The Mechanisms Underlying Chinese Medicines to Treat Inflammation in Diabetic Kidney Disease.

ETHNIC PHARMACOLOGICAL RELEVANCE: Diabetic kidney disease (DKD) is the main cause of end-stage renal disease (ESRD), which is a public health problem with a significant economic burden. Serious adverse effects, such as hypotension, hyperkalemia, and genitourinary infections, as well as increasing adverse cardiovascular events, limit the clinical application of available drugs. Plenty of randomized controlled trials(RCTs), meta-analysis(MAs) and systematic reviews(SRs) have demonstrated that many therapies that have been used for a long time in medical practice including Chinese patent medicines(CPMs), Chinese medicine prescriptions, and extracts are effective in alleviating DKD, but the mechanisms by which they work are still unknown. Currently, targeting inflammation is a central strategy in DKD drug development. In addition, many experimental studies have identified many Chinese medicine prescriptions, medicinal herbs and extracts that have the potential to alleviate DKD. And part of the mechanisms by which they work have been uncovered. AIM OF THIS REVIEW: This review aims to summarize therapies that have been proven effective by RCTs, MAs and SRs, including CPMs, Chinese medicine prescriptions, and extracts. This review also focuses on the efficiency and potential targets of Chinese medicine prescriptions, medicinal herbs and extracts discovered in experimental studies in improving immune inflammation in DKD. METHODS: We searched for relevant scientific articles in the following databases: PubMed, Google Scholar, and Web of Science. We summarized effective CPMs, Chinese medicine prescriptions, and extracts from RCTs, MAs and SRs. We elaborated the signaling pathways and molecular mechanisms by which Chinese medicine prescriptions, medicinal herbs and extracts alleviate inflammation in DKD according to different experimental studies. RESULTS: After overviewing plenty of RCTs with the low hierarchy of evidence and MAs and SRs with strong heterogeneity, we still found that CPMs, Chinese medicine prescriptions, and extracts exerted promising protective effects against DKD. However, there is insufficient evidence to prove the safety of Chinese medicines. As for experimental studies, Experiments in vitro and in vivo jointly demonstrated the efficacy of Chinese medicines(Chinese medicine prescriptions, medicinal herbs and extracts) in DKD treatment. Chinese medicines were able to regulate signaling pathways to improve inflammation in DKD, such as toll-like receptors, NLRP3 inflammasome, Nrf2 signaling pathway, AMPK signaling pathway, MAPK signaling pathway, JAK-STAT, and AGE/RAGE. CONCLUSION: Chinese medicines (Chinese medicine prescriptions, medicinal herbs and extracts) can improve inflammation in DKD. For drugs that are effective in RCTs, the underlying bioactive components or extracts should be identified and isolated. Attention should be given to their safety and pharmacokinetics. Acute, subacute, and subchronic toxicity studies should be designed to determine the magnitude and tolerability of side effects in humans or animals. For drugs that have been proven effective in experimental studies, RCTs should be designed to provide reliable evidence for clinical translation. In a word, Chinese medicines targeting immune inflammation in DKD are a promising direction.

Clinical characteristics and risk factors in patients with SARS-CoV-2 Omicron variant infection complicated with cardiovascular diseases.

