Results 151 to 160 of about 121,925 (266)

Encyclopedia of 2D β′‐In2Se3 Growth Using Chemical Vapor Deposition: The Effects of Synthesis Parameters Onto Material Quality

Advanced Engineering Materials, EarlyView.
A distinct semi‐confined inner‐tube chemical vapor deposition geometry enables reproducible, large‐area growth of phase‐pure 2D β′‐In2Se3 from InI + Se precursors. Engineering local vapor transport and optimizing precursor delivery and temperature–time conditions yield uniform continuous films.
Dasun P. W. Guruge, P. Sanju S. Panawala, Joseph F. S. Fernando, Zhenhuan Chen, Chao Zhang, Dong‐Chen Qi, Liangzhi Kou, Konstantin L. Firestein, Dmitri V. Golberg   +8 more
wiley   +1 more source

PruDensNet: a parameter efficient depthwise separable CNN for MRI-based brain tumor classification. [PDF]

Front Med (Lausanne)
Arman M, Samin A, Islam AKMM, Arnob MMR, Islam MJ, Mamoon IA.   +5 more
europepmc   +1 more source

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

Advanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele, Hossein Ipakchi, Tizazu H. Mekonnen   +2 more
wiley   +1 more source

Service-oriented vulnerability assessment for the larger-scale high speed railway infrastructure network: a case in China. [PDF]

Sci Rep
Zhang H, Xing H, Ma X, Jia L.
europepmc   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Advanced Electron Microscopy and Microcomputed Tomography Analysis of Single‐Crystal Ni‐Base Superalloys After Short‐Term Multiaxial Creep

Advanced Engineering Materials, EarlyView.
This work studies the anisotropic behavior of circular notched tensile specimens of Ni‐base superalloy single crystals during high‐temperature tensile creep along [001], [110], and [111]. Correlative scale‐bridging imaging of specimens reveals early rupture along [110] because 1) plastic deformation proceeds faster at notch center; 2) more (brittle ...
Leonardo Agudo Jácome, Lijie Cao, Christoph Somsen, Johannes Boes, René Hesse, Werner Theisen, Gunther Eggeler   +6 more
wiley   +1 more source

DOSET: dose optimization with simultaneous efficacy and toxicity evaluation, motivated by a first-in-human phase I CAR T lymphoma trial. [PDF]

ESMO Open
Hu X, Benjamin R, Graham C, Maher J, Yap C.   +4 more
europepmc   +1 more source

Influence of Scan Strategies in Electron Beam Powder Bed Fusion on Solidification, Microstructure, and High‐Temperature Compressive Properties of γ′‐Strengthened Inconel 738LC

Advanced Engineering Materials, EarlyView.
Experiments and thermophysical simulations were conducted to investigate the electron beam powder bed fusion electron beam (PBF‐EB/M) process for the γ′‐strengthened nickel‐based superalloy Inconel 738LC. The results demonstrate the impact of process‐induced microstructural variations on high‐temperature mechanical behavior, providing a basis for ...
Jan Niklas Petenati, Karthik Kumar Banku, Prasanth Bondi, Ivan Zhirnov, Yangyiwei Yang, Gordon Schmidt, Jürgen Christen, Georg Hasemann, Manja Krüger, Bai‐Xiang Xu, Bilal Gökce, Silja‐Katharina Rittinghaus   +11 more
wiley   +1 more source

Adaptive Multi-Wave Sampling for Efficient Chart Validation. [PDF]

Clin Epidemiol
Hahn G, Schneeweiss S, Wang SV.
europepmc   +1 more source

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

Advanced Engineering Materials, EarlyView.
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma, Sarath Menon, Fritz Körmann, Thomas Hammerschmidt, Ralf Drautz   +4 more
wiley   +1 more source