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Exploring the extraordinary optoelectronic properties of two‐dimensional (2D) materials to construct advanced optoelectronic devices is a major goal for academic researchers and industrialists. Emerging 2D Janus materials are the innovative class of 2D materials in which two sides are either asymmetrical functionalized or exposed to different environments. Distinctive features of Janus 2D materials such as tunable bandgaps, electronic structures, the presence of Rashba effects, excitonic effects, piezoelectric effects etc. make its magnificent candidates for optoelectronic devices. The van der Waals (vdWs) heterostructure with novel properties assembled by Janus 2D materials and low dimensional materials provides new opportunities and promising applications. This review aims to offer the recent advances in the Janus 2D materials and inside mechanism in 2D Janus vdWs heterostructure from an optoelectronics point of view. Here, the latest progress in the Janus 2D materials including their vdWs heterostructures from the perspective of theoretical prediction, and synthesis techniques is presented. The investigation of their physical optoelectronics properties and optoelectronic device applications is summarized. Finally, the future directions, challenges, and opportunities regarding the research process of Janus 2D materials and their vdWs heterostructure are discussed for designing promising optoelectronic devices. [ABSTRACT FROM AUTHOR]

Covalent polymerization of organic molecules into crystalline one‐dimensional (1D) polymers is effective for achieving desired thermal, optical, and electrical properties, yet it remains a persistent synthetic challenge for their inherent tendency to adopt amorphous or semicrystalline phases. Here we report a strategy to synthesize crystalline 1D covalent organic frameworks (COFs) composing quasi‐conjugated chains with benzoxazine linkages via the one‐pot Mannich reaction. Through [4+2] and [2+2] type Mannich condensation reactions, we fabricated stoichiometric and sub‐stoichiometric 1D covalent polymeric chains, respectively, using doubly and singly linked benzoxazine rings. The validity of their crystal structures has been directly visualized through state‐of‐the‐art cryogenic low‐dose electron microscopy techniques. Post‐synthetic functionalizations of them with a chiral MacMillan catalyst produce crystalline organic photocatalysts that demonstrated excellent catalytic and recyclable performance in light‐driven asymmetric alkylation of aldehydes, affording up to 94 % enantiomeric excess [ABSTRACT FROM AUTHOR]

A novel benzothiadiazole-based donor-acceptor type polymer, resistive random access memory (RRAM) material, poly{[4,4'-(2,7-diphenyl-9H-fluorene-9,9-diyl)bis(N,N-diphenylaniline)]-alt-[4,7-bis(4-dodecyl-5-vinylthiophen-2- yl)benzo[c][1,2,5] thiadiazole]} (PFVT) was synthesized. By using PFVT as the active layer, the as-fabricated electronic device with a configuration of Al/PFVT/ITO (ITO: indium tin oxides) exhibites a nonvolatile RRAM performance. During 50 consecutive cycle-to-cycle measurements, the observed average switch-on voltage, switch-off voltage and ON/OFF current ratio are (−0.54 ± 0.01) V, (2.42 ± 0.05) V, and 1.5×10³, respectively. The cycle-to-cycle variation for the programming voltage is less than 2.1%, suggesting excellent reliability. After thermal annealing at 200 ℃, the switch-on and switch-off voltages decrease to (−0.49±0.01) V and (2.27±0.02) V, respectively, due to the enhanced material crystallinity. The switching mechanism can be assigned to the intramolecular charge-transfer occurred in the materials system. The ON and OFF-state currents can be fitted by the Ohmic current model and space-charge-limited current model, respectively. The switchon voltage is highly associated with the bandgap of the materials. For comparison purpose, 4,4′-(2,7-diphenyl-9H-fluorene-9,9- diyl)bis(N,N-diphenylaniline) was replaced with phenyl group to synthesize poly[4-(4-dodecyl-5-((E)-4- methylstyryl)thiophen-2-yl)-7-(4-dodecyl-5-((E)-prop-1-en-1-yl)thiophen-2-yl)benzo[c][1,2,5]thiadiazole](PPVT). In contrast to PFVT, PPVT also shows the similar RRAM performance, with a bigger switch-on voltage and a smaller ON/OFF current ratio. Replacement of bulky fluorene unit with phenyl unit leads to a sharp decrease in the thermal stability of the material and an increase in the bandgap. [ABSTRACT FROM AUTHOR]

