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Machine Learning Augmented Spectroscopies For Intelligent Materials Design
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Book Synopsis Machine Learning-Augmented Spectroscopies for Intelligent Materials Design by : Nina Andrejevic
Download or read book Machine Learning-Augmented Spectroscopies for Intelligent Materials Design written by Nina Andrejevic and published by Springer Nature. This book was released on 2022-10-06 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: The thesis contains several pioneering results at the intersection of state-of-the-art materials characterization techniques and machine learning. The use of machine learning empowers the information extraction capability of neutron and photon spectroscopies. In particular, new knowledge and new physics insights to aid spectroscopic analysis may hold great promise for next-generation quantum technology. As a prominent example, the so-called proximity effect at topological material interfaces promises to enable spintronics without energy dissipation and quantum computing with fault tolerance, yet the characteristic spectral features to identify the proximity effect have long been elusive. The work presented within permits a fine resolution of its spectroscopic features and a determination of the proximity effect which could aid further experiments with improved interpretability. A few novel machine learning architectures are proposed in this thesis work which leverage the case when the data is scarce and utilize the internal symmetry of the system to improve the training quality. The work sheds light on future pathways to apply machine learning to augment experiments.
Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop
Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
Book Synopsis Machine Learning Meets Quantum Physics by : Kristof T. Schütt
Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.
Book Synopsis Machine Learning in Chemistry by : Hugh M. Cartwright
Download or read book Machine Learning in Chemistry written by Hugh M. Cartwright and published by Royal Society of Chemistry. This book was released on 2020-07-15 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.
Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton
Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Book Synopsis The Deep Learning Revolution by : Terrence J. Sejnowski
Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Book Synopsis Microstructure Sensitive Design for Performance Optimization by : Brent L. Adams
Download or read book Microstructure Sensitive Design for Performance Optimization written by Brent L. Adams and published by Butterworth-Heinemann. This book was released on 2012-12-31 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: The accelerating rate at which new materials are appearing, and transforming the engineering world, only serves to emphasize the vast potential for novel material structure and related performance. Microstructure Sensitive Design for Performance Optimization (MSDPO) embodies a new methodology for systematic design of material microstructure to meet the requirements of design in optimal ways. Intended for materials engineers and researchers in industry, government and academia as well as upper level undergraduate and graduate students studying material science and engineering, MSDPO provides a novel mathematical framework that facilitates a rigorous consideration of the material microstructure as a continuous design variable in the field of engineering design. - Presents new methods and techniques for analysis and optimum design of materials at the microstructure level - Authors' methodology introduces spectral approaches not available in previous texts, such as the incorporation of crystallographic orientation as a variable in the design of engineered components with targeted elastic properties - Numerous illustrations and examples throughout the text help readers grasp the concepts
Book Synopsis Transmission Electron Microscopy by : C. Barry Carter
Download or read book Transmission Electron Microscopy written by C. Barry Carter and published by Springer. This book was released on 2016-08-24 with total page 543 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is a companion volume to Transmission Electron Microscopy: A Textbook for Materials Science by Williams and Carter. The aim is to extend the discussion of certain topics that are either rapidly changing at this time or that would benefit from more detailed discussion than space allowed in the primary text. World-renowned researchers have contributed chapters in their area of expertise, and the editors have carefully prepared these chapters to provide a uniform tone and treatment for this exciting material. The book features an unparalleled collection of color figures showcasing the quality and variety of chemical data that can be obtained from today’s instruments, as well as key pitfalls to avoid. As with the previous TEM text, each chapter contains two sets of questions, one for self assessment and a second more suitable for homework assignments. Throughout the book, the style follows that of Williams & Carter even when the subject matter becomes challenging—the aim is always to make the topic understandable by first-year graduate students and others who are working in the field of Materials Science Topics covered include sources, in-situ experiments, electron diffraction, Digital Micrograph, waves and holography, focal-series reconstruction and direct methods, STEM and tomography, energy-filtered TEM (EFTEM) imaging, and spectrum imaging. The range and depth of material makes this companion volume essential reading for the budding microscopist and a key reference for practicing researchers using these and related techniques.
Book Synopsis Quantum Chemistry in the Age of Machine Learning by : Pavlo O. Dral
Download or read book Quantum Chemistry in the Age of Machine Learning written by Pavlo O. Dral and published by Elsevier. This book was released on 2022-09-16 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning. Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field. - Compiles advances of machine learning in quantum chemistry across different areas into a single resource - Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry - Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry
Book Synopsis Introduction to Machine Learning by : Ethem Alpaydin
Download or read book Introduction to Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2014-08-22 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Book Synopsis Pharmaceutical Applications of Raman Spectroscopy by : Slobodan Sasic
Download or read book Pharmaceutical Applications of Raman Spectroscopy written by Slobodan Sasic and published by John Wiley & Sons. This book was released on 2007-10-23 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Raman spectroscopy has advanced in recent years with increasing use both in industry and academia. This is due largely to steady improvements in instrumentation, decreasing cost, and the availability of chemometrics to assist in the analysis of data. Pharmaceutical applications of Raman spectroscopy have developed similarly and this book will focus on those applications. Carefully organized with an emphasis on industry issues, Pharmaceutical Applications of Raman Spectroscopy, provides the basic theory of Raman effect and instrumentation, and then addresses a wide range of pharmaceutical applications. Current applications that are routinely used as well as those with promising potential are covered. Applications cover a broad range from discovery to manufacturing in the pharmaceutical industry and include identifying polymorphs, monitoring real-time processes, imaging solid dosage formulations, imaging active pharmaceutical ingredients in cells, and diagnostics.