Objective: To investigate the clinical characteristics and risk factors of patients with SARS-CoV-2 Omicron variant infection complicated with cardiovascular diseases. Methods: A retrospective analysis of general clinical data was conducted on patients with SARS-CoV-2 omicron infection complicated with hypertension, coronary heart disease, and heart failure admitted to one hospital in Guangdong Province from December 1, 2022, to February 28, 2023. Clinical symptoms, laboratory tests, imaging examinations, treatment, and clinical outcomes were collected. Multivariate logistic regression analysis was used to analyze the risk factors for mortality in patients with SARS-CoV-2 Omicron variant infection complicated with cardiovascular diseases. ROC curves were drawn to evaluate the predictive value of CRP, D-dimer, and CK-MB in predicting the risk of death. Results: A total of 364 confirmed cases were included, divided into the asymptomatic group, mild to moderate group, and severe to critically ill group based on the symptoms of COVID-19. There were 216 males (59.34%) and 148 females (40.66%), with a median age of 75 years. The differences between the three groups in terms of sex and age were statistically significant (p < 0.05). The top three underlying diseases were hypertension (288 cases, 79.12%), coronary heart disease (100 cases, 27.47%), and diabetes (84 cases, 23.08%). The differences in unvaccinated and triple-vaccinated patients among the three groups were statistically significant (p < 0.05). The common respiratory symptoms were cough in 237 cases (65.11%) and sputum production in 199 cases (54.67%). In terms of laboratory tests, there were statistically significant differences in neutrophils, lymphocytes, red blood cells, C-reactive protein, D-dimer, aspartate aminotransferase, and creatinine among the three groups (p < 0.05). In imaging examinations, there were statistically significant differences among the three groups in terms of unilateral pulmonary inflammation, bilateral pulmonary inflammation, and bilateral pleural effusion (p < 0.05). There were statistically significant differences among the three groups in terms of antibiotic treatment, steroid treatment, oxygen therapy, nasal cannula oxygen inhalation therapy, non-invasive ventilation, and tracheal intubation ventilation (p < 0.05). Regarding clinical outcomes, there were statistically significant differences among the three groups in terms of mortality (p < 0.05). Multivariate logistic regression analysis showed that CRP (OR = 1.012, 95% CI = 1.004-1.019) and D-dimer (OR = 1.117, 95% CI = 1.021-1.224) were independent risk factors for patient mortality. The predictive value of CRP, D-dimer, and CK-MB for the risk of death was assessed. D-dimer had the highest sensitivity (95.8%) in predicting patient mortality risk, while CRP had the highest specificity (84.4%). Conclusion: For patients with COVID-19 and concomitant cardiovascular diseases without contraindications, early administration of COVID-19 vaccines and booster shots can effectively reduce the mortality rate of severe cases. Monitoring biomarkers such as CRP, D-dimer, and CK-MB and promptly providing appropriate care can help mitigate the risk of mortality in patients.

Floating Bimetallic Catalysts for Growing 30 cm-Long Carbon Nanotube Arrays with High Yields and Uniformity.

Ultralong carbon nanotubes (CNTs) are considered as promising candidates for many cutting-edge applications. However, restricted by the extremely low yields of ultralong CNTs, their practical applications can hardly be realized. Therefore, new methodologies shall be developed to boost the growth efficiency of ultralong CNTs and alleviate their areal density decay at the macroscale level. Herein, a facile, universal, and controllable method for the in situ synthesis of floating bimetallic catalysts (FBCs) is proposed to grow ultralong CNT arrays with high yields and uniformity. Ferrocene and metal acetylacetonates serve as catalyst precursors, affording the successful synthesis of a series of FBCs with controllable compositions. Among these FBCs, the optimized FeCu catalyst increases the areal density of ultralong CNT arrays to a record-breaking value of ≈8100 CNTs mm-1 and exhibits a lifetime 3.40 times longer than that of Fe, thus achieving both high yields and uniformity. A 30-centimeters-long and high-density ultralong CNT array is also successfully grown with the assistance of FeCu catalysts. As evidenced by this kinetic model and molecular dynamics simulations, the introduction of Cu into Fe can simultaneously improve the catalyst fluidity and decrease carbon solubility, and an optimal catalytic performance will be achieved by balancing this tradeoff.

Formation of Volatile Pyrazinones in the Asparagine Maillard Reaction Systems and Novel Pyrazinone Formation Pathways in the Amidated-Alanine Maillard Reaction Systems.

Maillard reaction (MR) plays a pivotal role in the food flavor industry, including a cascade of reactions starting with the reaction between amino compounds and reducing sugars, and thus provides various colors and flavors. A new group of volatile compounds called pyrazinones found in MR are now getting more attention. In this study, eight volatile pyrazinones were found in the asparagine MR systems, in which 3,5-dimethyl- and 3,6-dimethyl-2(1H)-pyrazinones were reported for the first time. The major formation pathways were the reactions between asparagine and α-dicarbonyls, with decarboxylation as a critical step. Besides, novel alternative pathways involving alanine amidation and successive reactions with α-dicarbonyls were explored and successfully formed eight pyrazinones. The major differences between alanine-amidated pathways and decarboxylation pathways are the amidation step and absence of the decarboxylation step. For the alanine-amidated pathways, the higher the temperature, the better the amidation effect. The optimal amidation temperature was 200 °C in this study. The reaction between the alanine amide and α-dicarbonyls after amidation can happen at low temperatures, such as 35 and 50 °C, proposing the possibility of pyrazinone formation in real food systems. Further investigations should be conducted to investigate volatile pyrazinones in various food systems as well as the biological effects and kinetic formation differences of the volatile pyrazinones.