Summary: Plasmas under atmospheric pressure offer a high-temperature environment for material synthesis, but electrode ablation compromises purity. Here, we introduce an atmospheric-pressure microwave plasma (AMP) operated without electrodes to overcome the existing limitations in pure material synthesis. The distribution of the electrostatic field intensity inside a waveguide during AMP excitation was examined via electrostatic field simulations. The lateral and radial gas temperature distributions were also studied using optical emission spectroscopy. The AMP exhibited a uniform ultrahigh temperature (9,000 K), a large volume (102–104 cm3), and a response time on the millisecond level. AMP efficiently synthesized silicon nanoparticles, graphene, and graphene@Si–Fe core-shell nanoparticles within tens of milliseconds, ensuring purity and size control. We propose the “heat impulse” metric for evaluating the plasma characteristics (na, Tg, and t) in material synthesis, extended to other high-temperature plasmas. AMP is compact, cost-effective, and easy to assemble, promising for eco-friendly mass production of pure materials.

Summary: This study presents a machine learning (ML) framework aimed at accelerating the discovery of multi-property optimized Fe-Ni-Co alloys, addressing the time-consuming, expensive, and inefficient nature of traditional methods of material discovery, development, and deployment. We compiled a detailed heterogeneous database of the magnetic, electrical, and mechanical properties of Fe-Co-Ni alloys, employing a novel ML-based imputation strategy to address gaps in property data. Leveraging this comprehensive database, we developed predictive ML models using tree-based and neural network approaches for optimizing multiple properties simultaneously. An inverse design strategy, utilizing multi-objective Bayesian optimization (MOBO), enabled the identification of promising alloy compositions. This approach was experimentally validated using high-throughput methodology, highlighting alloys such as Fe66.8Co28Ni5.2 and Fe61.9Co22.8Ni15.3, which demonstrated superior properties. The predicted properties data closely matched experimental data within 14% accuracy. Our approach can be extended to a broad range of materials systems to predict novel materials with an optimized set of properties.

Summary: A micro turbine engine’s thrust relies on combustion chamber efficiency, closely tied to the design of its evaporation tube. This study thoroughly investigates evaporation and atomization processes within the tube, introducing a pioneering bionic-inspired structure. Integrating a honeycomb sheet into the traditional tube, both configurations undergo a comparative analysis. Results show a direct correlation between elevated air temperatures and reduced fuel droplet diameters, leading to increased fuel evaporation rates. The bionic tube, with a 1mm-thick honeycomb sheet, 0.6 mm aperture diameter, and 3 sheets, significantly improves fuel droplet atomization and evaporation compared to the conventional design. This research holds broader significance in understanding and enhancing micro turbine engine performance.

Since their discovery in 2011, the number of research groups studying MXenes has increased exponentially. Despite so many groups focusing on MXenes, there still remains disagreement into fundamental MXene properties, such as conductivity and stability. The reason behind this is because MXenes are being treated as chemicals—not as materials. There is significant evidence that every step of the MXene production process affects their properties: Synthesis of the MAX precursor, etching MAX to synthesize MXene, delamination of the resultant MXene, and then consequent storage and processing. This complexity, even within one MXene composition, gives an unprecedented ability to tailor the properties to best fit their intended application, but only if the implications of each choice are well understood. Herein, these factors will be discussed, focusing on how each of these choices affects MXene defect density, surface chemistry, and morphology and then consequently their properties. [ABSTRACT FROM AUTHOR]

Diffractive optical neural networks (DONNs) are emerging as high‐throughput and energy‐efficient hardware platforms to perform all‐optical machine learning (ML) in machine vision systems. However, the current demonstrated applications of DONNs are largely image classification tasks, which undermine the prospect of developing and utilizing such hardware for other ML applications. Herein, the deployment of an all‐optical reconfigurable DONNs system for scientific computing is demonstrated numerically and experimentally, including guiding two‐dimensional quantum material synthesis, predicting the properties of two‐dimensional quantum materials and small molecular cancer drugs, predicting the device response of nanopatterned integrated photonic power splitters, and the dynamic stabilization of an inverted pendulum with reinforcement learning. Despite a large variety of input data structures, a universal feature engineering approach is developed to convert categorical input features to images that can be processed in the DONNs system. The results open up new opportunities for employing DONNs systems for a broad range of ML applications. [ABSTRACT FROM AUTHOR]

