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Valleytronics, based on the valley degree of freedom rather than charge, is a promising candidate for next-generation information devices beyond complementary metal–oxide–semiconductor (CMOS) technology1–4. Although many intriguing valleytronic properties have been explored based on excitonic injection or the non-local response of transverse current schemes at low temperature4–7, demonstrations of valleytronic building blocks similar to transistors in electronics, especially at room temperature, remain elusive. Here, we report a solid-state device that enables a full sequence of generating, propagating, detecting and manipulating valley information at room temperature. Chiral nanocrescent plasmonic antennae8 are used to selectively generate valley-polarized carriers in MoS2 through hot-electron injection under linearly polarized infrared excitation. These long-lived valley-polarized free carriers can be detected in a valley Hall configuration9–11 even without charge current, and can propagate over 18 μm by means of drift. In addition, electrostatic gating allows us to modulate the magnitude of the valley Hall voltage. The electrical valley Hall output could drive the valley manipulation of a cascaded stage, rendering the device able to serve as a transistor free of charge current with pure valleytronic input/output. Our results demonstrate the possibility of encoding and processing information by valley degree of freedom, and provide a universal strategy to study the Berry curvature dipole in quantum materials.A MoS2 transistor with chiral nanocrescent plasmonic antennae enables the generation, propagation, detection and manipulation of valley information at room temperature.

Ultrathin silicon nanowires (diameter <30 nm) with strong electrostatic control are ideal quasi-1D channel materials for high-performance field effect transistors, while a short channel is desirable to enhance driving current. Typically, the patterning of such delicate channels relies on high-precision lithography, which is not applicable for large area electronics. In this work, we demonstrate that ultrathin and short silicon nanowires channels can be created through a local-curvature-modulated catalytic growth, where a planar silicon nanowires is directed to jump over a crossing step. During the jumping dynamic, the leading droplet undergoes significant stretching, producing a short necking segment of <100 nm in length, with a reduced diameter from approximately 45 nm to <25 nm. Compared to the FETs with uniform silicon nanowire channels, our step-necked silicon nanowire FETs exhibit substantially enhanced on/off current ratio I on/off  > 8 × 10 7 and a sharper subthreshold swing of 70 mV/dec, thanks to a stronger gating effect in the middle channel and markedly improved electric contacts at the thicker source/drain ends. These findings mark the pioneering experimental demonstration of catalytic growth acting as a deterministic fabrication method for precisely crafting engineered FET channels, ideally fitting the requirements of high-performance large-area displays and sensors. Ultrathin and short silicon nanowires are ideal for high-performance field effect transistors but require high-precision lithography. The authors use step-necking catalytic growth to create thick/thin/thick SiNW channels, ensuring efficient gate control and favorable electric contact.

Ultracompact and soft pairwise grippers, capable of swift large-amplitude multi-dimensional maneuvering, are widely needed for high-precision manipulation, assembly and treatment of microscale objects. In this work, we demonstrate the simplest construction of such robotic structures, shaped via a single-nanowire-morphing and powered by geometry-tailored Lorentz vectorial forces. This has been accomplished via a designable folding growth of ultralong and ultrathin silicon NWs into single and nested omega-ring structures, which can then be suspended upon electrode frames and coated with silver metal layer to carry a passing current along geometry-tailored pathway. Within a magnetic field, the grippers can be driven by the Lorentz forces to demonstrate swift large-amplitude maneuvers of grasping, flapping and twisting of microscale objects, as well as high-frequency or even resonant vibrations to overcome sticky van de Waals forces in microscale for a reliable releasing of carried payloads. More sophisticated and functional teamwork of mutual alignment, precise passing and selective light-emitting-diode unit testing and installation were also successfully accomplished via pairwise gripper collaborations. This single-nanowire-morphing strategy provides an ideal platform to rapidly design, construct and prototype a wide range of advanced ultracompact nanorobotic, mechanical sensing and biological manipulation functionalities. A single nanowire morphing strategy has been established to construct ultracompact soft robotic grippers, capable of large amplitude multi-dimensional maneuvering and dexterous manipulation of microscale objects, under swift Lorentz forces driving.

