Results 191 to 200 of about 3,046,793 (299)

How Much Physics Should a Neural Network Know? Thermodynamics‐Informed Neural Networks for Rock Constitutive Modeling With Epistemic Uncertainty

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Machine learning offers a flexible route to constitutive modeling, with two emergent questions for geoscience applications: what level of thermodynamic constraint should be embedded in the network architecture, and how should predictive uncertainty be quantified when extrapolating from laboratory to field conditions? We address both challenges
Kangan Li, Tushar Mittal, Benjamin K. Holtzman, Seth Saltiel   +3 more
wiley   +1 more source

Visualizing interfacial thermal resistance in two-dimensional material-polymer composites from measurement to mechanistic understanding. [PDF]

Sci Adv
Li Z, Zhang X, Liu J, Miao R, Zhang G, Kong S, Sun M, Wang J, Chen J, Shi X.   +9 more
europepmc   +1 more source

ML‐Accelerated Framework for Fatigue Life‐Timescale Homogenization and Cyclic Damage Evolution Under Physics Constraints

International Journal for Numerical Methods in Engineering, Volume 127, Issue 17, 15 September 2026.
ABSTRACT Predicting structural lifetime under complex loading remains a major challenge in computational mechanics, especially for high cycle fatigue in large scale systems such as aircraft, bridges, and wind turbines. This difficulty arises from the need to capture fatigue damage accumulation, crack initiation, crack growth across scales, and life ...
Elsayed S. Elsayed, Abedulgader Baktheer, Fadi Aldakheel   +2 more
wiley   +1 more source

Characterization of Silicon-Membrane TES Microcalorimeters for Large-Format X-ray Spectrometers with Integrated Microwave SQUID Readout. [PDF]

IEEE Trans Appl Supercond
Roy A, Singh R, Weber JC, Doriese WB, Gard J, Keller MW, Mates JAB, Morgan KM, Ortiz NJ, Swetz DS, Schmidt DR, Ullom JN, Jahrman EP, Allison TC, Jamnuch S, Vinson J, Titus CJ, Jaye C, Fischer DA, O'Neil GC.   +19 more
europepmc   +1 more source

Detection Techniques for Polycyclic Aromatic Hydrocarbons and Their Metabolites: A Review

physica status solidi (a), Volume 223, Issue 17, 9 September 2026.
Overview of the different techniques that can be used to detect polyclic aromatic hydrocarbons and their metabolites. Polycyclic aromatic hydrocarbons (PAHs) are a class of organic pollutants affecting the environment as well as individual health that has been linked to various diseases including cancer.
Martin Wolfgang Konrad, Jeroen Vanoirbeek, Patrick Wagner, Irene Taurino   +3 more
wiley   +1 more source

DEEP INELASTIC SCATTERING [PDF]

, 2000
openaire   +2 more sources

Tuning perovskite recombination by hydrogen interstitial oxidation state. [PDF]

RSC Adv
Huang Y, Zhou R, Chen X, Zhou W, Yan H, Zheng Z.   +5 more
europepmc   +1 more source

Numerical Investigation on Thermal Fluid Flow-Induced Porosity During EBW of Aluminum Alloy. [PDF]

Materials (Basel)
Zeng R, Song D, Cui H, Wang T.
europepmc   +1 more source

Future Perspective of Muons: A Quantum Particle Measuring Quantum Processes. [PDF]

ACS Omega
Berlie A, Biswas S, Louat A, Stewart R, Wilkinson J.   +4 more
europepmc   +1 more source

Chemical Control of Space Charge Barriers and Grain Boundary Resistances in Polycrystalline Ionic Conductors

Advanced Functional Materials, Volume 36, Issue 74, 14 September 2026.
Grain boundaries (GBs) in polycrystalline materials often block charge transport and drive degradation. Using Gd‐doped CeO2 as a model electrolyte used in fuel/electrolysis cells, we developed a core‐shell infiltration method to selectively modify GB chemistry and space charge potential, achieving orders‐of‐magnitude ionic conductivity changes.
Z. Sha, T. Defferriere, C. Gilgenbach, J. M. LeBeau, I. Lubomirsky, H. L. Tuller   +5 more
wiley   +1 more source