Designing Nanoporous Polymer Films for High-Performance Passive Daytime Radiative Cooling.

Energy-free passive daytime radiative cooling (PDRC) technology makes it an attractive solution to both the building energy crisis and global warming. Spectrally selective porous polymers have great potential for practical PDRC applications owing to their cooling performance and scalability. A fundamental understanding of the relationship between the cooling performance and pore properties is crucial for guiding future structural designs of high-performance PDRC materials. However, one of the key challenges is achieving uniform nanopores and tailorable pore morphologies in the PDRC coating films. Here we demonstrate a strategy to use advanced metal-organic framework (MOF) nanocrystals as a sacrificial template creating a nanoporous poly(vinylidene fluoride) (PVDF) coating film with uniform-sized nanopores for highly daytime passive radiative cooling. The experimental evidence indicates that nanopores around 400 nm in size, comparable to the wavelength within the ultraviolet and visible spectra, along with an appropriate porosity of 37%, contribute to excellent solar reflectance (94.9 ± 0.8%) and high long-wave infrared emission (92.8 ± 1.4%) in the resulting porous PVDF films. This leads to subambient cooling of ≈9.5 °C and a promising net cooling power of 137 W/m2 at midday under solar intensities of ∼1275 and ∼1320 W/m2. The performance equals or exceeds that of state-of-the-art polymeric PDRC designs, and this general strategy of tailing nanostructures is expected to open a new avenue toward high-performance radiative cooling materials for PDRC applications.

Effectiveness and Safety of Qishen Yiqi Dripping Pill in Patients with Acute Coronary Syndrome after Percutaneous Coronary Intervention: 3-Year Results from a Multicentre Cohort Study.

OBJECTIVES: To evaluate the effectiveness and safety of Qishen Yiqi Dripping Pill (QSYQ) in patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). METHODS: This multicentre prospective cohort study was conducted at 40 centers in China. Patients with ACS after PCI entered either the QSYQ or Western medicine (WM) groups naturally based on whether they had received QSYQ before enrollment. QSYQ group received QSYQ (0.52 g, 3 times a day for 12 months) in addition to WM. The primary endpoint included cardiac death, non-fatal myocardial infarction, and urgent revascularization. The secondary endpoint included rehospitalization due to ACS, heart failure, stroke, and other thrombotic events. Quality of life was assessed by the Seattle Angina Questionnaire (SAQ). RESULTS: A total of 936 patients completed follow-up of the primary endpoint from February 2012 to December 2018. Overall, 487 patients received QSYQ and WM. During a median follow-up of 566 days (inter quartile range, IQR, 517-602), the primary endpoint occurred in 46 (9.45%) and 65 (14.48%) patients in QSYQ and WM groups respectively [adjusted hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.41-0.90; P=0.013]. The secondary endpoint occurred in 61 (12.53%) and 74 (16.48%) patients in QSYQ and WM groups, respectively (adjusted HR 0.76, 95% CI 0.53-1.09; P=0.136). In sensitivity analysis, the results still demonstrated that WM combined with QSYQ reduced the risk of the primary endpoint (HR 0.67, 95% CI 0.46-0.98; P=0.039). Moreover, QSYQ improved the disease perception domain of the SAQ (P<0.05). CONCLUSION: In patients with ACS after PCI, QSYQ combined with WM reduced the incidence of the primary endpoint. These findings provide a promising option for managing ACS after PCI and suggest the potential treatment for reducing the risk of primary endpoint included cardiac death, non-fatal myocardial infarction, and urgent revascularization through intermittent administration of QSYQ (Registration No. ChiCTR-OOC-14005552).

Neural-network Density Functional Theory Based on Variational Energy Minimization.

Deep-learning density functional theory (DFT) shows great promise to significantly accelerate material discovery and potentially revolutionize materials research. However, current research in this field primarily relies on data-driven supervised learning, making the developments of neural networks and DFT isolated from each other. In this work, we present a theoretical framework of neural-network DFT, which unifies the optimization of neural networks with the variational computation of DFT, enabling physics-informed unsupervised learning. Moreover, we develop a differential DFT code incorporated with deep-learning DFT Hamiltonian, and introduce algorithms of automatic differentiation and backpropagation into DFT, demonstrating the capability of neural-network DFT. The physics-informed neural-network architecture not only surpasses conventional approaches in accuracy and efficiency, but also offers a new paradigm for developing deep-learning DFT methods.

Ectoine maintains the flavor and nutritional quality of broccoli during postharvest storage.

