AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
The origin and evolution of open habitats in North America inferred by Bayesian deep learning models. [PDF]
Nat Commun, 2022 Andermann T +3 more
europepmc +1 more source
Advanced 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
Patient-specific uncertainty and bias quantification of non-transparent convolutional neural network model through knowledge distillation and Bayesian deep learning. [PDF]
Proc SPIE Int Soc Opt Eng, 2023 Gong H +5 more
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir +4 more
wiley +1 more source
Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning. [PDF]
Nat Commun, 2021 Leitherer A, Ziletti A, Ghiringhelli LM.
europepmc +1 more source
The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers
Advanced Intelligent Discovery, EarlyView.We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen +6 more
wiley +1 more source
The MindGomoku: An Online P300 BCI Game Based on Bayesian Deep Learning. [PDF]
Sensors (Basel), 2021 Li M +6 more
europepmc +1 more source
A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction
Advanced Intelligent Discovery, EarlyView.This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai +8 more
wiley +1 more source
Attenuation Coefficient Estimation for PET/MRI With Bayesian Deep Learning Pseudo-CT and Maximum-Likelihood Estimation of Activity and Attenuation. [PDF]
IEEE Trans Radiat Plasma Med Sci, 2022 Leynes AP +6 more
europepmc +1 more source