With high surface-to-volume ratio, the abundant surface states and high carrier concentration are challenging the near-infrared photodetection behaviors of narrow band gap semiconductors nanowires. In this study, the narrow band gap semiconductor of Bi2O2Se nanosheets (NSs) is adopted to construct mixed-dimensional heterojunctions with GaSb nanowires (NWs) for demonstrating the impressive self-powered NIR photodetection. Benefiting from the built-in electric field of ~ 140 meV, the as-constructed NW/NS mixed-dimensional heterojunction self-powered photodetector shows the low dark current of 0.07 pA, high I_light/I_dark ratio of 82 and fast response times of < 2/2 ms at room temperature. The self-powered photodetector performance can be further enhanced by fabricating the NW array/NS mixed-dimensional heterojunction by using a contact printing technique. The excellent photodetection performance promises the as-constructed NW/NS mixed-dimensional heterojunction self-powered photodetector in imaging and photocommunication.

Spina bifida is a serious congenital condition caused by abnormal neural tube development during early pregnancy. While folic acid supplementation has dramatically reduced its incidence, cases persist due to a complex interplay of genetic mutations and environmental exposures.

Alloying strategies have proven effective in enhancing the properties of metallic materials. However, conventional alloying strategies face significant limitations in preparing nanoscale multi-alloys and continuous optimizing surface-active sites. High-entropy alloys (HEAs) display a broader spectrum of unique properties due to their complex electron distribution and atomic-level heterogeneity arising from the stochastic mixing of multiple elements, which provides a diverse array of binding sites and almost continuous distribution of binding energies. This review aims to summarize recent research advancements in synthesis strategies and multi-field applications of nanoscale HEAs. It emphasizes several commonly employed synthesis strategies and significant challenges in synthesizing nanoscale HEAs. Finally, we present a comprehensive analysis of the advantages of HEAs for multi-field applications, emphasizing significant application trends related to nanosizing and multidimensionalization to develop more efficient nanoscale HEAs.

How do plants regenerate roots from scratch after being wounded? In this study, scientists used spatial transcriptomics and time-series gene expression analysis to trace poplar root regeneration from its earliest stages.

This study pioneers the integration of electrochemical neutralization energy (ENE) into the electrocatalytic methane conversion (EOM) electrolytic system through a pH-asymmetric electrolyzer design, converting chemical potential differences from industrial wastewater into reaction driving forces. By constructing an asymmetric acid/alkaline electrolyte environment (Figure 1), researchers achieve the first synergistic enhancement of EOM with the hydrogen evolution reaction (HER), overcoming traditional energy barriers (voltage reduction of 0.7 V). The NiO/Ni heterostructure catalyst delivers a liquid product yield of 2.7 mmol gNiO^–1 h^–1 under ambient conditions, with mechanistic studies confirming that dynamically formed Ni^III–O^Ÿ–Ni^III–O^– centers accelerate C–H bond cleavage. The system demonstrates exceptional stability (<2% voltage fluctuation over 48 h) in simulated industrial wastewater, concurrently producing high-value C3 oxygenates (>50% selectivity) and green hydrogen (>90% Faradaic efficiency). This breakthrough integrates methane valorization-wastewater treatment-green hydrogen production into a unified carbon-neutral pathway, highlighting significant energy and economic advantages while identifying enhanced methane-to-oxygenate efficiency as the key commercialization target. This innovative strategy offers a high-efficiency, low-energy, and cost-effective approach for distributed methane conversion and industrial wastewater valorization.

In the field of natural language processing, the rapid development of large language model (LLM) has attracted increasing attention. LLMs have shown a high level of creativity in various tasks, but the methods for assessing such creativity are inadequate. Assessment of LLM creativity needs to consider differences from humans, requiring multiple dimensional measurement while balancing accuracy and efficiency. This paper aims to establish an efficient framework for assessing the level of creativity in LLMs. By adapting the modified Torrance tests of creative thinking, the research evaluates the creative performance of various LLMs across 7 tasks, emphasizing 4 criteria including fluency, flexibility, originality, and elaboration. In this context, researchers develop a comprehensive dataset of 700 questions for testing and an LLM-based evaluation method. In addition, this study presents a novel analysis of LLMs′ responses to diverse prompts and role-play situations. Researchers found that the creativity of LLMs primarily falls short in originality, while excelling in elaboration. In addition, the use of prompts and role-play settings of the model significantly influence creativity. Additionally, the experimental results also indicate that collaboration among multiple LLMs can enhance originality. Notably, their findings reveal a consensus between human evaluations and LLMs regarding the personality traits that influence creativity. The findings underscore the significant impact of LLM design on creativity and bridge artificial intelligence and human creativity, offering insights into LLMs′ creativity and potential applications.