Advances in Flexible Magnetosensitive Materials and Devices for Wearable Electronics.

Emerging fields, such as wearable electronics, digital healthcare, the Internet of Things, and humanoid robots, highlight the need for flexible devices capable of recording signals on curved surfaces and soft objects. In particular, flexible magnetosensitive devices garner significant attention owing to their ability to combine the advantages of flexible electronics and magnetoelectronic devices, such as reshaping capability, conformability, contactless sensing, and navigation capability. Several key challenges must be addressed to develop well-functional flexible magnetic devices. These include determining how to make magnetic materials flexible and even elastic, understanding how the physical properties of magnetic films change under external strain and stress, and designing and constructing flexible magnetosensitive devices. In recent years, significant progress is made in addressing these challenges. This study aims to provide a timely and comprehensive overview of the most recent developments in flexible magnetosensitive devices. This includes discussions on the fabrications and mechanical regulations of flexible magnetic materials, the principles and performances of flexible magnetic sensors, and their applications for wearable electronics. In addition, future development trends and challenges in this field are discussed.

Self-calibrated atom-interferometer gyroscope by modulating atomic velocities.

Atom-interferometer gyroscopes have attracted much attention for their long-term stability and extremely low drift. For such high-precision instruments, self-calibration to achieve an absolute rotation measurement is critical. In this work, we propose and demonstrate the self-calibration of an atom-interferometer gyroscope. This calibration is realized by using the detuning of the laser frequency to control the atomic velocity, thus modulating the scale factor of the gyroscope. The modulation determines the order and the initial phase of the interference stripe, thus eliminating the ambiguity caused by the periodicity of the interferometric signal. This self-calibration method is validated through a measurement of the Earth's rotation rate, and a relative uncertainty of 162 ppm is achieved. Long-term stable and self-calibrated atom-interferometer gyroscopes have important applications in the fields of fundamental physics, geophysics, and long-time navigation.

Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery.

BACKGROUND: Intraoperative hypotension during cesarean section has become a serious complication for maternal and fetal healthy. It is commonly encountered by subarachnoid anesthesia. However, currently used control methods have varying degrees of side effects, such as drugs. The Root Cause Analysis (RCA) - Plan, Do, Check, Act (PDCA) is a new model of care that identifies the root causes of problems. The study aimed to demonstrate the usefulness of RCA-PDCA nursing methods in preventing intraoperative hypotension during cesarean section and to predict the occurrence of intraoperative hypotension through a machine learning model. METHODS: Patients who underwent cesarean section at Traditional Chinese Medicine of Southwest Medical University from January 2023 to December 2023 were retrospectively screened, and the data of their gestational times, age, height, weight, history of allergies, intraoperative vital signs, fetal condition, operative time, fluid out and in, adverse effects, use of vasopressor drugs, anxiety-depression-pain scores, and satisfaction were collected and analyzed. The statistically different features were screened and five machine learning models were used as predictive models to assess the usefulness of the RCA-PDCA model of care. RESULTS: (1) Compared with the general nursing model, the RCA-PDCA nursing model significantly reduces the incidence of intraoperative hypotension and postoperative complications in cesarean delivery, and the patient experience is comfortable and satisfactory. (2) Among the five machine learning models, the RF model has the best predictive performance, and the accuracy of the random forest model in preventing intraoperative hypotension is as high as 90%. CONCLUSION: Through computer machine learning model analysis, we prove the importance of the RCA-PDCA nursing method in the prevention of intraoperative hypotension during cesarean section, especially the Random Forest model which performed well and promoted the application of artificial intelligence computer learning methods in the field of medical analysis.

Formation of Volatile Pyrazinones in Amadori Rearrangement Products and Maillard Reaction Systems and the Major Formation Pathways.

