Results 161 to 170 of about 6,815,752 (285)

Accelerated Materials Discovery Through In Situ X‐ray Diffraction: Solvothermal Formation of PdxMy (M═Si, Ge, Sn, Pb) Intermetallic Nanoparticles

Advanced Materials, EarlyView.
In situ PXRD data on solvothermal reactions accelerate materials discovery while simultaneously providing fundamental insights into complex crystal formation processes. Using PdxMy (M = Si, Ge, Sn, Pb) as an example, a general formation mechanism is identified, and specific synthesis strategies for ex situ preparation of SnPd2, Sn13Pd20, and SnPd ...
Anders Bæk Borup, Bo Brummerstedt Iversen   +1 more
wiley   +1 more source

Machine learning-based prediction of postoperative venous thromboembolism in orthopedic surgery using the MIMIC-IV database and external validation. [PDF]

Front Surg
Wu G, Cai G, Wu G, Zhu M, Guo J.
europepmc   +1 more source

Phase‐Engineered MoS2 Quantum Monolayer Catalysts

Advanced Materials, EarlyView.
A new type of catalyst model—phase‐engineered MoS2 quantum‐monolayer catalyst (∼0.8 nm thick, < 6 nm in the lateral size; switchable freely among metallic 1T, semiconducting 2H, and a hybrid phase of metallic‐semiconducting 1T‐2H)—is reported. It can efficiently and stably drive photochemical H2, syngas and ammonia synthesis as a catalyst or co ...
Ruijie Yang, Yingying Fan, Lillian Pernitsky, Mojtaba Ebrahimian Mashhadi, Ningxin Chen, Md. Mehadi Hassan, Zheng Li, Heng Zhao, Liang Mei, Zhiyuan Zeng, Zhangxing Chen, Jinguang Hu, Qingye Lu   +12 more
wiley   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Cross-Alloy Transferability of Spindle-Synchronous Vibration Signatures in CNC Milling Using Physics-Informed Autospectrum Features. [PDF]

Materials (Basel)
İşci M.
europepmc   +1 more source

GaSex Nanoparticles Modulate Neutrophil Function and Mitigate NET‐Driven Osteogenic Impairment in Osteomyelitis Therapy

Advanced Materials, EarlyView.
Neutrophil extracellular traps (NETs) emerge as a critical repair‐limiting factor in osteomyelitis, driving osteoblast mitochondrial dysfunction and excessive PINK1/Parkin‐mediated mitophagy. Gallium–selenium nanoparticles (GaSex) scavenge reactive oxygen species, redirect neutrophils from NETosis toward bactericidal phagocytosis, eliminate methicillin‐
Kai Ye, Xuanzhe Liu, Zifan Pei, Chenyi Jiang, Xiaofen Zhang, Lin Lin, Qihang Fang, Binyu Chen, Longxiang Shen, Liang Cheng, Peng Ding, Xianyou Zheng   +11 more
wiley   +1 more source

Deconstructing Risk: A Machine Learning-Guided Logistic Regression Model for Predicting Early Mucosal Edema Following Prophylactic Ileostomy in Elderly Rectal Cancer Patients. [PDF]

Int J Gen Med
Zeng Y, Bao L, Li J, Hong Y.
europepmc   +1 more source

Mapping Correlated Environmental Landscapes in the Fluorescence Response of a Pyrenylated Charge‐Transfer Probe via Data‐Driven Nonlinear Regression

Advanced Materials Interfaces, EarlyView.
A pyrenylated donor–acceptor probe exhibits environment‐dependent fluorescence governed by intramolecular charge transfer, restricted molecular motion, and supramolecular organization. Nonlinear regression accurately reconstructs fluorescence responses to viscosity, temperature, concentration, and pH, while correlated parameter maps reveal hidden ...
Harshal V. Barkale, Anakhi Hazarika, Nilanjan Dey   +2 more
wiley   +1 more source

A Hybrid and Comparative Machine Learning Framework for Predicting Gestational Diabetes Mellitus via a Prospective Case-Control Design: A Pilot Study Integrating Periodontal Health and Hematological Inflammatory Markers. [PDF]

Metabolites
Temur İ, Özsan M, Temur KT, Çolak AB.
europepmc   +1 more source

Reducing Interfacial Separation Force in High‐Speed Constrained‐Surface Projection Stereolithography Using a Dual‐Modulus Silicone Release Film

Advanced Materials Interfaces, EarlyView.
A dual‐modulus silicone release film creates distributed stress concentrations at high‐/low‐modulus boundaries, triggering multi‐site crack initiation and rapid interfacial detachment. The architecture lowers the peak separation force by 97.6%, shortens detachment time, and enables stable continuous projection stereolithography at 720 mm h−1, offering ...
Xiaogang Li, Xiaoqing Kang, Hong Xiao, Yugang Duan   +3 more
wiley   +1 more source