Self-assembled high-entropy Prussian blue analogue nanosheets enabling efficient sodium storage.

High entropy material (HEM) has emerged as an appealing material platform for various applications, and specifically, the electrochemical performances of HEM could be further improved through self-assembled structure design. However, it remains a big challenge to construct such high-entropy self-assemblies primarily due to the compositional complexity. Herein, we propose a bottom-up directional freezing route to self-assemble high-entropy hydrosols into porous nanosheets. Taking Prussian blue analogue (PBA) as an example, the simultaneous coordination-substitution reactions yield stable high-entropy PBA hydrosols. During subsequent directional freezing process, the anisotropic growth of ice crystals could guide the two-dimensional confined assembly of colloidal nanoparticles, resulting in high-entropy PBA nanosheets (HE-PBA NSs). Thanks to the high-entropy and self-assembled structure design, the HE-PBA NSs manifests markedly enhanced sodium storage kinetics and performances in comparison with medium/low entropy nanosheets and high entropy nanoparticles.

Viscoelastic Extracellular Matrix Enhances Epigenetic Remodeling and Cellular Plasticity.

Living tissue and extracellular matrices possess viscoelastic properties, but understanding how viscoelastic matrix regulates chromatin and the epigenome is limited. Here, we find that the regulation of the epigenetic state by the viscoelastic matrix is more pronounced on softer matrices. Cells on viscoelastic matrices exhibit larger nuclei, increased nuclear lamina ruffling, loosely organized chromatin, and faster chromatin dynamics, compared to those on elastic matrices. These changes are accompanied by a global increase in euchromatic marks and a local increase in chromatin accessibility at the cis -regulatory elements associated with neuronal and pluripotent genes. Consequently, viscoelastic matrices enhanced the efficiency of reprogramming fibroblasts into neurons and induced pluripotent stem cells, respectively. Together, our findings demonstrate the key roles of matrix viscoelasticity in the regulation of epigenetic state, and uncover a new mechanism of biophysical regulation of chromatin and cell reprogramming, with implications for the design of smart materials to engineer cell fate.

Engineering vascularized skin-mimetic phantom for non-invasive Raman spectroscopy.

Recent advances in Raman spectroscopy have shown great potential for non-invasive analyte sensing, but the lack of a standardized optical phantom for these measurements has hindered further progress. While many research groups have developed optical phantoms that mimic bulk optical absorption and scattering, these materials typically have strong Raman scattering, making it difficult to distinguish metabolite signals. As a result, solid tissue phantoms for spectroscopy have been limited to highly scattering tissues such as bones and calcifications, and metabolite sensing has been primarily performed using liquid tissue phantoms. To address this issue, we have developed a layered skin-mimetic phantom that can support metabolite sensing through Raman spectroscopy. Our approach incorporates millifluidic vasculature that mimics blood vessels to allow for diffusion akin to metabolite diffusion in the skin. Furthermore, our skin phantoms are mechanically mimetic, providing an ideal model for development of minimally invasive optical techniques. By providing a standardized platform for measuring metabolites, our approach has the potential to facilitate critical developments in spectroscopic techniques and improve our understanding of metabolite dynamics in vivo.

Creating A child-friendly social environment for fewer conduct problems and more prosocial behaviors among children: A LASSO regression approach.

BACKGROUND: Creating a child-friendly social environment is an important component of promoting child-friendly city development. This study aims to explore the key indicators of friendly family, school and community social environments from the perspective of children's conduct problems and prosocial behaviors. METHOD: The sample included grade 3-5 students from one public elementary school in the urban areas and another public elementary school in the rural areas of a Chinese city pursuing a child-friendly philosophy. A total of 418 participants were included in this study. Data on conduct problems, prosocial behaviors and the social environment were collected. To effectively select important variables and eliminate estimation bias, this study used LASSO regression to identify key indicators predicting children's conduct problems and prosocial behavior, followed by linear regression coefficient estimation and significance testing. RESULTS: Creating a friendly family environment (ensuring family members' assistance with academic problems) and school environment (reducing cheating, fighting, and unfriendly teacher language) was associated with reduced conduct problems in children. Creating a positive family atmosphere (enhancing children's trust in family members), school environment (increasing parents' awareness of school affairs, reinforcing students' prosocial behavior, increasing extracurricular activity programs, and encouraging student engagement in academics) and community environment (respecting all children in the community) was associated with improving children's prosocial behavior. CONCLUSIONS: This study transforms the multidimensional, complex child-friendly social environment evaluation indicator system into concise and specific measurement indicators, which can provide theoretical and practical implications for government decision-making in child-friendly city development through empirical research.