Amadori rearrangement products (ARPs) are gaining more attention for their potential usage in the food flavor industry. Peptide-ARPs have been studied, but pyrazinones that were theoretically found in the Maillard reaction (MR) have not been reported to be formed from small peptide-ARPs. This study found four pyrazinones: 1-methyl-, 1,5-dimethyl-, 1,6-dimethyl-, and 1,5,6-trimethyl-2(1H)-pyrazinones in both MR and ARP systems. It was the first time 1-methyl-2(1H)-pyrazinone was reported, along with 1,5-dimethyl- and 1,5,6-trimethyl-2(1H)-pyrazinones being purified and analyzed by nuclear magnetic resonance for the first time. The primary formation routes of the pyrazinones were also proven as the reaction between diglycine and α-dicarbonyls, including glyoxal, methylglyoxal, and diacetyl. The pyrazinones, especially 1,5-dimethyl-2(1H)-pyrazinone, have strong fluorescence intensity, which may be the reason for the increase of fluorescence intensity in MR besides α-dicarbonyls. Cytotoxicity analysis showed that both Gly-/Digly-/Trigly-ARP and the three pyrazinones [1-methyl-, 1,5-dimethyl-, and 1,5,6-trimethyl-2(1H)-pyrazinones] showed no prominent cytotoxicity in the HepG2 cell line below 100 µg/mL, further suggesting that ARPs or pyrazinones could be used as flavor additives in the future. Further research should be conducted to investigate pyrazinones in various systems, especially the peptide-ARPs, which are ubiquitous in real food systems.

Iron-Catalyzed Photochemical Synthesis of Sulfinamides from Aliphatic Hydrocarbons and Sulfinylamines.

An iron-catalyzed photochemical sulfinamidation of hydrocarbons with N-sulfinylamines has been developed. The merger of ligand-to-metal charge transfer (LMCT) of FeCl3 with hydrogen atom transfer (HAT) process is the key for the generation of alkyl radicals from hydrocarbons, and the resultant alkyl radicals were readily trapped by N-sulfinylamines to produce structurally diverse sulfinamides. Contrary to traditional methods that inevitably use sensitive organometallic reagents and prefunctionalized substrates, our approach features simple operation and the wide availability of starting materials. Gratifyingly, the reaction is scalable, and the obtained sulfinamides can be conveniently converted to highly functionalized sulfur(VI) derivatives.

High-Performance Airflow Sensors Based on Suspended Ultralong Carbon Nanotube Crossed Networks.

Airflow sensors are in huge demand in many fields such as the aerospace industry, weather forecasting, environmental monitoring, chemical and biological engineering, health monitoring, wearable smart devices, etc. However, traditional airflow sensors can hardly meet the requirements of these applications in the aspects of sensitivity, response speed, detection threshold, detection range, and power consumption. Herein, this work reports high-performance airflow sensors based on suspended ultralong carbon nanotube (CNT) crossed networks (SCNT-CNs). The unique topologies of SCNT-CNs with abundant X junctions can fully exhibit the extraordinary intrinsic properties of ultralong CNTs and significantly improve the sensing performance and robustness of SCNT-CNs-based airflow sensors, which simultaneously achieved high sensitivity, fast response speed, low detection threshold, and wide detection range. Moreover, the capability for encapsulation also guaranteed the practicality of SCNT-CNs, enabling their applications in respiratory monitoring, flow rate display and transient response analysis. Simulations were used to unveil the sensing mechanisms of SCNT-CNs, showing that the piezoresistive responses were mainly attributed to the variation of junction resistances. This work shows that SCNT-CNs have many superiorities in the fabrication of advanced airflow sensors as well as other related applications.

Elastic Relaxor Ferroelectric by Thiol-ene Click Reaction.

As ferroelectrics hold significance and application prospects in wearable devices, the elastification of ferroelectrics becomes more and more important. Nevertheless, achieving elastic ferroelectrics requires stringent synthesis conditions, while the elastification of relaxor ferroelectric materials remains unexplored, presenting an untapped potential for utilization in energy storage and actuation for wearable electronics. The thiol-ene click reaction offers a mild and rapid reaction platform to prepare functional polymers. Therefore, we employed this approach to obtain an elastic relaxor ferroelectric by crosslinking an intramolecular carbon-carbon double bonds (CF=CH) polymer matrix with multiple thiol groups via a thiol-ene click reaction. The resulting elastic relaxor ferroelectric demonstrates pronounced relaxor-type ferroelectric behaviour. This material exhibits low modulus, excellent resilience, and fatigue resistance, maintaining a stable ferroelectric response even under strains up to 70 %. This study introduces a straightforward and efficient approach for the construction of elastic relaxor ferroelectrics, thereby expanding the application possibilities in wearable electronics.

