Results 91 to 100 of about 23,300 (197)

Nonlinear stochastic modelling with Langevin regression. [PDF]

Proc Math Phys Eng Sci, 2021
Callaham JL, Loiseau JC, Rigas G, Brunton SL.   +3 more
europepmc   +1 more source

Transient modeling of extraction columns: Parameter estimation, uncertainty analysis, and operation optimization

AIChE Journal, EarlyView.
Abstract Despite extensive modeling efforts in extraction research, transient column models are rarely applied in industry due to concerns regarding parameter identifiability and model reliability. To address this, we analyzed uncertainty propagation from estimated parameters in a previously introduced column model and assessed identifiability via ill ...
Andreas Palmtag, Jannik Dohmen, Andreas Jupke   +2 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Flexible Memory: Progress, Challenges, and Opportunities

Advanced Intelligent Discovery, EarlyView.
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan, Sen Chen, Minghui Guo, Ziliang Cui, Yujie Du, Jing Liu   +5 more
wiley   +1 more source

Investigating various nonlinear vibration problems using VIBRANT: A tool based on Abaqus and Python. [PDF]

PLoS One
Tüfekci M, Sevencan F, Yurdakul O.
europepmc   +1 more source

Accelerating Surface Composition Characterization of Thin‐Film Materials Libraries Using Multi‐Output Gaussian Process Regression

Advanced Intelligent Discovery, EarlyView.
To integrate surface analysis into materials discovery workflows, Gaussian process regression is used to accurately predict surface compositions from rapidly acquired volume composition data (obtained by energy‐dispersive X‐ray spectroscopy), drastically reducing the number of required surface measurements on thin‐film materials libraries.
Felix Thelen, Florian Lourens, Alfred Ludwig   +2 more
wiley   +1 more source

Soliton-like coherent structures: a key to opening the door to turbulence. [PDF]

Natl Sci Rev
Chen S, Deng X, Lee C.
europepmc   +1 more source

Scattering of guided waves propagating through pipe bends based on normal mode expansion. [PDF]

Sci Rep, 2022
Wu W, Dong H, Zhang S.
europepmc   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Can de Broglie-Bohm Mechanics Be Considered Complete? [PDF]

Entropy (Basel)
Drezet A, Amblard A.
europepmc   +1 more source