Diffractive optical neural networks (DONNs) are emerging as high‐throughput and energy‐efficient hardware platforms to perform all‐optical machine learning (ML) in machine vision systems. However, the current demonstrated applications of DONNs are largely image classification tasks, which undermine the prospect of developing and utilizing such hardware for other ML applications. Herein, the deployment of an all‐optical reconfigurable DONNs system for scientific computing is demonstrated numerically and experimentally, including guiding two‐dimensional quantum material synthesis, predicting the properties of two‐dimensional quantum materials and small molecular cancer drugs, predicting the device response of nanopatterned integrated photonic power splitters, and the dynamic stabilization of an inverted pendulum with reinforcement learning. Despite a large variety of input data structures, a universal feature engineering approach is developed to convert categorical input features to images that can be processed in the DONNs system. The results open up new opportunities for employing DONNs systems for a broad range of ML applications.

Abstract For pursuing the ambitious goals in the burgeoning electric vehicles, portable electronic devices, and energy storage sectors, Li‐ion batteries (LIBs) are considered as one of the most promising electrochemical power sources because of their high energy density and moderate cost. Particularly, the improvement of battery materials and recycling of spent LIBs are receiving great attention since the sustainable approaches for the synthesis, modification, and recycling of battery materials are the crucial factors to the successful large‐scale implementation of LIBs. In this regard, supercritical carbon dioxide (SC‐CO2), which possesses many merits, such as environmentally friendly, low‐cost, individual chemical environment, and especially its unique physical properties, has been employed as solvent and reaction medium in the synthesis and modification of diverse functional materials. In this review, we mainly aim at compiling the applications of SC‐CO2 technology in the synthesis and modification of electrode materials as well as the recycling of LIBs. First, the unique properties and principles of SC‐CO2 technology are highlighted. Second, the latest progresses of the electrode materials design and recycling with the assistance of SC‐CO2 technique are summarized. Finally, the challenges, future directions, and perspectives on the design and development of battery materials and battery recycling by SC‐CO2 technology are proposed.

Due to their unique combination of metallic- and ceramic-like properties, MAX phases have attracted a lot of attentions. By selectively etching A-site atoms, MXenes with unique two-dimensional structures can be potentially generated. Due to their extraordinary properties, MXenes have currently made their way to the forefront of various research areas including electronics, photonics and catalysis. Therefore, the development of novel synthesis strategies for MAX/MXene is a key issue for the further development of MAX/MXene. Distilling insights from scientific literatures could accelerate the exploration of novel synthesis recipes; however, manually extracting scattered information from thousands of journal articles is laborious. In this study, we present an annotated corpus incorporating domain knowledge about MAX/MXene synthesis processes, deriving from experimental sections within 110 papers on MAX/MXene research; and based on that, a baseline model (including named entity recognition (NER) and relation extraction (RE) parts) is proposed for distilling information about MAX/MXene synthesis conditions from literatures using pre-trained natural language processing (NLP) models. We also demonstrate the efficacy of the proposed pipeline owning to the joint effort of domain knowledge (about MAX/MXene) and machine learning; where the entity recognition model possessing optimized setting could detect the entities with F1 score of 0.8452, and for relation extraction model with F1 score of 0.8476. It is hoped that the current work would provide an auxiliary for the future research and development of novel MAX/MXenes. In addition, the developed model could serve as a pre-trained model of MAX/MXenes synthesis routes extraction for future data augment.