Clopidogrel Plus Aspirin vs Aspirin Alone in Patients With Acute Mild to Moderate Stroke: The ATAMIS Randomized Clinical Trial.

Importance: Dual antiplatelet therapy has been demonstrated to be superior to single antiplatelet in reducing recurrent stroke among patients with transient ischemic attack or minor stroke, but robust evidence for its effect in patients with mild to moderate ischemic stroke is lacking. Objective: To evaluate whether dual antiplatelet therapy is superior to single antiplatelet among patients with mild to moderate ischemic stroke. Design, Setting, and Participants: This was a multicenter, open-label, blinded end point, randomized clinical trial conducted at 66 hospitals in China from December 20, 2016, through August 9, 2022. The date of final follow-up was October 30, 2022. The analysis was reported on March 12, 2023. Of 3065 patients with ischemic stroke, 3000 patients with acute mild to moderate stroke within 48 hours of symptom onset were enrolled, after excluding 65 patients who did not meet eligibility criteria or had no randomization outcome. Interventions: Within 48 hours after symptom onset, patients were randomly assigned to receive clopidogrel plus aspirin (n = 1541) or aspirin alone (n = 1459) in a 1:1 ratio. Main Outcomes and Measures: The primary end point was early neurologic deterioration at 7 days, defined as an increase of 2 or more points in National Institutes of Health Stroke Scale (NIHSS) score, but not as a result of cerebral hemorrhage, compared with baseline. The superiority of clopidogrel plus aspirin to aspirin alone was assessed based on a modified intention-to-treat population, which included all randomized participants with at least 1 efficacy evaluation regardless of treatment allocation. Bleeding events were safety end points. Results: Of the 3000 randomized patients, 1942 (64.6%) were men, the mean (SD) age was 65.9 (10.6) years, median (IQR) NIHSS score at admission was 5 (4-6), and 1830 (61.0%) had a stroke of undetermined cause. A total of 2915 patients were included in the modified intention-to-treat analysis. Early neurologic deterioration occurred in 72 of 1502 (4.8%) in the dual antiplatelet therapy group vs 95 of 1413 (6.7%) in the aspirin alone group (risk difference -1.9%; 95% CI, -3.6 to -0.2; P = .03). Similar bleeding events were found between 2 groups. Conclusions and Relevance: Among Chinese patients with acute mild to moderate ischemic stroke, clopidogrel plus aspirin was superior to aspirin alone with regard to reducing early neurologic deterioration at 7 days with similar safety profile. These findings indicate that dual antiplatelet therapy may be a superior choice to aspirin alone in treating patients with acute mild to moderate stroke. Trial Registration: ClinicalTrials.gov Identifier: NCT02869009.

A more biofriendly piezoelectric material.

A ferroelectric molecular crystal displays characteristics required for implantation.

Integrated self-injection-locked narrow linewidth laser based on thin-film lithium niobate.

Narrow linewidth lasers have a wide range of applications in the fields of coherent optical communications, atomic clocks, and measurement. Lithium niobate material possesses excellent electro-optic and thermo-optic properties, making it an ideal photonic integration platform for a new generation. The light source is a crucial element in large-scale photonic integration. Therefore, it is essential to develop integrated narrow linewidth lasers based on low-loss LNOI. This study is based on the multimode race-track type add-drop microring resonator with multimode interferometric coupler (MMRA-MRR) of the DFB laser self-injection-locked, to achieve the narrowing of linewidth to the laser. The microring external cavity was used to narrow the linewidth of the laser to 2.5 kHz. The output power of the laser is 3.18 mW, and the side-mode suppression ratio is 60 dB. This paper presents an integrated low-noise, narrow-linewidth laser based on thin-film lithium niobate material for the communication band. This is significant for achieving all-optical device on-chip integration of lithium niobate material in the future. It has great potential for use in high-speed coherent optical communication.

High-Curie-Temperature Elastic Polymer Ferroelectric by Carbene Cross-Linking.