The bacterial derived osmolyte ectoine has been shown to stabilize cell structure and function, a property that may help to extend the shelf life of broccoli. The impact of ectoine on broccoli stored for 4 d at 20 °C and 90% relative humidity was investigated. Results indicated that 0.20% ectoine treatment maintained the quality of broccoli, by reducing rate of respiration and ethylene generation, while increasing the levels of total phenolics, flavonoids, TSS, soluble protein, and vitamin C, relative to control. Headspace-gas chromatography-mass spectrometry, transcriptomic and metabolomic analyses revealed that ectoine stabilized aroma components in broccoli by maintaining level of volatile compounds and altered the expression of genes and metabolites associated with sulfur metabolism, as well as fatty acid and amino acid biosynthesis pathways. These findings provide a greater insight into how ectoine preserves the flavor and nutritional quality of broccoli, thus, extending its shelf life.

Spontaneous Inversion Symmetry Breaking and Emergence of Berry Curvature and Orbital Magnetization in Topological ZrTe_{5} Films.

ZrTe_{5} has recently attracted much attention due to the observation of intriguing nonreciprocal transport responses which necessitate the lack of inversion symmetry (I). However, there has been debate on the exact I-asymmetric structure and the underlying I-breaking mechanism. Here, we report a spontaneous I breaking in ZrTe_{5} films, which initiates from interlayer sliding and is stabilized by subtle intralayer distortion. Moreover, we predict significant nonlinear anomalous Hall effect (NAHE) and kinetic magnetoelectric effect (KME), which are attributed to the emergence of Berry curvature and orbital magnetization in the absence of I symmetry. We also explicitly manifest the direct coupling between sliding ferroelectricity, NAHE, and KME based on a sliding-dependent k·p model. By studying the subsurface sliding in ZrTe_{5} multilayers, we speculate that surface nonlinear Hall current and magnetization would emerge on the natural cleavage surface. Our findings elucidate the sliding-induced I-broken mechanism in ZrTe_{5} films and open new avenues for tuning nonreciprocal transport properties in Van der Waals layered materials.

Universal materials model of deep-learning density functional theory Hamiltonian.

Realizing large materials models has emerged as a critical endeavor for materials research in the new era of artificial intelligence, but how to achieve this fantastic and challenging objective remains elusive. Here, we propose a feasible pathway to address this paramount pursuit by developing universal materials models of deep-learning density functional theory Hamiltonian (DeepH), enabling computational modeling of the complicated structure-property relationship of materials in general. By constructing a large materials database and substantially improving the DeepH method, we obtain a universal materials model of DeepH capable of handling diverse elemental compositions and material structures, achieving remarkable accuracy in predicting material properties. We further showcase a promising application of fine-tuning universal materials models for enhancing specific materials models. This work not only demonstrates the concept of DeepH's universal materials model but also lays the groundwork for developing large materials models, opening up significant opportunities for advancing artificial intelligence-driven materials discovery.

Differences in the Ability of Lactic Acid Bacteria To Prevent Acute Alcohol-Induced Liver Injury via the Gut Microbiota-Bile Acid-Liver Axis.

Probiotics can regulate gut microbiota and protect against acute alcohol-induced liver injury through the gut-liver axis. However, efficacy is strain-dependent, and their mechanism remains unclear. This study investigated the effect of lactic acid bacteria (LAB), including Lacticaseibacillus paracasei E10 (E10), Lactiplantibacillus plantarum M (M), Lacticaseibacillus rhamnosus LGG (LGG), Lacticaseibacillus paracasei JN-1 (JN-1), and Lacticaseibacillus paracasei JN-8 (JN-8), on the prevention of acute alcoholic liver injury in mice. We found that LAB pretreatment reduced serum alanine transaminase (ALT) and aspartate transaminase (AST) and reduced hepatic total cholesterol (TC) and triglyceride (TG). JN-8 pretreatment exhibited superior efficacy in improving hepatic antioxidation. LGG and JN-8 pretreatment significantly attenuated hepatic and colonic inflammation by decreasing the expression of interleukin 6 (IL-6) and tumor necrosis factor α (TNF-α) and increasing the expression of interleukin 10 (IL-10). JN-1 and JN-8 pretreatments have better preventive effects than other LAB pretreatment on intestinal barrier dysfunction. In addition, the LAB pretreatment improved gut microbial dysbiosis and bile acid (BA) metabolic abnormality. All of the strains were confirmed to have bile salt deconjugation capacities in vitro, where M and JN-8 displayed higher activities. This study provides new insights into the prevention and mechanism of LAB strains in preventing acute alcoholic liver injury.

Hidden Charge Order and Multiple Electronic Instabilities in EuTe4.

