Search for dissertations about: "Machine learning chemistry"

Showing result 1 - 5 of 22 swedish dissertations containing the words Machine learning chemistry.

  2. 1. Simulating ion transport in electrolyte materials with physics-based and machine-learning models

    Author : Yunqi Shao; Chao Zhang; Peter Broqvist; Carl Nettelblad; Barbara Kirchner; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; electrolytes; ionic conductivity; ion transport; molecular dynamics; machine learning potential; proton transfer; Chemistry with specialization in Inorganic Chemistry; Kemi med inriktning mot oorganisk kemi;

    Abstract : Electrolytes are indispensable components of electrochemical devices such as batteries, fuel cells, and supercapacitors, and the mass transport in electrolytes is one of the most important design focuses of such devices. A microscopic picture of ion transport is essential to link the chemical properties of electrolyte materials to their electrochemical applications. READ MORE

  4. 2. Organic Electrode Battery Materials : A Journey from Quantum Mechanics to Artificial Intelligence

    Author : Rodrigo P. Carvalho; Moyses Araujo; Daniel Brandell; Susanne Mirbt; Wolfgang Wenzel; Uppsala universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Batteries; Artificial Intelligence; Organic electrodes; High-voltage cathode materials; Machine learning; Materials discovery; High throughput screening; Physics with spec. in Atomic; Molecular and Condensed Matter Physics; Fysik med inriktning mot atom- molekyl- och kondenserande materiens fysik;

    Abstract : Batteries have become an irreplaceable technology in human life as society becomes progressively more dependent on electricity. The demand for novel battery technologies has increased fast, especially with the popularisation of different portable devices. READ MORE

  5. 3. Synergies between Chemometrics and Machine Learning

    Author : Rickard Sjögren; Johan Trygg; Olivier Cloarec; Ola Spjuth; Umeå universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; computational science; machine learning; chemometrics; multivariate data analysis; design of experiments; data science; beräkningsvetenskap; maskininlärning; kemometri; multivariat dataanalys; experimentdesign;

    Abstract : Thanks to digitization and automation, data in all shapes and forms are generated in ever-growing quantities throughout society, industry and science. Data-driven methods, such as machine learning algorithms, are already widely used to benefit from all these data in all kinds of applications, ranging from text suggestion in smartphones to process monitoring in industry. READ MORE

  6. 4. Practical application of machine learning for analyses of biological matrices and environmental phenomena

    Author : Alexandra Walsh; Göteborgs universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Machine learning; Surface enhanced Raman spectroscopy; Acute lymphatic leukaemia; Volatile halogenated organic carbons; Marine algae; Doxorubicin; Principal component analysis; Multivariate statistics; Design of experiments; Waterlogged archaelogical wood; Transposed orthogonal partial least squares;

    Abstract : This thesis presents research aimed at forwarding an understanding of machine learning methods as a method of studying complex matrices and environmental phenomena. A number of machine learning methods in the form of linear projection algorithms and statistical experimental designs were applied for qualitative analysis of different matrices. READ MORE

  7. 5. Theoretical prediction of properties of atomistic systems : Density functional theory and machine learning

    Author : Alexander Lindmaa; Rickard Armiento; Igor Abrikosov; Torbjörn Björkman; Linköpings universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Abstract : The prediction of ground state properties of atomistic systems is of vital importance in technological advances as well as in the physical sciences. Fundamentally, these predictions are based on a quantum-mechanical description of many-electron systems. READ MORE