite NMs with more biocompatibility during their manufacture and application.

Breaking scaling relations for efficient CO2 electrochemical reduction through dual-atom catalysts.

The electrochemical reduction of CO2 offers an elegant solution to the current energy crisis and carbon emission issues, but the catalytic efficiency for CO2 reduction is seriously restricted by the inherent scaling relations between the adsorption energies of intermediates. Herein, by combining the concept of single-atom catalysts and multiple active sites, we design heteronuclear dual-atom catalysts to break through the stubborn restriction of scaling relations on catalytic activity. Twenty-one kinds of heteronuclear transition-metal dimers are embedded in monolayer C2N as potential dual-atom catalysts. First-principles calculations reveal that by adjusting the components of dimers, the two metal atoms play the role of carbon adsorption sites and oxygen adsorption sites respectively, which results in the decoupling of adsorption energies of key intermediates. Free energy profiles demonstrate that CO2 can be efficiently reduced to CH4 on CuCr/C2N and CuMn/C2N with low limiting potentials of -0.37 V and -0.32 V, respectively. This study suggests that the introduction of multiple active sites into porous two-dimensional materials would provide a great possibility for breaking scaling relations to achieve efficient multi-intermediate electrocatalytic reactions.

Perspective on theoretical methods and modeling relating to electro-catalysis processes.

Electro-catalysis is expected to be a promising clean alternative for energy conversion, and the search for effective and stable electro-catalysts is fundamental. Theoretical calculations play an important role in the rational design and optimization of the performance of electro-catalysts by revealing active sites for reactions and corresponding reaction mechanisms. However, the simulation of electrochemical processes under realistic conditions, for instance, electrode-electrolyte interface structures and the dynamic movement of species around the interface, is still limited. In this review, we summarize advances in theoretical methods and models for the description of thermodynamics and kinetics in electro-catalysis, including solvent effects, externally applied potentials, and many-body interactions. Multiple innovative methods and models are covered with specific examples, and the scope for future development is discussed.

Effect of illumination and Se vacancies on fast oxidation of ultrathin gallium selenide.

Gallium selenide (GaSe) has recently emerged as a unique platform due to its exciting properties, namely, large and fast photo-response, high carrier mobility and non-linear optical properties. However, exposure for a few days causes the fast oxidation of ultrathin GaSe under ambient conditions and the oxidation mechanism remains unclear. By means of density functional theory calculations and ab initio molecular dynamics simulations, we comprehensively investigated the possible sources that cause oxidation of ultrathin GaSe. Our results show that illumination and Se vacancies induce the fast oxidation of GaSe. Under illumination, photo-excited electrons from the surface of GaSe are effectively transferred to oxygen molecules and thus, superoxide anions (O2-) are generated that react with GaSe. Moreover, Se vacancies directly react with O2. In both the cases, the Ga-Se bonds are continually replaced by Ga-O bonds, which eventually leads to complete degradation of GaSe, accompanied with the formation of the oxidation products Ga2O3 and elemental Se. The comprehensive degradation mechanism unveiled herein lays an important foundation for the development of suitable protecting strategies in GaSe-based devices.

Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning.

Rapidly discovering functional materials remains an open challenge because the traditional trial-and-error methods are usually inefficient especially when thousands of candidates are treated. Here, we develop a target-driven method to predict undiscovered hybrid organic-inorganic perovskites (HOIPs) for photovoltaics. This strategy, combining machine learning techniques and density functional theory calculations, aims to quickly screen the HOIPs based on bandgap and solve the problems of toxicity and poor environmental stability in HOIPs. Successfully, six orthorhombic lead-free HOIPs with proper bandgap for solar cells and room temperature thermal stability are screened out from 5158 unexplored HOIPs and two of them stand out with direct bandgaps in the visible region and excellent environmental stability. Essentially, a close structure-property relationship mapping the HOIPs bandgap is established. Our method can achieve high accuracy in a flash and be applicable to a broad class of functional material design.

Ultrathin Semiconducting Bi2Te2S and Bi2Te2Se with High Electron Mobilities.