The rare-earth telluride compound EuTe4 exhibits a charge density wave (CDW) and an unconventional thermal hysteresis transition. Herein, we report a comprehensive study of the CDW states in EuTe4 by using low-temperature scanning tunneling microscopy. Two types of charge orders are observed at 4 K, including a newly discovered spindle-shaped pattern and a typical stripe-like pattern. As an exotic charge order, the spindle-shaped CDW is off-axis and barely visible at 77 K, indicating that it is a hidden order developed at low temperature. Based on our first-principles calculations, we reveal the origins of the observed electronic instabilities. The spindle-shaped charge order stems from a subsequent transition based on the stripe-like CDW phase. Our work demonstrates that the competition and cooperation between multiple charge orders can generate exotic quantum phases.

Observation of dichotomic field-tunable electronic structure in twisted monolayer-bilayer graphene.

Twisted bilayer graphene (tBLG) provides a fascinating platform for engineering flat bands and inducing correlated phenomena. By designing the stacking architecture of graphene layers, twisted multilayer graphene can exhibit different symmetries with rich tunability. For example, in twisted monolayer-bilayer graphene (tMBG) which breaks the C2z symmetry, transport measurements reveal an asymmetric phase diagram under an out-of-plane electric field, exhibiting correlated insulating state and ferromagnetic state respectively when reversing the field direction. Revealing how the electronic structure evolves with electric field is critical for providing a better understanding of such asymmetric field-tunable properties. Here we report the experimental observation of field-tunable dichotomic electronic structure of tMBG by nanospot angle-resolved photoemission spectroscopy (NanoARPES) with operando gating. Interestingly, selective enhancement of the relative spectral weight contributions from monolayer and bilayer graphene is observed when switching the polarity of the bias voltage. Combining experimental results with theoretical calculations, the origin of such field-tunable electronic structure, resembling either tBLG or twisted double-bilayer graphene (tDBG), is attributed to the selectively enhanced contribution from different stacking graphene layers with a strong electron-hole asymmetry. Our work provides electronic structure insights for understanding the rich field-tunable physics of tMBG.

Chirality-Dependent Dynamic Evolution for Trions in Monolayer WS2.

Monolayer transition metal dichalcogenides exhibit valley-dependent excitonic characters with a large binding energy, acting as the building block for future optoelectronic functionalities. Herein, combined with pump-probe ultrafast transient transmission spectroscopy and theoretical simulations, we reveal the chirality-dependent trion dynamics in h-BN encapsulated monolayer tungsten disulfide. By resonantly pumping trions in a single valley and monitoring their temporal evolution, we identify the temperature-dependent competition between two relaxation channels driven by chirality-dependent scattering processes. At room temperature, the phonon-assisted upconversion process predominates, converting excited trions to excitons within the same valley on a sub-picosecond (ps) time scale. As temperature decreases, this process becomes less efficient, while alternative channels, notably valley depolarization process for trions, assume importance, leading to an increase of trion density in the unpumped valley within a ps time scale. Our time-resolved valley-contrast results provide a comprehensive insight into trion dynamics in 2D materials, thereby advancing the development of novel valleytronic devices.

Evolution of the flat band and the role of lattice relaxations in twisted bilayer graphene.

Magic-angle twisted bilayer graphene exhibits correlated phenomena such as superconductivity and Mott insulating states related to the weakly dispersing flat band near the Fermi energy. Such a flat band is expected to be sensitive to both the moiré period and lattice relaxations. Thus, clarifying the evolution of the electronic structure with the twist angle is critical for understanding the physics of magic-angle twisted bilayer graphene. Here we combine nano-spot angle-resolved photoemission spectroscopy and atomic force microscopy to resolve the fine electronic structure of the flat band and remote bands, as well as their evolution with twist angle from 1.07° to 2.60°. Near the magic angle, the dispersion is characterized by a flat band near the Fermi energy with a strongly reduced band width. Moreover, we observe a spectral weight transfer between remote bands at higher binding energy, which allows to extract the modulated interlayer spacing near the magic angle. Our work provides direct spectroscopic information on flat band physics and highlights the important role of lattice relaxations.

Deep-Learning Density Functional Perturbation Theory.

Calculating perturbation response properties of materials from first principles provides a vital link between theory and experiment, but is bottlenecked by the high computational cost. Here, a general framework is proposed to perform density functional perturbation theory (DFPT) calculations by neural networks, greatly improving the computational efficiency. Automatic differentiation is applied on neural networks, facilitating accurate computation of derivatives. High efficiency and good accuracy of the approach are demonstrated by studying electron-phonon coupling and related physical quantities. This work brings deep-learning density functional theory and DFPT into a unified framework, creating opportunities for developing ab initio artificial intelligence.