With the emergence of wearable electronics, ferroelectrics are poised to serve as key components for numerous potential applications. Currently, intrinsically elastic ferroelectrics featuring a network structure through a precise "slight cross-linking" approach have been realized. The resulting elastic ferroelectrics demonstrate a combination of stable ferroelectric properties and remarkable resilience under various strains. However, challenges arose as the cross-linking temperature was too high when integrating ferroelectrics with other functional materials, and the Curie temperature of this elastic ferroelectric was comparatively low. Addressing these challenges, we strategically chose a poly(vinylidene fluoride)-based copolymer with high vinylidene fluoride content to obtain a high Curie temperature while synthesizing a cross-linker with carbene intermediate for high reactivity to reduce the cross-linking temperature. At a relatively low temperature, we successfully fabricated elastic ferroelectrics through carbene cross-linking. The resulting elastic polymer ferroelectrics exhibit a higher Curie temperature and show a stable ferroelectric response under strains up to 50%. These materials hold significant potential for integration into wearable electronics.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications.

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.

Assessing and prioritizing drivers and strategies for transition to a green energy for sustainable development in China.

This study addresses the critical global challenge of climate change, primarily caused by the overconsumption of fossil fuels. Recognizing the urgent need for a transition to green energy (GE) sources such as wind, solar, hydro, and biomass, this research focuses on identifying effective strategies for fostering a sustainable and low-carbon energy future in China. The study employs a combination of the Analytical Hierarchy Process (AHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL), both well-established multi-criteria decision-making (MCDM) methods, to analyze various drivers, sub-drivers, and strategies crucial for this transition. Through an extensive literature review, we identified several key drivers and strategies aiding the shift towards GE for sustainable development. The AHP method was applied to evaluate and rank the major drivers and sub-drivers, such as policy, financing, and infrastructure and innovation, that are crucial for China's successful transition to GE. Simultaneously, fuzzy DEMATEL was utilized to prioritize vital strategies, including public awareness and education, financial incentives and support mechanisms, and policy and regulatory frameworks. The findings reveal that, in addition to strong policy and financial support, public awareness and education are critical for advancing GE development in China. This study underscores the importance of integrating various drivers and strategies for effective green energy development, aiming to mitigate the environmental impacts of fossil fuel use.

Controlled Growth of Submillimeter-Scale Cr5Te8 Nanosheets and the Domain Wall Nucleation Governed Magnetization Reversal Process.

Two-dimensional (2D) ferromagnets have attracted widespread attention for promising applications in compact spintronic devices. However, the controlled synthesis of high-quality, large-sized, and ultrathin 2D magnets via facile, economical method remains challenging. Herein, we develop a hydrogen-tailored chemical vapor deposition approach to fabricating 2D Cr5Te8 ferromagnetic nanosheets. Interestingly, the time period of introducing hydrogen was found to be crucial for controlling the lateral size, and a Cr5Te8 single-crystalline nanosheet of lateral size up to ∼360 µm with single-unit-cell thickness has been obtained. These samples exhibit a leading role of domain wall nucleation in governing the magnetization reversal process, providing important references for optimizing the performances of associated devices. The nanosheets also show notable magnetotransport response, including nonmonotonous magnetic-field-dependent magnetoresistance and sizable anomalous Hall resistivity, demonstrating Cr5Te8 as a promising material for constructing high-performance magnetoelectronic devices. This study presents a breakthrough of large-sized CVD-grown 2D magnetic materials, which is indispensable for constructing 2D spintronic devices.

A dual-selective thermal emitter with enhanced subambient radiative cooling performance.

Radiative cooling is a zero-energy technology that enables subambient cooling by emitting heat into outer space (~3 K) through the atmospheric transparent windows. However, existing designs typically focus only on the main atmospheric transparent window (8-13 µm) and ignore another window (16-25 µm), under-exploiting their cooling potential. Here, we show a dual-selective radiative cooling design based on a scalable thermal emitter, which exhibits selective emission in both atmospheric transparent windows and reflection in the remaining mid-infrared and solar wavebands. As a result, the dual-selective thermal emitter exhibits an ultrahigh subambient cooling capacity (~9 °C) under strong sunlight, surpassing existing typical thermal emitters (≥3 °C cooler) and commercial counterparts (as building materials). Furthermore, the dual-selective sample also exhibits high weather resistance and color compatibility, indicating a high practicality. This work provides a scalable and practical radiative cooling design for sustainable thermal management.