Summary: Mixed-dimensional heterostructures have drawn significant attention due to their intriguing physical properties and potential applications in electronic and optoelectronic nanodevices. However, limited by the lattice matching, the preparation of heterostructures is experimentally difficult and the underlying growth mechanism has not been well established. Here, we report a three-step seeding epitaxial growth strategy for synthesizing mixed-dimensional heterostructures of one-dimensional microwire (MW) and two-dimensional atomic thin film. Our growth strategy has successfully realized direct epitaxial growth of WSe2 film on WOx MW and significantly improves the quality of the epitaxial WSe2 monolayer, which is evidenced by the remarkably enhanced photoluminescence (PL). More intriguingly, the as-synthesized WOx MWs exhibit a strong nonlinear optical response due to the enhancement effect of the core (WOx)-shell (WSe2) nanocavity. Our work provides a feasible route for direct growth of WOx-based mixed-dimensional heterostructures, which possess potential applications in high-performance optoelectronic devices.

Summary: Metal-organic frameworks (MOFs) are crystalline porous materials characterized by their high porosity and chemical tailorability. To realize the full potential of synthesized MOFs, it is important to transform them from crystalline solid powders into materials with integrated morphologies and properties. One promising approach is facet-controlled assembly, which involves arranging individual crystalline MOF particles into ordered macroscale structures by carefully controlling the interactions between particles. The resulting assembled MOF structures maintain the characteristics of individual particles while also exhibiting improved properties overall. In this article, we emphasize the essential concepts of MOF assembly, highlighting the impact of building blocks, surface interactions, and Gibbs free energy on the assembly process. We systematically examine three methods of guiding facet-controlled MOF assembly, including spontaneous assembly, assembly guided by external forces, and assembly through surface modifications. Lastly, we offer outlooks on future advancements in the fabrication of MOF-based material and potential application exploration.

Abstract Water constitutes the largest energy carrier on earth, absorbing more than 70% of the solar energy received by the earth's surface, yet its low exploitation has been a constant concern. The hydrovoltaic effect is an emerging technology that generates electricity through the direct interaction between nanomaterials and water of various forms (raindrops, waves, flows, moisture, and natural evaporation). Especially, the evaporation‐driven hydrovoltaic effect is a spontaneous and ubiquitous process that can directly convert thermal energy from the surrounding environment into electricity without the demand for additional mechanical work, which shows unique advantages compared with other hydrovoltaic effects. A variety of nanostructured materials have been steadily developed for evaporation‐driven hydrovoltaic devices (EHDs) in recent years. However, there has been a lack of a clear specification on the selection and design of materials for improving device performance. Herein, we first analyze the mechanisms of EHDs followed by a summarization of the recent advances in materials, including carbon materials, biomass‐based materials, metal oxides, composite materials, and others. We then discuss the strategies for improving the energy conversion efficiency and the output power in terms of structural design, surface modification, and interface treatment. Finally, we provide an outlook on the potential applications of electricity generation, sensors, and desalination technology, as well as the challenges and prospects for the development of this emerging technology in the future.

Summary: Certain types of face masks are highly efficient in protecting humans from bacterial and viral pathogens, and growing concerns with high safety, low cost, and wide market suitability have accelerated the replacement of reusable face masks with disposable ones during the last decades. However, wearing these masks creates countless problems associated with personnel comfort as well as more significant issues related to the cost of fabrication, the generation of medical waste, and environmental contaminants. In this work, we present a facile spray-pressing technique for the production of P-masks with a potential scale-up prospect by adding a graphene layer on one side of meltblown fabric and a functional layer on the other side. In principle, this technique could be easily integrated into the present automatic mask production process and the masks have self-cleaning and/or self-sterilizing properties when it is exposed to solar or simulated solar irradiation.

Summary: Sportswear worn next to the skin is easily soaked by sweat and may become a breeding ground for the microbiome, thus a source of malodor. Malodor can cause social embarrassment and discomfort to both wearer and others. Given the risks current deodorant products pose to nature and human life, the development of sustainable textiles for odor control comes to the forefront. This review introduces the odor-generating mechanism in clothing from the perspectives of perspiration composition and cutaneous microbiome. With the knowledge of the significant role of sweat in odor formation, the sweat distribution of the human body, measurement techniques, and advanced technologies developed for quick-dry function are presented in the second part. Lastly, odor management in sportswear is evaluated, covering the odor-assessing techniques, the effects of various textile materials, and emerging solutions in terms of antibacterial treatment, adsorbent materials, and photocatalytic degradations of odorous compounds. Overall, it is of both personal and social value to develop novel textile materials with odor-control functions by making use of natural materials and fabric designs.

