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Meeting Materials Science & Technology 2020
Symposium Ceramics and Glasses Simulations and Machine Learning
Presentation Title De Novo Discovery of Nanoporous Structures with Tailored Sorption Isotherm by Machine Learning
Author(s) Yuhan Liu, Mathieu Bauchy
On-Site Speaker (Planned) Mathieu Bauchy
Abstract Scope Nanoporous materials (e.g., zeolite, activated carbon, metal-organic framework, polymeric membranes, etc.) have various technological applications, including gas separation, gas storage, catalytic transformations, etc. The functionalities of nanoporous materials strongly depend on their pore size and shape distribution—which present virtually limitless degrees of freedom. Here, based on high-throughput lattice density functional theory (LDFT) simulations and a convolutional neural network (CNN) predictor, we present a model allowing us to predict the water sorption isotherm of nanoporous configurations. The training of an inverse CNN generator then enables the inverse design of optimal porous microstructures featuring tailored/unusual sorption isotherms.


Ab-initio and Reactive MD Simulations of Polymer Pyrolysis and Formation of Silicon-based Ceramics
Application of Natural Language Processing to Zeolites and Cementitious Materials
Beyond the Average: Fluctuations in Glass-forming Systems
Data, Materials and Disorder
De Novo Discovery of Nanoporous Structures with Tailored Sorption Isotherm by Machine Learning
Defect Formation and Self-diffusion in Alumina: Computational Approaches
Introductory Comments: Ceramics and Glasses Simulations and Machine Learning
JAX, M.D.: End-to-End Differentiable, Hardware Accelerated, Molecular Dynamics in Pure Python
The Energy Landscape Governs Brittle-to-Ductile Transitions in Glasses
The Role of Pore Pattern on The Ductility Enhancement of Crystalline Silicon Nitride Nanoporous Membranes
Theoretical Calculation of Formation Energies and Site Preference of Substitutional Divalent Cations in Carbonated Apatite
Verification of Mn Local Structure in Manganese Lithium Borate-based Glass by Computer Simulations and X-ray Absorption Spectroscopy

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