High carrier mobility and moderate band gap are two key properties of electronic device applications. Two ultrathin two-dimensional (2D) semiconductors, namely, Bi2Te2S and Bi2Te2Se nanosheets, with novel electronic and optical properties are predicted based on first-principles calculations. The Bi2Te2S and Bi2Te2Se monolayers own moderate band gaps (∼0.7 eV) and high electron mobilities (∼20 000 cm2 V-1 s-1), and they can absorb sunlight efficiently through the whole incident solar spectrum. Meanwhile, layer-dependent exponential decay band gaps are also unveiled. The relatively low interlayer binding energies suggest that these monolayers can be easily exfoliated from bulk structures. Their high dynamical and thermal stabilities are further verified by phonon dispersion calculations and ab initio molecular dynamics simulations. The exceptional properties render Bi2Te2X (X = S, Se) monolayers promising candidates in future high-speed (opto)electronic devices.

Insight into the catalytic activity of MXenes for hydrogen evolution reaction.

MXenes have exhibited great potential as cost-effective electrocatalysts for hydrogen evolution reaction (HER). However, insight into the origin of activity is still missing. Herein, on the basis of a systematical investigation of the HER performance of 20 MXenes (M2NO2 and M2CO2, M = Sc, Ti, V, Cr, Zr, Nb, Mo, Hf, Ta and W), a Fermi-abundance model is proposed to understand variation of the activity in different MXenes. It is found that the occupied p electronic states of surface O atoms play a decisive role in the HER activity of MXenes. More importantly, Ti2NO2 and Nb2NO2 are found to be promising HER electrocatalysts with the free energy for hydrogen adsorption close to zero. This work not only provides possible catalysts for HER, the developed Fermi-abundance model but also is applicable to other two-dimensional materials and may serve as a simple descriptor of the intrinsic HER activity.

Chemically activating MoS2 via spontaneous atomic palladium interfacial doping towards efficient hydrogen evolution.

Lacking strategies to simultaneously address the intrinsic activity, site density, electrical transport, and stability problems of chalcogels is restricting their application in catalytic hydrogen production. Herein, we resolve these challenges concurrently through chemically activating the molybdenum disulfide (MoS2) surface basal plane by doping with a low content of atomic palladium using a spontaneous interfacial redox technique. Palladium substitution occurs at the molybdenum site, simultaneously introducing sulfur vacancy and converting the 2H into the stabilized 1T structure. Theoretical calculations demonstrate the sulfur atoms next to the palladium sites exhibit low hydrogen adsorption energy at -0.02 eV. The final MoS2 doped with only 1wt% of palladium demonstrates exchange current density of 805 µA cm-2 and 78 mV overpotential at 10 mA cm-2, accompanied by a good stability. The combined advantages of our surface activating technique open the possibility of manipulating the catalytic performance of MoS2 to rival platinum.

High intrinsic catalytic activity of two-dimensional boron monolayers for the hydrogen evolution reaction.

Two-dimensional (2D) boron monolayers have been successfully synthesized on a silver substrate very recently. Their potential application is thus of great significance. In this work, we explore the possibility of boron monolayers (BMs) as electrocatalysts for the hydrogen evolution reaction (HER) by first-principles methods. Our calculations show that BMs are active catalysts for HER with nearly zero free energy of hydrogen adsorption, metallic conductivity and plenty of active sites in the basal plane. The effect of the substrate on HER activity is further assessed. It is found that the substrate has a positive effect on the HER performance caused by the competitive effect of mismatch strain and charge transfer. The in-depth understanding of the structure dependent HER activity is also provided.

Oxidation Mechanism and Protection Strategy of Ultrathin Indium Selenide: Insight from Theory.

Ultrathin indium selenide (InSe), as a newly emerging two-dimensional material with high carrier mobility and a broad absorption spectrum, has been the focus of current research. However, the long-term environmental instability of atomically thin InSe seriously limits its practical applications. To develop an effective strategy to protect InSe, it is crucial to reveal the degradation mechanism at the atomic level. By employing density functional theory and ab initio molecular dynamics simulations, we provide an in-depth understanding of the oxidation mechanism of InSe. The defect-free InSe presents excellent stability against oxidation. Nevertheless, the Se vacancies on the surface can react with water and oxygen in air directly and activate the neighboring In-Se bonds on the basal plane for further oxidation, leading to complete degradation of InSe into oxidation products of In2O3 and elemental Se. Furthermore, we propose an efficient strategy to repair the Se vacancies by thiol chemistry. In this way, the repaired surface can resist oxidation from oxygen and retain the original high electron mobility of pristine InSe simultaneously.