相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Comparative evaluation of artificial neural networks for the performance prediction of Pt-based catalysts in water gas shift reaction
Changsu Kim et al.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH (2022)
Parallel and series multi-bed pressure swing adsorption processes for H2 recovery from a lean hydrogen mixture
Yongha Park et al.
CHEMICAL ENGINEERING JOURNAL (2021)
Investigating the impact of data normalization on classification performance
Dalwinder Singh et al.
APPLIED SOFT COMPUTING (2020)
Water gas shift reaction for hydrogen production and carbon dioxide capture: A review
Wei-Hsin Chen et al.
APPLIED ENERGY (2020)
Machine Learning for Catalysis Informatics: Recent Applications and Prospects
Takashi Toyao et al.
ACS CATALYSIS (2020)
The optimal carbon and hydrogen balance for methanol production from coke oven gas and Linz-Donawitz gas: Process development and techno-economic analysis
Sunghoon Kim et al.
FUEL (2020)
Mechanistic Kinetic Model for Biogas Dry Reforming
Prakash Ponugoti et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2020)
Machine Learning for Atomic Simulation and Activity Prediction in Heterogeneous Catalysis: Current Status and Future
Sicong Ma et al.
ACS CATALYSIS (2020)
Machine learning in chemical reaction space
Sina Stocker et al.
NATURE COMMUNICATIONS (2020)
The next level in chemical space navigation: going far beyond enumerable compound libraries
Torsten Hoffmann et al.
DRUG DISCOVERY TODAY (2019)
Machine Learning for Computational Heterogeneous Catalysis
Philomena Schlexer Lamoureux et al.
CHEMCATCHEM (2019)
Mathematical Modeling and Simulation of Carbon Monoxide Absorption Column for Blast Furnace Gas and Linz-Donawitz Gas Separation by COSORB Process
Yoon-Tae Go et al.
JOURNAL OF CHEMICAL ENGINEERING OF JAPAN (2019)
Progress in Accurate Chemical Kinetic Modeling, Simulations, and Parameter Estimation for Heterogeneous Catalysis
Sebastian Matera et al.
ACS CATALYSIS (2019)
The promise of artificial intelligence in chemical engineering: Is it here, finally?
Venkat Venkatasubramanian
AICHE JOURNAL (2019)
Process development and techno-economic evaluation of methanol production by direct CO2 hydrogenation using solar-thermal energy
Thai Ngan Do et al.
JOURNAL OF CO2 UTILIZATION (2019)
Iron Catalysis in Reduction and Hydrometalation Reactions
Duo Wei et al.
CHEMICAL REVIEWS (2019)
A Pharmaceutical Industry Perspective on Sustainable Metal Catalysis
John D. Hayler et al.
ORGANOMETALLICS (2019)
Less is more: Sampling chemical space with active learning
Justin S. Smith et al.
JOURNAL OF CHEMICAL PHYSICS (2018)
A review of gas separation technologies within emission reduction programs in the iron and steel sector: Current application and development perspectives
Alvaro A. Ramirez-Santos et al.
SEPARATION AND PURIFICATION TECHNOLOGY (2018)
Optimization Approach to the Reduction of CO2 Emissions for Syngas Production Involving Dry Reforming
Shaik Afzal et al.
ACS SUSTAINABLE CHEMISTRY & ENGINEERING (2018)
Artificial neural networks with response surface methodology for optimization of selective CO2 hydrogenation using K-promoted iron catalyst in a microchannel reactor
Yong Sun et al.
JOURNAL OF CO2 UTILIZATION (2018)
Modelling and optimization of syngas production by methane dry reforming over samarium oxide supported cobalt catalyst: response surface methodology and artificial neural networks approach
Bamidele V. Ayodele et al.
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY (2017)
Techno-economic analysis of production of Fischer-Tropsch liquids via biomass gasification: The effects of Fischer-Tropsch catalysts and natural gas co-feeding
Mohammad Rafati et al.
ENERGY CONVERSION AND MANAGEMENT (2017)
Data Mining and Analytics in the Process Industry: The Role of Machine Learning
Zhiqiang Ge et al.
IEEE ACCESS (2017)
Analysis Resilient Algorithm on Artificial Neural Network Backpropagation
Widodo Saputra et al.
INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICONICT) (2017)
Optimization of Biopharmaceutical Downstream Processes Supported by Mechanistic Models and Artificial Neural Networks
Silvia M. Pirrung et al.
BIOTECHNOLOGY PROGRESS (2017)
Response surface methodology and artificial neural network modelling of an aqueous two-phase system for purification of a recombinant alkaline active xylanase
Farshad Rahimpour et al.
PROCESS BIOCHEMISTRY (2016)
Techno-economic Comparison of Absorption and Adsorption Processes for Carbon Monoxide (CO) Separation from Linze-Donawitz Gas (LDG)
Young-Il Kim et al.
KOREAN CHEMICAL ENGINEERING RESEARCH (2016)
Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks
Farid Talebnia et al.
BIOTECHNOLOGY AND BIOPROCESS ENGINEERING (2015)
Pressure Swing Adsorption Process for Recovering H2 from the Effluent Gas of a Melting Incinerator
Dong-Kyu Moon et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2014)
Knowledge extraction for water gas shift reaction over noble metal catalysts from publications in the literature between 2002 and 2012
Cagla Odabasi et al.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY (2014)
Design and simulation of a methanol production plant from CO2 hydrogenation
Everton Simoes Van-Dal et al.
JOURNAL OF CLEANER PRODUCTION (2013)
Kinetic Modeling Studies of Heterogeneously Catalyzed Biodiesel Synthesis Reactions
Ankur Kapil et al.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH (2011)
Application of artificial neural networks to high-throughput synthesis of zeolites
M Moliner et al.
MICROPOROUS AND MESOPOROUS MATERIALS (2005)
The NIST Chemistry WebBook: A chemical data resource on the internet
PJ Linstrom et al.
JOURNAL OF CHEMICAL AND ENGINEERING DATA (2001)
Intrinsic kinetics of the gas-solid Fischer-Tropsch and water gas shift reactions over a precipitated iron catalyst
GP van der Laan et al.
APPLIED CATALYSIS A-GENERAL (2000)
分享论文