Redox-tunable isoindigos for electrochemically mediated carbon capture.

Efficient CO2 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 CO2 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 >350 mV to impart sorbents with high oxygen stability without compromising CO2 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 CO2, addressing a longstanding challenge in developing effective carbon capture methods driven by non-conventional stimuli.

Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries.

Recently, deep learning surrogates and neural operators have shown promise in solving partial differential equations  (PDEs). However, they often require a large amount of training data and are limited to bounded domains. In this work, we present a novel physics-informed neural operator method to solve parameterized boundary value problems without labeled data. By reformulating the PDEs into boundary integral equations (BIEs), we can train the operator network solely on the boundary of the domain. This approach reduces the number of required sample points from O(Nd) to O(Nd-1), where d is the domain's dimension, leading to a significant acceleration of the training process. Additionally, our method can handle unbounded problems, which are unattainable for existing physics-informed neural networks (PINNs) and neural operators. Our numerical experiments show the effectiveness of parameterized complex geometries and unbounded problems.

Thin-film lithium niobate electro-optic isolator fabricated by photolithography assisted chemo-mechanical etching.

We report an electro-optic isolator fabricated on thin-film lithium niobate by photolithography-assisted chemo-mechanical etching that shows an isolation of 39.50 dB and an overall fiber-to-fiber loss of 2.6 dB.

A porous silicon composite with irregular silver nano-dendritic particles: a rapid optical sensor for trace detection of malachite green in freshwater fish.

This study focused on creating a SERS composite particle specifically designed for detecting malachite green. We synthesized silver nano-dendritic structures on p-type porous silicon using an external electric field, separating them from the silicon wafer. Ultrasonic crushing yielded irregular silver nanodendrite-modified porous silicon composite particles. Upon being tested in an aqueous solution of malachite green, these composite particles demonstrated significant surface-enhanced Raman scattering effects. Our findings highlight the exceptional performance of the SERS substrate composed of porous silicon and irregular silver nano-dendritic particles. It exhibited high sensitivity, specificity, consistent signal strength, and reliability in detecting trace amounts of malachite green in water. Under ideal conditions, the substrate could detect malachite green at concentrations as low as 10-8 M. Moreover, its swift response to trace amounts of malachite green in fish underscores its potential as an effective Raman detector.

Enhancing academic self-efficacy on decreasing adolescents' unmonitored internet usage and depressive mood.

Unmonitored internet use and depression are difficulties that adolescents experience. Efforts to promote healthy adolescent development tend to focus on reducing these two risk outcomes. Therefore, the purpose of this study was to examine how three important school-related factors (teachers, peers, and academics) affect adolescents' levels of unmonitored internet use and depression. For this study, a cross-sectional data analysis was conducted. The sample included 9297 students who participated in two waves of the China Education Panel Survey (CEPS). Structural equation modeling (SEM) was performed using LISREL 8.80 to analyze the data. Monte Carlo resampling was then performed using R to confirm the significance of the mediating effects. Teacher criticism and negative peers can increase unmonitored internet use and depression in adolescents, while academic stress can exacerbate depression. In contrast, teacher praise and positive peers can reduce those risk outcomes. Academic self-efficacy serves as a key mediator of the impacts of teachers, peers, and academics on adolescents' levels of unmonitored internet use and depression. We advocate that schools should establish a positive school climate, provide teacher feedback training and design physical activity programs to improve academic self-efficacy, thereby reducing the risk of unmonitored internet use and depression among adolescents, effectively preventing possible subsequent internet addiction and promoting the mental health of adolescents.

Data-driven inverse design of mode-locked fiber lasers.

