Results 11 to 20 of about 152 (143)
Graphene‐Based Wearable Textile Triboelectric Nanogenerators and Biomechanical Sensors
This study presents a wearable textile‐based triboelectric nanogenerator (T‐TENG) using sprayed graphene enhanced with a PVA adhesion layer. The graphene‐based electrode demonstrates high electrical conductivity and robustness to multiple bends. The fabricated T‐TENG provides stable and efficient output, with strong responsiveness to biomotion.
Hongyang Dang +4 more
wiley +1 more source
Laser‐induced graphene (LIG) provides a scalable, laser‐direct‐written route to porous graphene architecture with tunable chemistry and defect density. Through heterojunction engineering, catalytic functionalization, and intrinsic self‐heating, LIG achieves highly sensitive and selective detection of NOX, NH3, H2, and humidity, supporting next ...
Md Abu Sayeed Biswas +6 more
wiley +1 more source
The unique lamellar structure of the eutectic alloy promotes selective oxidation of Al initially, while lattice distortion‐induced diffusion suppression slows oxide growth during steady state. Combining these strategies, a Multi‐Principal Element Alloy with excellent oxidation resistance at 1200℃ was designed.
Xinyu Zhang +6 more
wiley +1 more source
Mechanism of Solid Solution‐Driven Texture Induced by Ag Doping in YBCO Superconductor
Ag‐doped YBCO with a designed concentration gradient is produced by dual‐material co‐extrusion and freeze‐drying. During annealing, Ag+ ions diffuse into Y123, substituting for Cu(1) and inducing c‐axis relaxation. This leads to the formation of [001]‐oriented YBCAO, creating a coherent interface that templates the textured growth of Y123. Consequently,
Fenyan Zhao +4 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
A lithium‐bearing slag is investigated with the goal of holistic valorization. The present β‐eucryptite (LiAlSiO4) exhibits a high lithium content and low levels of impurities. The spinel contains most of the chromium and vanadium, representing additional valorization opportunities.
Peter Cornelius Gantz +9 more
wiley +1 more source
Topological Materials and Related Applications
This review covers topological materials—including topological insulators, quantum valley Hall and quantum spin Hall insulators, and topological Weyl and Dirac semimetals—as well as their most recent advancements in fields such as spintronics, electronics, photonics, thermoelectrics, and catalysis.
Carlo Grazianetti +9 more
wiley +1 more source
This study establishes an in situ electrochemical framework using dense bulk electrodes to identify defect chemistry and surface kinetics. While oxygen vacancy concentration is derived via bias modulation, surface exchange coefficients are quantified at open circuit voltage conditions to isolate kinetics.
Taeyun Kim +5 more
wiley +1 more source
Graph‐based imitation and reinforcement learning for efficient Benders decomposition
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman +3 more
wiley +1 more source
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar +3 more
wiley +1 more source