Book Synopsis Chemically Deposited Nanocrystalline Metal Oxide Thin Films by : Fabian I. Ezema
Download or read book Chemically Deposited Nanocrystalline Metal Oxide Thin Films written by Fabian I. Ezema and published by Springer Nature. This book was released on 2021-06-26 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book guides beginners in the areas of thin film preparation, characterization, and device making, while providing insight into these areas for experts. As chemically deposited metal oxides are currently gaining attention in development of devices such as solar cells, supercapacitors, batteries, sensors, etc., the book illustrates how the chemical deposition route is emerging as a relatively inexpensive, simple, and convenient solution for large area deposition. The advancement in the nanostructured materials for the development of devices is fully discussed.
Book Synopsis Computational Electrochemistry by : S. Paddison
Download or read book Computational Electrochemistry written by S. Paddison and published by The Electrochemical Society. This book was released on 2015-12-28 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Hard X-ray Photoelectron Spectroscopy (HAXPES) by : Joseph Woicik
Download or read book Hard X-ray Photoelectron Spectroscopy (HAXPES) written by Joseph Woicik and published by Springer. This book was released on 2015-12-26 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the first complete and up-to-date summary of the state of the art in HAXPES and motivates readers to harness its powerful capabilities in their own research. The chapters are written by experts. They include historical work, modern instrumentation, theory and applications. This book spans from physics to chemistry and materials science and engineering. In consideration of the rapid development of the technique, several chapters include highlights illustrating future opportunities as well.
Book Synopsis Information Science for Materials Discovery and Design by : Turab Lookman
Download or read book Information Science for Materials Discovery and Design written by Turab Lookman and published by Springer. This book was released on 2015-12-12 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with an information-driven approach to plan materials discovery and design, iterative learning. The authors present contrasting but complementary approaches, such as those based on high throughput calculations, combinatorial experiments or data driven discovery, together with machine-learning methods. Similarly, statistical methods successfully applied in other fields, such as biosciences, are presented. The content spans from materials science to information science to reflect the cross-disciplinary nature of the field. A perspective is presented that offers a paradigm (codesign loop for materials design) to involve iteratively learning from experiments and calculations to develop materials with optimum properties. Such a loop requires the elements of incorporating domain materials knowledge, a database of descriptors (the genes), a surrogate or statistical model developed to predict a given property with uncertainties, performing adaptive experimental design to guide the next experiment or calculation and aspects of high throughput calculations as well as experiments. The book is about manufacturing with the aim to halving the time to discover and design new materials. Accelerating discovery relies on using large databases, computation, and mathematics in the material sciences in a manner similar to the way used to in the Human Genome Initiative. Novel approaches are therefore called to explore the enormous phase space presented by complex materials and processes. To achieve the desired performance gains, a predictive capability is needed to guide experiments and computations in the most fruitful directions by reducing not successful trials. Despite advances in computation and experimental techniques, generating vast arrays of data; without a clear way of linkage to models, the full value of data driven discovery cannot be realized. Hence, along with experimental, theoretical and computational materials science, we need to add a “fourth leg’’ to our toolkit to make the “Materials Genome'' a reality, the science of Materials Informatics.
Book Synopsis Nanotechnology Research Directions: IWGN Workshop Report by : R.S. Williams
Download or read book Nanotechnology Research Directions: IWGN Workshop Report written by R.S. Williams and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: energy production, environmental management, transportation, communication, computation, and education. As the twenty-first century unfolds, nanotechnology's impact on the health, wealth, and security of the world's people is expected to be at least as significant as the combined influences in this century of antibiotics, the integrated circuit, and human-made polymers. Dr. Neal Lane, Advisor to the President for Science and Technology and former National Science Foundation (NSF) director, stated at a Congressional hearing in April 1998, "If I were asked for an area of science and engineering that will most likely produce the breakthroughs of tomorrow, I would point to nanoscale science and engineering. " Recognizing this potential, the White House Office of Science and Technology Policy (OSTP) and the Office of Management and Budget (OMB) have issued a joint memorandum to Federal agency heads that identifies nanotechnology as a research priority area for Federal investment in fiscal year 2001. This report charts "Nanotechnology Research Directions," as developed by the Interagency W orking Group on Nano Science, Engineering, and Technology (IWGN) of the National Science and Technology Council (NSTC). The report incorporates the views of leading experts from government, academia, and the private sector. It reflects the consensus reached at an IWGN-sponsored workshop held on January 27-29, 1999, and detailed in contributions submitted thereafter by members of the V. S. science and engineering community. (See Appendix A for a list of contributors.
Book Synopsis Solid State Batteries: Materials Design and Optimization by : Christian Julien
Download or read book Solid State Batteries: Materials Design and Optimization written by Christian Julien and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of solid state ionics is multidisciplinary in nature. Chemists, physicists, electrochimists, and engineers all are involved in the research and development of materials, techniques, and theoretical approaches. This science is one of the great triumphs of the second part of the 20th century. For nearly a century, development of materials for solid-state ionic technology has been restricted. During the last two decades there have been remarkable advances: more materials were discovered, modem technologies were used for characterization and optimization of ionic conduction in solids, trial and error approaches were deserted for defined predictions. During the same period fundamental theories for ion conduction in solids appeared. The large explosion of solid-state ionic material science may be considered to be due to two other influences. The first aspect is related to economy and connected with energy production, storage, and utilization. There are basic problems in industrialized countries from the economical, environmental, political, and technological points of view. The possibility of storing a large amount of utilizable energy in a comparatively small volume would make a number of non-conventional intermittent energy sources of practical convenience and cost. The second aspect is related to huge increase in international relationships between researchers and exchanges of results make considerable progress between scientists; one find many institutes joined in common search programs such as the material science networks organized by EEC in the European countries.