The diverse applications of mode-locked fiber lasers (MLFLs) raise various demands on the output of the laser, including the pulse duration, energy, and shape. Simulation is an excellent method to guide the design and construction of an MLFL for on-demand laser output. Traditional simulation of an MLFL uses the split-step Fourier method (SSFM) to solve the nonlinear Schrödinger (NLS) equation, which suffers from high computational complexity. As a result, the inverse design of MLFLs via the traditional SSFM-based simulation method relies on the design experience. Here, a completely data-driven approach for the inverse design of MLFLs is proposed, which significantly reduces the computational complexity and achieves a fast automatic inverse design of MLFLs. We utilize a recurrent neural network to realize fast and accurate MLFL modeling, then the desired cavity settings meeting the output demands are searched via a deep-reinforcement learning algorithm. The results prove that the data-driven method enables the accurate inverse design of an MLFL to produce a preset target femtosecond pulse with a certain duration and pulse energy. In addition, the cavity settings generating soliton molecules with different target separations can also be located via the data-driven inverse design. With the GPU acceleration, the time consumption of the data-driven inverse design of an MLFL is less than 1.3 hours. The proposed data-driven approach is applicable to guide the inverse design of an MLFL to meet the different demands of various applications.

On-chip coherent beam combination of waveguide amplifiers on Er3+-doped thin film lithium niobate.

We demonstrate on-chip coherent beam combination of two waveguide amplifiers on Er3+-doped thin film lithium niobate (Er:TFLN) platform. Our device is built based on an electro-optic modulator fabricated on Er:TFLN. The output power of the coherently combined amplifiers is measured as high as 12.9 mW, surpassing that of previous single waveguide amplifiers based on an Er3+-doped thin film lithium niobate platform.

Functionalization of Pentacene: A Facile and Versatile Approach to Contorted Polycyclic Aromatic Hydrocarbons.

In this work, a facile and versatile strategy for the synthesis of contorted polycyclic aromatic hydrocarbons (PAHs) starting from the functionalized pentacene was established. A series of novel PAHs 1-4 and their derivatives were synthesized through a simple two-step synthesis procedure involving an intramolecular reductive Friedel-Crafts cyclization of four newly synthesized pentacene aldehydes 5-8 as a key step. All the molecules were confirmed by single-crystal X-ray diffraction and their photophysical and electrochemical properties were studied in detail. Interestingly, the most striking feature of 1-4 is their highly contorted carbon structures and the accompanying helical chirality. In particular, the optical resolution of 2 was successfully achieved by chiral-phase HPLC, and the enantiomers were characterized by circular dichroism and circularly polarized luminescence spectroscopy. Despite the highly nonplanar conformations, these contorted PAHs exhibited emissive properties with moderate-to-good fluorescence quantum yields, implying the potential utility of this series PAHs as high-quality organic laser dyes. By using a self-assembly method with the help of epoxy resin, a bottle microlaser based on 3 a was successfully illustrated with a lasing wavelength of 567.8 nm at a threshold of 0.3 mJ/cm2 . We believe that this work will shed light on the chemical versatility of pentacene and its derivatives in the construction of novel functionalized PAHs.

Erbium-ytterbium codoped thin-film lithium niobate integrated waveguide amplifier with a 27†dB internal net gain.

A photonic integrated waveguide amplifier fabricated on erbium-ytterbium (Er-Yb) codoped thin-film lithium niobate (TFLN) has been investigated in this work. A small-signal internal net gain of 27 dB is achieved at a signal wavelength of 1532 nm in the fabricated Er-Yb TFLN waveguide amplifier pumped by a diode laser at ≈980 nm. Experimental characterizations reveal the suitability of waveguide fabrication by the photolithography-assisted chemo-mechanical etching (PLACE) technique and also the gain in an Yb-sensitized-Er material. The demonstrated high-gain chip-scale TFLN amplifier is promising for interfacing with established lithium niobate integrated devices, greatly extending the spectrum of TFLN photonic applications.

Component Distribution Regulation in Sn-Pb Perovskite Solar Cells through Selective Molecular Interaction.

