Results 191 to 200 of about 5,510,773 (262)

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

open access: yesAIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho   +4 more
wiley   +1 more source

Spectral Tuning of Hyperbolic Shear Polaritons in Monoclinic Gallium Oxide via Isotopic Substitution. [PDF]

open access: yesAdv Mater
Carini G   +28 more
europepmc   +1 more source

Asking the 5 W's for designing next‐generation bioprocessing

open access: yesAIChE Journal, EarlyView.
Abstract Biotechnology is expanding beyond traditional, centralized fermentation and toward next‐generation bioprocessing paradigms that emphasize flexible deployment outside the laboratory with application‐specific performance. However, many bioprocesses fail to translate beyond proof‐of‐concept into industrially viable systems because early design ...
Sangdo Yook   +4 more
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

open access: yesAdvanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour   +5 more
wiley   +1 more source

Mode conversion of hyperbolic phonon polaritons in van der Waals terraces. [PDF]

open access: yesNat Commun
Noh BI   +9 more
europepmc   +1 more source

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender   +2 more
wiley   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

open access: yesAdvanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam   +5 more
wiley   +1 more source

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