Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Hybrid modeling of first-principles and machine learning: A step-by-step tutorial review for practical implementation
In recent years, the integration of mechanistic process models with advanced machine
learning techniques has led to the development of hybrid models, which have shown …
learning techniques has led to the development of hybrid models, which have shown …
Investigating high-performance non-precious transition metal oxide catalysts for nitrogen reduction reaction: a multifaceted DFT–kMC–LSTM approach
The need for non-precious-metal catalysts for the nitrogen reduction reaction (NRR) is
growing due to the high cost of precious-metal catalysts. Transition metal oxides (TMOs) are …
growing due to the high cost of precious-metal catalysts. Transition metal oxides (TMOs) are …
[HTML][HTML] Physics-informed machine learning for MPC: Application to a batch crystallization process
This work presents a framework for develo** physics-informed recurrent neural network
(PIRNN) models and PIRNN-based predictive control schemes for batch crystallization …
(PIRNN) models and PIRNN-based predictive control schemes for batch crystallization …
Machine learning meets process control: Unveiling the potential of LSTMc
In the past three decades, proportional‐integral/PI‐differential (PI/PID) controllers and model
predictive controller (MPCs) have predominantly governed complex chemical process …
predictive controller (MPCs) have predominantly governed complex chemical process …
Deterministic and Monte Carlo methods for simulation of plasma‐surface interactions
Two approaches to the modeling of surface kinetics in reactive plasmas are discussed.
Coarse‐grained deterministic models incorporate rate balance equations for coverages of …
Coarse‐grained deterministic models incorporate rate balance equations for coverages of …
Multiscale modeling of dendrite formation in lithium-ion batteries
The commercialization of Lithium-ion batteries (LIBs) with Li metal anode has reached an
impasse due to the unpredictable dendrite growth, which significantly deteriorates the …
impasse due to the unpredictable dendrite growth, which significantly deteriorates the …
Neural network-based model predictive control for thin-film chemical deposition of quantum dots using data from a multiscale simulation
Recently, thin-film deposition of quantum dot (QDs) to manufacture solar cells and displays
have received significant attention due to the lucrative optoelectronic properties of these …
have received significant attention due to the lucrative optoelectronic properties of these …
Exploring dynamics in single atom catalyst research: a comprehensive DFT-kMC study of nitrogen reduction reaction with focus on tm aggregation
Transition metal (TM)-based single atom catalysts (SACs) have emerged as a promising
solution for the electrochemical nitrogen reduction reaction (NRR) due to their unique d …
solution for the electrochemical nitrogen reduction reaction (NRR) due to their unique d …
Nonlinear model predictive control of a multiscale thin film deposition process using artificial neural networks
The purpose of this study was to employ Artificial Neural Networks (ANNs) to develop data-
driven models that would enable the shrinking horizon nonlinear model predictive control of …
driven models that would enable the shrinking horizon nonlinear model predictive control of …
A slip-spring framework to study relaxation dynamics of entangled wormlike micelles with kinetic Monte Carlo algorithm
Abstract Hypothesis Wormlike micelles (WLMs) formed due to the self-assembly of
amphiphiles in aqueous solution have similar viscoelastic properties as polymers. Owing to …
amphiphiles in aqueous solution have similar viscoelastic properties as polymers. Owing to …