Tin-lead (Sn-Pb) perovskite solar cells (PSCs) with near-ideal bandgap still lag behind the pure lead PSCs. Disordered heterojunctions caused by inhomogeneous Sn/Pb ratio in the binary perovskite film induce large recombination loss. Here, an Sn-Pb perovskite film is reported with homogeneous component and energy distribution by introducing hydrazine sulfate (HS) in Sn perovskite precursor. HS can form hydrogen bond network and coordinate with FASnI3 thus no longer bond with Pb2+ , which reduces the crystallization rate of tin perovskite to the level of lead analog. The strong bonding between SO4 2- and Sn2+ can also suppress its oxidation. As a result, the Sn-Pb PSCs with HS exhibit a significantly improved VOC of 0.91 V along with a high efficiency of 23.17%. Meanwhile, the hydrogen bond interaction network, strong bonding between Sn2+ and sulfate ion also improve the thermal, storage, and air stability of resulting devices.

Continuous carbon capture in an electrochemical solid-electrolyte reactor.

Electrochemical carbon-capture technologies, with renewable electricity as the energy input, are promising for carbon management but still suffer from low capture rates, oxygen sensitivity or system complexity1-6. Here we demonstrate a continuous electrochemical carbon-capture design by coupling oxygen/water (O2/H2O) redox couple with a modular solid-electrolyte reactor7. By performing oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) redox electrolysis, our device can efficiently absorb dilute carbon dioxide (CO2) molecules at the high-alkaline cathode-membrane interface to form carbonate ions, followed by a neutralization process through the proton flux from the anode to continuously output a high-purity (>99%) CO2 stream from the middle solid-electrolyte layer. No chemical inputs were needed nor side products generated during the whole carbon absorption/release process. High carbon-capture rates (440 mA cm-2, 0.137 mmolCO2 min-1 cm-2 or 86.7 kgCO2 day-1 m-2), high Faradaic efficiencies (>90% based on carbonate), high carbon-removal efficiency (>98%) in simulated flue gas and low energy consumption (starting from about 150 kJ per molCO2) were demonstrated in our carbon-capture solid-electrolyte reactor, suggesting promising practical applications.

A multifunctional copper single-atom electrocatalyst aerogel for smart sensing and producing ammonia from nitrate.

Despite modern chemistry's success in providing affordable fertilizers for feeding the population and supporting the ammonia industry, ineffective nitrogen management has led to pollution of water resources and air, contributing to climate change. Here, we report a multifunctional copper single-atom electrocatalyst-based aerogel (Cu SAA) that integrates the multiscale structure of coordinated single-atomic sites and 3D channel frameworks. The Cu SAA demonstrates an impressive faradaic efficiency of 87% for NH3 synthesis, as well as remarkable sensing performance with detection limits of 0.15 ppm for NO3- and 1.19 ppm for NH4+. These multifunctional features enable precise control and conversion of nitrate to ammonia in the catalytic process, facilitating accurate regulation of the ammonium and nitrate ratios in fertilizers. We thus designed the Cu SAA into a smart and sustainable fertilizing system (SSFS), a prototype device for on-site automatic recycling of nutrients with precisely controlled nitrate/ammonium concentrations. The SSFS represents a forward step toward sustainable nutrient/waste recycling, thus permitting efficient nitrogen utilization of crops and mitigating pollutant emissions. This contribution exemplifies how electrocatalysis and nanotechnology can be potentially leveraged to enable sustainable agriculture.

On-chip single-mode thin-film lithium niobate Fabry-Perot resonator laser based on Sagnac loop reflectors.

We demonstrate an on-chip single-mode Er3+-doped thin-film lithium niobate (Er:TFLN) laser which consists of a Fabry-Perot (FP) resonator based on Sagnac loop reflectors (SLRs). The fabricated Er:TFLN laser has a footprint of 6.5 mm × 1.5 mm with a loaded quality (Q) factor of 1.6 × 105 and a free spectral range (FSR) of 63 pm. We generate the single-mode laser at 1544 nm wavelength with a maximum output power of 44.7 µW and a slope efficiency of 0.18%.

Factors influencing adolescent experimental and current smoking behaviors based on social cognitive theory: A cross-sectional study in Xiamen.