The synthesis of advanced materials at high pressures has been an area of growing research interest for several decades. This article is the third in a three-part series that reviews Laser Materials Processing Within Diamond Anvil Cells (L-DACs). Part III focuses on the practice of Laser Reactive Synthesis Within Diamond Anvil Cells (LRS-DAC). During LRS-DAC processing, chemicals are precompressed within diamond anvil cells, then microscale chemical reactions are induced by focused laser beams. The method is distinguished from the well-known Laser-Heated Diamond Anvil Cell (LH-DAC) technique (see Part I) through the existence of chemical precursors (reactants), end-products, and quantifiable changes in chemical composition upon reaction. LRS-DAC processing provides at least three new degrees of freedom in the search for advanced materials (beyond adjusting static pressures and temperatures), namely: laser-excitation/cleavage of chemical bonds, time-dependent reaction kinetics via pulsed lasers, and pressure-dependent chemical kinetics. All of these broaden the synthetic phase space considerably. Through LRS-DAC experimentation, it is possible to obtain increased understanding of high-pressure chemical kinetics—and even the nature of chemical bonding itself. Here, LRS-DAC experimental methods are reviewed, along with the underlying chemistry/physics of high-pressure microchemical reactions. A chronology of key events influencing the development of LRS-DAC systems is provided, together with a summary of novel materials synthesised, and unusual chemical reactions observed. Current gaps in knowledge and emerging opportunities for further research are also suggested. [ABSTRACT FROM AUTHOR]

The emergence of two-dimensional (2D) layered materials with unique physiochemical properties and structure versatility has significantly boosted the development of gas sensing technology. This review paper explores recent advances in utilizing 2D materials, such as graphene, transition metal dichalcogenides (TMDs), black phosphorus, hexagonal boron nitride (h-BN), g-C 3 N 4 , MXenes, metal-organic frameworks (MOFs), and covalent organic frameworks (COFs), for field-effect transistor (FET) and chemiresistive gas sensors. In addition to the unique properties contributing to the sensing performance, the key aspects of synthesis methods, sensing mechanisms, and sensing performance of 2D materials are systematically elaborated. Furthermore, the review highlights recent progress in performance optimization through material functionalization, heterostructure design, and material systems hybridization. Potential solutions to the key challenges, including scalability, reproducibility, selectivity, and environmental stability, are addressed to unlock the full potential of 2D materials in gas-sensing applications. By comprehensively compiling state-of-the-art developments in 2D layered materials for gas sensing, this review provides critical insights into the evolving landscape of sensor technologies and inspires new strategies for addressing critical environmental and industrial challenges. [ABSTRACT FROM AUTHOR]

Summary: Developing active and cost-effective bifunctional electrocatalysts for overall water splitting is challenging but mandatory for renewable energy technologies. We report a high-entropy alloy (HEA) of PtIrCuNiCr as a bifunctional electrocatalyst for overall water splitting, which shows a low overpotential of ca. 190 mV at the current density of 10 mA cm−2. Compared with pure metals, HEAs exhibit remarkable surface strain due to severe lattice distortion in their crystal structures. Theoretical calculations reveal that the strain can regulate the binding energy of intermediates on catalysts by adjusting the metal-metal bonding energy. It pushes the HEA toward the top of volcano plots to achieve superior electrocatalytic activity for both hydrogen and oxygen evolution reactions. The strain effect of HEAs on electrocatalysis can be well engineered by tuning the catalyst radius or configurational entropy. This work renders a systematic strain regulation strategy for designing a high-performance HEA catalyst for overall water splitting.

Summary: Au-DNA self-assembled nanomachines can perform intelligent tasks such as sensing biomarkers and delivery of drug molecules through rational customization and programming. By virtue of their efficient signal amplification and flexible scalability, Au-DNA nanomachines have developed into one of the most promising nanodevices. In this review, we summarize the latest progress in Au-DNA self-assembled nanomachines for biosensing applications. First, the functional modules for building Au-DNA nanomachines are introduced. Subsequently, we summarize the biosensing applications of Au-DNA nanomachines with electrochemical or fluorescent signals as the output, respectively. Finally, we discuss the challenges and potential opportunities for Au-DNA nanomachines in biomedical applications.