Tunable quantum anomalous Hall effects in ferromagnetic van der Waals heterostructures.

The quantum anomalous Hall effect (QAHE) has unique advantages in topotronic applications, but it is still challenging to realize the QAHE with tunable magnetic and topological properties for building functional devices. Through systematic first-principles calculations, we predict that the in-plane magnetization induced QAHE with Chern numbers C = ±1 and the out-of-plane magnetization induced QAHE with high Chern numbers C = ±3 can be realized in a single material candidate, which is composed of van der Waals (vdW) coupled Bi and MnBi2Te4 monolayers. The switching between different phases of QAHE can be controlled in multiple ways, such as applying strain or (weak) magnetic field or twisting the vdW materials. The prediction of an experimentally available material system hosting robust, highly tunable QAHE will stimulate great research interest in the field. Our work opens a new avenue for the realization of tunable QAHE and provides a practical material platform for the development of topological electronics.

Lactic acid fermentation of goji berries (Lycium barbarum) prevents acute alcohol liver injury and modulates gut microbiota and metabolites in mice.

Juice fermented with lactic acid bacteria (LAB) has received attention due to its health benefits, such as antioxidant and anti-inflammatory. Previous research on LAB-fermented goji juice mainly focused on exploring the changes in the metabolite profile and antioxidant activity in vitro, whereas the liver protection properties of LAB-fermented goji juice in vivo are still unknown. This study aimed to investigate the effects of Lacticaseibacillus paracasei E10-fermented goji juice (E10F), Lactiplantibacillus plantarum M-fermented goji juice (MF), Lacticaseibacillus rhamnosus LGG-fermented goji juice (LGGF) on preventing acute alcoholic liver injury with physiology, gut microbial, and metabolic profiles in mice. Compared with goji juice, E10F, MF, and LGGF enhanced the protective effect against liver injury by reducing serum alanine transaminase (ALT) levels, improving the hepatic glutathione (GSH) antioxidant system, and attenuating inflammation by decreasing the levels of interleukin (IL)-1ß, IL-6, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-ß. Furthermore, E10F, MF, and LGGF increased intestinal integrity, restructured the gut microbiota including Bacteroides and Lactobacillus, and altered gut microbial metabolites including kyotorphin, indolelactic acid, and N-methylserotonin. Pretreatment of different LAB-fermented goji juice in mice showed significant differences in gut microbiota and metabolism. The correlation analysis demonstrated that the increase of Lactobacillus, indolelactic acid, and N-methylserotonin by E10F, MF, and LGGF was positively correlated with reduced inflammation and improved liver and gut function. Taken together, E10F, MF, and LGGF all have the potential to be converted into dietary interventions to combat acute alcoholic liver injury. It provided a reference for the study of the hepatoprotective effect of LAB-fermented goji juice.

Molecular understanding of the critical role of alkali metal cations in initiating CO2 electroreduction on Cu(100) surface.

Molecular understanding of the solid-liquid interface is challenging but essential to elucidate the role of the environment on the kinetics of electrochemical reactions. Alkali metal cations (M+), as a vital component at the interface, are found to be necessary for the initiation of carbon dioxide reduction reaction (CO2RR) on coinage metals, and the activity and selectivity of CO2RR could be further enhanced with the cation changing from Li+ to Cs+, while the underlying mechanisms are not well understood. Herein, using ab initio molecular dynamics simulations with explicit solvation and enhanced sampling methods, we systematically investigate the role of M+ in CO2RR on Cu surface. A monotonically decreasing CO2 activation barrier is obtained from Li+ to Cs+, which is attributed to the different coordination abilities of M+ with *CO2. Furthermore, we show that the competing hydrogen evolution reaction must be considered simultaneously to understand the crucial role of alkali metal cations in CO2RR on Cu surfaces, where H+ is repelled from the interface and constrained by M+. Our results provide significant insights into the design of electrochemical environments and highlight the importance of explicitly including the solvation and competing reactions in theoretical simulations of CO2RR.

Water extract of Pingchuan formula ameliorated murine asthma through modulating metabolites and gut microbiota.