Introduction: China has the largest youth population in the world. To better implement the Smoke-free School Initiative, this study aims to examine the protective and risk factors for different smoking behaviors (never smoked, experimental smoking, and current smoking) among school adolescents based on social cognitive theory. Methods: This research was a secondary analysis of a cross-sectional survey of middle schools in Huli District of Xiamen, China. The final sample consisted of 1937 participants with an average age of 15.41 (SD = 1.64). Descriptive statistics were used to summarize the sociodemographic characteristics of the sample. Multivariate multinomial logistic regression analysis was performed using four models. Results: Of the respondents, 1685 (86.99%) were never smokers, 210 (10.84%) were experimental smokers, and 42 (2.17%) were current smokers. Social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies were associated with adolescents' smoking behaviors. The number of smoking family members, classmates smoking, the perception that smoking is cool and attractive, and attitudes toward control tobacco policies were the predictors of current smoking behavior (p < 0.05). In contrast, friends smoking and individual and social relationship motivation were associated with only experimental smoking (p < 0.05). Discussion: The relationship of social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies varied across smoking behaviors. Family, school, society and the government need to cooperate in prevention and intervention programs for adolescent smoking. The relationships between these factors and adolescents' different smoking behaviors needs to be further verified.

Carryover Contamination-Controlled Amplicon Sequencing Workflow for Accurate Qualitative and Quantitative Detection of Pathogens: a Case Study on SARS-CoV-2.

Carryover contamination during amplicon sequencing workflow (AMP-Seq) put the accuracy of the high-throughput detection for pathogens at risk. The purpose of this study is to develop a carryover contaminations-controlled AMP-Seq (ccAMP-Seq) workflow to enable accurate qualitative and quantitative detection for pathogens. By using the AMP-Seq workflow to detect SARS-CoV-2, Aerosols, reagents and pipettes were identified as potential sources of contaminations and ccAMP-Seq was then developed. ccAMP-Seq used filter tips and physically isolation of experimental steps to avoid cross contamination, synthetic DNA spike-ins to compete with contaminations and quantify SARS-CoV-2, dUTP/uracil DNA glycosylase system to digest the carryover contaminations, and a new data analysis procedure to remove the sequencing reads from contaminations. Compared to AMP-Seq, the contamination level of ccAMP-Seq was at least 22-folds lower and the detection limit was also about an order of magnitude lower-as low as one copy/reaction. By testing the dilution series of SARS-CoV-2 nucleic acid standard, ccAMP-Seq showed 100% sensitivity and specificity. The high sensitivity of ccAMP-Seq was further confirmed by the detection of SARS-CoV-2 from 62 clinical samples. The consistency between qPCR and ccAMP-Seq was 100% for all the 53 qPCR-positive clinical samples. Seven qPCR-negative clinical samples were found to be positive by ccAMP-Seq, which was confirmed by extra qPCR tests on subsequent samples from the same patients. This study presents a carryover contamination-controlled, accurate qualitative and quantitative amplicon sequencing workflow that addresses the critical problem of pathogen detection for infectious diseases. IMPORTANCE Accuracy, a key indicator of pathogen detection technology, is compromised by carryover contamination in the amplicon sequencing workflow. Taking the detection of SARS-CoV-2 as case, this study presents a new carryover contamination-controlled amplicon sequencing workflow. The new workflow significantly reduces the degree of contamination in the workflow, thereby significantly improving the accuracy and sensitivity of the SARS-CoV-2 detection and empowering the ability of quantitative detection. More importantly, the use of the new workflow is simple and economical. Therefore, the results of this study can be easily applied to other microorganism, which has great significance for improving the detection level of microorganism.

Wavelength-Tunable Narrow-Linewidth Laser Diode Based on Self-Injection Locking with a High-Q Lithium Niobate Microring Resonator.

We demonstrate a narrow linewidth 980 nm laser by self-injection locking of an electrically pumped distributed-feedback (DFB) laser diode to a high quality (Q) factor (>105) lithium niobate (LN) microring resonator. The lithium niobate microring resonator is fabricated by photolithography-assisted chemo-mechanical etching (PLACE) technique, and the Q factor of lithium niobate microring is measured as high as 6.91 × 105. The linewidth of the multimode 980 nm laser diode, which is ~2 nm measured from its output end, is narrowed down to 35 pm with a single-mode characteristic after coupling with the high-Q LN microring resonator. The output power of the narrow-linewidth microlaser is about 4.27 mW, and the wavelength tuning range reaches 2.57 nm. This work explores a hybrid integrated narrow linewidth 980 nm laser that has potential applications in high-efficient pump laser, optical tweezers, quantum information, as well as chip-based precision spectroscopy and metrology.