Micro/nano metal–organic frameworks (MOFs) have attracted significant attention in recent years due to their numerous unique properties, with many synthetic methods and strategies being reported for constructing MOFs with specific micro/nano structures. In addition, the design of micro/nano MOFs for energy storage and conversion applications and the study of the structure–activity relationship have also become research hotspots. Herein, a comprehensive overview of the recent progress on micro/nano MOFs is presented. We begin with a brief introduction to the various synthesis methods for controlling the morphology of micro/nano MOFs. Subsequently, the structure-dependent properties of micro/nano MOFs as electrode materials or catalysts in terms of batteries, supercapacitors, and catalysis are discussed. Finally, the remaining challenges and future perspectives in this field are presented. Overall, this review is expected to inspire the design of advanced micro/nano MOFs for efficient energy storage and conversion technologies.

Magnesium and its alloys have become a great sparking topic of research due to their excellent biocompatible and biodegradable behavior. Magnesium and several biocompatible alloying elements were developed long back. The trends are to develop a surface composite of as-cast Mg alloys to control the degradation behavior. In this work, the surface composites of AZ31–TiO2 were developed by friction stir processing (FSP). The influence of spindle speed or tool rotation speed and number of processing passes on mechanical and microstructural performance were analyzed. The tool rotation speeds 720, 1050, 1550 and 2260RPM with pass 1, pass 2 and pass 3 were considered. The FSP workpiece was analyzed by microstructure and universal testing machine and the significant improvement in grain refinement and hardness was observed. [ABSTRACT FROM AUTHOR]

As a conjugated and unsymmetric building block composed of an electron‐poor seven‐membered sp2 carbon ring and an electron‐rich five‐membered carbon ring, azulene and its derivatives have been recognized as one of the most promising building blocks for novel electronic devices due to its intrinsic redox activity. By using 1,3,5‐tris(4‐aminophenyl)‐benzene and azulene‐1,3‐dicarbaldehyde as the starting materials, an azulene(Azu)‐based 2D conjugated covalent organic framework, COF‐Azu, is prepared through liquid‐liquid interface polymerization strategy for the first time. The as‐fabricated Al/COF‐Azu/indium tin oxide (ITO) memristor shows typical non‐volatile resistive switching performance due to the electric filed induced intramolecular charge transfer effect. Associated with the unique memristive performance, a simple convolutional neural network is built for image recognition. After 8 epochs of training, image recognition accuracy of 80 % for a neutral network trained on a larger data set is achieved. [ABSTRACT FROM AUTHOR]

How to erase sensitive data stored on memory devices quickly in an emergency has become a critical issue that needs to be addressed. Using BP‐BIBB as a key template for atom transfer radical polymerization, which is prepared by the reaction of p‐hydroxyphenyl‐functionalized black phosphorous nanosheets (C6H4OH‐BP) with 2‐bromoisobutyryl bromide (BIBB), a highly soluble poly[4‐(4‐(3,3,4,4,5,5‐hexafluoro‐2‐(2‐methyl‐5‐phenylthiophen‐3‐yl)cyclopent‐1‐en‐1‐yl)‐5‐methylthiophen‐2‐yl)phenyl methacrylate] (PHPM)‐covalently grafted BP derivative, hereafter abbreviated as PHPM‐g‐BP, is synthesized in situ. PHPM is a typical photochromic polymer that emits blue light under UV irradiation, while showing pale yellow under visible light illumination. By using PHPM‐g‐BP as an active layer, an as‐fabricated transient optoelectronic memory device exhibits a nonvolatile rewritable memory effect under UV irradiation, with an ON/OFF current ratio of 3.6 × 103, a turn‐on voltage of 1.60 V, and a turn‐off voltage of −1.41 V. Upon visible light illumination for 10 s, all the information stored in the device is erased quickly. The observed device current drops down from 10−3 to 10−8 A rapidly. [ABSTRACT FROM AUTHOR]

