Entropy engineering has emerged as a promising paradigm for tailoring the electronic and photoelectric properties of materials. Although high-entropy transition metal sulfides have been achieved, entropy engineering in 2D tellurides remains challenging. In this work, we report the successful synthesis of a 1T' monolayer heptanary medium-entropy (ME) alloy (Mo_aW_bFe_cCo_dS_xSe_yTe_z) via a one-step chemical vapor deposition method. Advanced characterizations, including scanning transmission electron microscopy, energy dispersive X-ray spectroscopy and electron energy loss spectroscopy confirm the uniform atomic-level distribution of the seven constituent elements within the alloy. The 1T' ME alloy device exhibits a high drain current of ~ 6.5 mA, which is 216 times higher than the ~ 30 μA observed in pristine 1T' MoTe₂. Furthermore, the 1T' ME alloy photodetector exhibits responsivities of 27.92 A/W at 1064 nm and 63.74 A/W at 1550 nm, outperforming those of the pristine 1T' MoTe₂ by more than two orders of magnitude. This remarkable enhancement is attributed to the reduced Schottky barrier (15.9 meV) at the 1T' ME alloy/electrode interface, along with the enhanced conductance (0.43 S) and reduced thermal activation energy (4.1 meV) in the 1T' ME alloy, collectively facilitating more efficient carrier injection and transport. Our work provides a distinct pathway for tailoring the properties of transition metal dichalcogenides through entropy engineering and offers valuable insights for the design of high-performance infrared photodetectors.

A new study examines the early impact of mandatory cybersecurity disclosure in the U.S. In their study, Associate Professor Elina Haapamäki from the University of Vaasa and Associate Professor Jukka Sihvonen from Aalto University School of Business analysed how U.S. public companies responded to the disclosure requirement that came into force in 2023. Research shows that mandatory cybersecurity disclosure does not prompt reactions from investors or stock analysts. Instead, the main benefits appear to materialise within firms themselves. The requirement forces organisations to document cybersecurity responsibilities, processes, and decision-making more systematically.

Hypervision Surgical (HVS), a pioneer in real-time hyperspectral imaging for surgery has announced the closure of its Series A financing round after successfully raising £17 million to progress its UK-certified and FDA-cleared HYPERSNAP® system.

 

Hydrogels have been highlighted as effective wound dressings for tissue regeneration, while microbeads serve as versatile carriers for controlled drug release and targeted delivery, allowing customization for specific therapeutic needs. Ahmed, Guo and Huang et al. from Taiyuan University of Technology provide a comprehensive review published by Frontiers of Materials Science on microbeads-assisted antibacterial hydrogels for wound healing.

AI is rapidly entering classrooms worldwide, but current education governance models are not designed to manage its systemic impact. A new study argues that AI should be understood not merely as a teaching tool, but as a governance actor that reshapes authority, accountability, and professional autonomy in education systems. The article proposes a reconfigured hybrid governance framework to help education systems harness AI’s benefits while protecting democratic values, learner autonomy, and professional judgment.

The School Digital Renewal Process (SDRP) has evolved from infrastructure-focused adoption to deep pedagogical transformation centered on personalized, competence-based learning. Traditional indicators—such as device availability or connectivity—lose relevance at advanced SDRP stages. This article proposes a novel, evidence-based approach to constructing indicators that capture shifts in learning content and organization through automated analysis of schools’ digital footprints (publicly available digital materials) using AI tools. Drawing on Bloom’s Revised Taxonomy and empirical data from international schools, we demonstrate the feasibility of tracking second-order educational change without relying on teacher surveys. The framework supports comparative monitoring of digital transformation aligned with the demands of the AI era. The article introduces a groundbreaking innovation: the use of AI tools for gathering and analyzing indicators from publicly available digital sources in education institutions. This approach offers a scalable and cost-efficient way to track and evaluate SDRP at later stages of its development.