Index Catalog // Arch : Northwestern University Institutional Repository

Description:: The field of materials discovery is undergoing an unprecedented transition from laboratory tocomputer. Behind this transition is the new ability to accurately compute material properties, especially energetic stability, from first principles with density functional theory (DFT). However, DFT remains computationally expensive, and DFT-based materials discovery is intractable, especially in high...
Keyword:: High throughput, Inorganic compounds, Big data, Density functional theory, Materials discovery, and Machine learning
Subject:: Materials Science, Condensed matter physics, and Computational chemistry
Creator:: Griesemer, Sean Darius
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 05/31/2023
Date Created:: 2023-01-01
Resource Type:: Dissertation
Alternate Identifier:: http://dissertations.umi.com/northwestern:16606 and etdadmin_upload_986816

Description:: Metal–organic frameworks (MOFs) are a class of crystalline materials composed of metal nodes connected by organic linkers. Due to their high degree of synthetic tunability, MOFs have been considered for a wide range of applications, including many that rely on a change in oxidation state. While most MOFs are generally...
Keyword:: Computational screening, Density functional theory, Machine learning, and Metal-organic framework
Subject:: Chemical engineering
Creator:: Rosen, Andrew Scott
Owner:: Scholarly Digital Publishing
Language:: en
Date Uploaded:: 10/07/2021
Date Created:: 2021-01-01
Resource Type:: Dissertation
Alternate Identifier:: etdadmin_upload_838355 and http://dissertations.umi.com/northwestern:15675

Description:: Moving away from fossil fuels requires environmentally friendly and economically viable alternative energy sources. A wide adoption of new technologies for energy production and storage depends on better performing materials. Computational methods, such as electronic structure calculations and machine learning, hold the promise to work in conjunction with traditional experimentation...
Keyword:: Perovskites, Hydrogen production, Water splitting, Density functional theory, Materials discovery, and Machine learning
Subject:: Materials Science and Engineering
Creator:: Antoine Alexandre Emery
Owner:: Scholarly Digital Publishing
Date Uploaded:: 10/22/2018
Date Modified:: 10/22/2018
Date Created:: 2017-01-01
Resource Type:: Dissertation

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