Summary: Although it has been shown that configurational entropy can improve the structural stability in transition metal oxides (TMOs), little is known about the oxidation state of transition metals under random mixing of alloys. Such information is essential in understanding the chemical reactivity and properties of TMOs stabilized by configurational entropy. Herein, utilizing electron energy loss spectroscopy (EELS) technique in an aberration-corrected scanning transmission electron microscope (STEM), we systematically studied the oxidation state of binary (Mn, Fe)3O4, ternary (Mn, Fe, Ni)3O4, and quinary (Mn, Fe, Ni, Cu, Zn)3O4 solid solution polyelemental transition metal oxides (SSP-TMOs) nanoparticles. Our findings show that the random mixing of multiple elements in the form of solid solution phase not only promotes the entropy stabilization but also results in stable oxidation state in transition metals spanning from binary to quinary transition metal oxide nanoparticles.

Abstract How to erase sensitive data stored on memory devices quickly in an emergency has become a critical issue that needs to be addressed. Using BP‐BIBB as a key template for atom transfer radical polymerization, which is prepared by the reaction of p‐hydroxyphenyl‐functionalized black phosphorous nanosheets (C6H4OH‐BP) with 2‐bromoisobutyryl bromide (BIBB), a highly soluble poly[4‐(4‐(3,3,4,4,5,5‐hexafluoro‐2‐(2‐methyl‐5‐phenylthiophen‐3‐yl)cyclopent‐1‐en‐1‐yl)‐5‐methylthiophen‐2‐yl)phenyl methacrylate] (PHPM)‐covalently grafted BP derivative, hereafter abbreviated as PHPM‐g‐BP, is synthesized in situ. PHPM is a typical photochromic polymer that emits blue light under UV irradiation, while showing pale yellow under visible light illumination. By using PHPM‐g‐BP as an active layer, an as‐fabricated transient optoelectronic memory device exhibits a nonvolatile rewritable memory effect under UV irradiation, with an ON/OFF current ratio of 3.6 × 103, a turn‐on voltage of 1.60 V, and a turn‐off voltage of −1.41 V. Upon visible light illumination for 10 s, all the information stored in the device is erased quickly. The observed device current drops down from 10−3 to 10−8 A rapidly.

Summary: Searching for an efficient, durable, and low cost catalyst toward oxygen reduction reaction (ORR) is of paramount importance for the application of fuel cell technology. Herein, PtFeCoNiCu high-entropy alloy nanoparticles (PFCNC-HEA) is reported as electrocatalyst toward ORR. It shows remarkable ORR catalytic mass activity of 1.738 A mg−1Pt at 0.90 V, which is 15.8 times higher than that of the state-of-art commercial Pt/C catalyst. It also exhibits outstanding stability with negligible voltage decay (3 mV) after 10k cycles accelerated durability test. High ORR activity is ascribed to the ligand effect caused by polymetallic elements, the optimization of the surface electronic structure, and the formation of multiple active sites on the surface. In the proton exchange membrane fuel cell setup, this cell delivers a power density of up to 1.380 W cm−2 with a cathodic Pt loading of 0.03 mgPt cm−2, demonstrating a promising catalyst design direction for highly efficient ORR.

Summary: The preparation technology of unconventional low-dimensional Cu2O monocrystals, which exhibit specific crystal planes and present significantly unique interfacial and physicochemical properties, is attracting increasing attention and interest. Herein, by integrating a high-temperature oxidation process under vacuum and a pure-water incubation process under ambient conditions, we propose the self-assembled growth and synthesis of quasi-two-dimensional Cu2O monocrystals on reduced graphene oxide (rGO) membranes. The prepared Cu2O crystals have a single (110) crystal plane, regular rectangular morphology, and potentially well conductivity. Experimental and theoretical results suggest that this assembly is attributed to the pre-nucleation clusters aggregation and directional attachment of Cu and O on the rGO membranes in aqueous environment and cation-π interactions between the (110) crystal plane of Cu2O and rGO surface. Our findings offer a potential avenue for the discovery and design of advanced low-dimensional single-crystal materials with specific interfacial properties in a pure aqueous environment.