Highlights Crystalline silicon (c-Si) is one of the most mature and reliable materials for high-performance electronic devices and has garnered widespread attention in the field of flexible electronics. This article examines the detailed transition enabled by geometry engineering from \"3D bulk materials\" to \"2D thin films,\" and ultimately to \"1D nanowires,\" highlighting the advancements and challenges in enhancing the flexibility and mechanical properties of c-Si. We emphasize the forefront applications of silicon nanowires in wearable electronics and healthcare, aiming to accelerate the rapid development of c-Si within the realm of flexible electronics. Soft electronics, which are designed to function under mechanical deformation (such as bending, stretching, and folding), have become essential in applications like wearable electronics, artificial skin, and brain-machine interfaces. Crystalline silicon is one of the most mature and reliable materials for high-performance electronics; however, its intrinsic brittleness and rigidity pose challenges for integrating it into soft electronics. Recent research has focused on overcoming these limitations by utilizing structural design techniques to impart flexibility and stretchability to Si-based materials, such as transforming them into thin nanomembranes or nanowires. This review summarizes key strategies in geometry engineering for integrating crystalline silicon into soft electronics, from the use of hard silicon islands to creating out-of-plane foldable silicon nanofilms on flexible substrates, and ultimately to shaping silicon nanowires using vapor–liquid–solid or in-plane solid–liquid–solid techniques. We explore the latest developments in Si-based soft electronic devices, with applications in sensors, nanoprobes, robotics, and brain-machine interfaces. Finally, the paper discusses the current challenges in the field and outlines future research directions to enable the widespread adoption of silicon-based flexible electronics.

Background It’s widely acknowledged that students pursuing the Master of Nursing Specialist (MNS) degree must be equipped with adequate clinical competency to be qualified for clinical nursing practice. However, there is a lack of a clear definition for clinical competency and its primary components for MNS students. Hence, the purpose of this study is to explore and explain the clinical competencies of MNS students. Methods Purposive sampling was employed to select participants to participate in the semi-structured interviews. This study was conducted in 7 Chinese hospitals with 21 individuals (13 MNS graduates and 8 nursing experts). The concepts were derived from content analysis after recording and transcribing the interviews. Results For MNS students, the concept of clinical competency was multidimensional, with eleven main categories: evaluation and observation of the medical condition, prediction of disease progression, clinical operational skill, health education and health promotion, documentation of medical treatment and nursing records, communication and cooperation, administration, promotion of professional development, self-development, knowledge of law and ethics, and personal traits. Conclusion The present study examined the multifaceted nature of clinical competency for MNS students. Having a comprehensive understanding of its core components provides nursing educators with guidance in developing clinical competency training programs and enhancing the attainment of clinical competency among MNS students.

Social isolation and disability in performing activities of daily living are increasingly recognised as significant public health concerns globally. We aimed to investigate their bidirectional associations and the related temporal dynamics in Chinese older adults. We retrieved data from the six waves of the Chinese Longitudinal Healthy Longevity Survey (2002-18) and used generalised cross-lagged modelling (GCLM) to assess the bidirectional associations between social isolation and disability in performing activities of daily living. We found that higher levels of social isolation were predictive of increased scores in disabilities in performing activities of daily living. Conversely, disabilities in performing activities of daily living showed less predictive power in relation to social isolation. The temporal dynamics analysis indicated a peak in the bidirectional associations after approximately six years, followed by decreasing trends. Our results indicate that social isolation is dominant in the bidirectional relationship. Efforts focusing on reducing it can potentially minimise disabilities in performing activities of daily living among older adults. Reinstating preventive interventions beyond the six-year mark could help maintain their effectiveness.

Nanostructured cell culture substrates featuring nanowire (NW) arrays have been applied to a variety of basic cell lines and rodent neurons to investigate cellular behavior or to stimulate cell responses. However, patient-derived human neurons—a prerequisite for studying e.g. neurodegenerative diseases efficiently—are rarely employed due to sensitive cell culture protocols and usually long culturing periods. Here, we present human patient induced pluripotent stem cell-derived neurons cultured on densely-spaced spiky silicon NW arrays (600 NWs/ 100 µm 2 with NW lengths of 1 µm) which show mature electrophysiological characteristics after only 20 days of culturing. Exemplary neuronal growth and network formation on the NW arrays are demonstrated using scanning electron microscopy and immunofluorescence microscopy. The cells and neurites rest in a fakir-like settling state on the NWs only in contact with the very NW tips shown by cross-sectional imaging of the cell/NW interface using focused ion beam milling and confocal laser scanning microscopy. Furthermore, the NW arrays promote the cell culture by slightly increasing the share of differentiated neurons determined by the quantification of immunofluorescence microscopy images. The electrophysiological functionality of the neurons is confirmed with patch-clamp recordings showing the excellent capability to fire action potentials. We believe that the short culturing time to obtain functional human neurons generated from patient-derived neural progenitor cells and the robustness of this differentiation protocol to produce these neurons on densely-spaced spiky nanowire arrays open up new pathways for stem cell characterization and neurodegenerative disease studies.

Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are neurodegenerative disorders characterized by the accumulation of α-synuclein aggregates. α-synuclein forms droplets via liquid-liquid phase separation (LLPS), followed by liquid-solid phase separation (LSPS) to form amyloids, how this process is physiologically-regulated remains unclear. β-synuclein colocalizes with α-synuclein in presynaptic terminals. Here, we report that β-synuclein partitions into α-synuclein condensates promotes the LLPS, and slows down LSPS of α-synuclein, while disease-associated β-synuclein mutations lose these capacities. Exogenous β-synuclein improves the movement defects and prolongs the lifespan of an α-synuclein-expressing NL5901 Caenorhabditis elegans strain, while disease-associated β-synuclein mutants aggravate the symptoms. Decapeptides targeted at the α-/β-synuclein interaction sites are rationally designed, which suppress the LSPS of α-synuclein, rescue the movement defects, and prolong the lifespan of C. elegans NL5901. Together, we unveil a Yin-Yang balance between α- and β-synuclein underlying the normal and disease states of PD and DLB with therapeutical potentials. The authors report a Yin-Yang balance between α-Synuclein and β-Synuclein via regulating phase separation in physiological states and Parkinson’s disease. AI-designed peptides mitigate the symptoms and prolong the lifespan of C. elegans PD models.

•Participant dyads conducted a collective perceptual task.•Participants with similar abilities in a dyad achieved more collective benefit.•Dyads inclined the higher-able participant's decision as the collective one.•There were enhanced IBS at frontopolar, premotor areas, supramarginal gyri, etc.•As the dyad's inclination increased, the IBS might decrease, and potentially leading to an improved collective benefit. People perform better collectively than individually, a phenomenon known as the collective benefit. To pursue the benefit, they may learn from previous behaviors, come to know whose initial opinion should be valued, and develop the inclination to take it as the collective one. Such learning may affect interpersonal brain communication. To test these hypotheses, this study recruited participant dyads to conduct a perceptual task on which they made individual decisions first and then the collective one. The enhanced interpersonal brain synchronization (IBS) between participants was explored when individual decisions were in disagreement vs. agreement. Computational modeling revealed that participant dyads developed the dyad inclination of taking the higher-able participants', not the lower-able ones' decisions as their collective ones. Brain analyses unveiled the enhanced IBS at frontopolar areas, premotor areas, supramarginal gyri, and right temporal-parietal junctions. The premotor IBS correlated negatively with dyad inclination and collective benefit in the absence of correction. The Granger causality analyses further supported the negative relation of dyad inclination with inter-brain communication. This study highlights that dyads learn to weigh individuals' decisions, resulting in dyad inclinations, and explores associated inter-brain communication, offering insights into the dynamics of collective decision-making.

Highlights The latest advancements in the application of machine learning (ML) for the screening of solid-state battery materials are reviewed. The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. Future challenges and perspectives of artificial intelligence in solid-state battery are discussed. Solid-state batteries are widely recognized as the next-generation energy storage devices with high specific energy, high safety, and high environmental adaptability. However, the research and development of solid-state batteries are resource-intensive and time-consuming due to their complex chemical environment, rendering performance prediction arduous and delaying large-scale industrialization. Artificial intelligence serves as an accelerator for solid-state battery development by enabling efficient material screening and performance prediction. This review will systematically examine how the latest progress in using machine learning (ML) algorithms can be used to mine extensive material databases and accelerate the discovery of high-performance cathode, anode, and electrolyte materials suitable for solid-state batteries. Furthermore, the use of ML technology to accurately estimate and predict key performance indicators in the solid-state battery management system will be discussed, among which are state of charge, state of health, remaining useful life, and battery capacity. Finally, we will summarize the main challenges encountered in the current research, such as data quality issues and poor code portability, and propose possible solutions and development paths. These will provide clear guidance for future research and technological reiteration.