BACKGROUND: Pingchuan formula is a traditional Chinese herbal prescription for asthma, but its components and underlying mechanisms remain unclear. Here, we evaluated its anti-asthmatic actvity and regulatory effects on the gut microbiota in mice based on the traditional Chinese medicine Zang-Fu theory, which proposed the exterior-interior relationship between the lung and the large intestine. METHODS: Mouse model withovalbumin (OVA)-induced asthma was used to assess the protective effect of the water extract of Pingchuan formula (PC). The chemical compounds of PC and mouse serum metabolites were identified by Ultraperformance liquid chromatography-Q Exactive HF-X spectrometry. Gut microbiota was evaluated by 16 S rRNA gene sequencing. The gut microbiota was depleted with a broad-spectrum antibiotic mixture (Abx) to explore whether it plays a role in the protective effects of PC. RESULTS: PC mainly contains phenols, flavonoids, alkaloids, carboxylic acids, and their derivatives. PC attenuated OVA-induced asthma in mice by alleviating inflammatory infiltration, indicated by decreased levels of IL-18, IL-6, IL-4, and Eotaxin in lung tissues. PC treatment altered the serum metabolites and affected the pyrimidine pathway. In addition, our results showed that acacetin and abscisic acid were the key serum metabolites PC treatment changed the composition of gut microbiota by increasing the relative abundance of Clostridia_UCG_014 and Akkermansia while decreasing Blautia, Barnesiella, and Clostridium_Ⅲ at the genus level. Importantly, the Abx treatment partly abolished the anti-asthmatic effect of PC. CONCLUSION: We demonstrated that PC could alleviate OVA-induced asthma in mice and protect against inflammatory infiltration in lungs via modulating the serum metabolites and gut microbiota, thereby providing a new reference for the therapeutic effect of PC.

Floquet Engineering of Black Phosphorus upon Below-Gap Pumping.

Time-periodic light field can dress the electronic states and lead to light-induced emergent properties in quantum materials. While below-gap pumping is regarded favorable for Floquet engineering, so far direct experimental evidence of momentum-resolved band renormalization still remains missing. Here, we report experimental evidence of light-induced band renormalization in black phosphorus by pumping at photon energy of 160 meV, which is far below the band gap, and the distinction between below-gap pumping and near-resonance pumping is revealed. Our Letter demonstrates light-induced band engineering upon below-gap pumping, and provides insights for extending Floquet engineering to more quantum materials.

Intrinsic Nonlinear Hall Detection of the Néel Vector for Two-Dimensional Antiferromagnetic Spintronics.

The respective unique merit of antiferromagnets and two-dimensional (2D) materials in spintronic applications inspires us to exploit 2D antiferromagnetic spintronics. However, the detection of the Néel vector in 2D antiferromagnets remains a great challenge because the measured signals usually decrease significantly in the 2D limit. Here we propose that the Néel vector of 2D antiferromagnets can be efficiently detected by the intrinsic nonlinear Hall (INH) effect which exhibits unexpected significant signals. As a specific example, we show that the INH conductivity of the monolayer manganese chalcogenides MnX (X=S, Se, Te) can reach the order of nm·mA/V^{2}, which is orders of magnitude larger than experimental values of paradigmatic antiferromagnetic spintronic materials. The INH effect can be accurately controlled by shifting the chemical potential around the band edge, which is experimentally feasible via electric gating or charge doping. Moreover, we explicitly demonstrate its 2π-periodic dependence on the Néel vector orientation based on an effective k·p model. Our findings enable flexible design schemes and promising material platforms for spintronic memory device applications based on 2D antiferromagnets.

A computational study on bifunctional 1T-MnS2 with an adsorption-catalysis effect for lithium-sulfur batteries.

Lithium-sulfur (Li-S) batteries are promising rechargeable energy storage systems with a high energy density, environmental friendliness and low cost. However, the commercialization process of Li-S batteries has been seriously hindered by the shuttling of lithium polysulfides (LiPSs) and the sluggish kinetics of conversion reaction among sulfur species. In this work, the adsorption-catalysis performance of five transition metal disulfide 1T-MS2 (M = Mn, V, Ti, Zr, and Hf) surfaces is investigated by evaluating the adsorption energy of sulfur species, Li-ion diffusion energy barrier, decomposition energy barrier of Li2S, and the Gibbs free energy barrier of the sulfur reduction reaction based on first-principles calculations. Our results show that the sulfiphilicity of 1T-MS2 plays an important role in the adsorption behavior of short-chain sulfur species, in addition to lithiophilicity. Remarkably, among the five 1T-MS2 materials, our results confirm that 1T-TiS2 and 1T-VS2 show excellent adsorption-catalysis performance and it is predicted that 1T-MnS2 is an even better candidate catalyst to inhibit the shuttle effect and accelerate delithiation/lithiation kinetics. Moreover, the outstanding performance of 1T-MnS2 persists in a solvent environment and under strain modulation. Our results not only demonstrate that 1T-MnS2 is an excellent potential catalyst for high-performance Li-S batteries, but also provide great insights into the adsorption-catalysis mechanism during the cycling process.