Download or read book Machine Learning for Polymer Informatics written by Ying Li and published by American Chemical Society. This book was released on 2024-06-28 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has significantly accelerated the development of new polymer materials. Machine Learning for Polymer Informatics introduces the reader to the most popular ways of applying machine learning in polymer informatics. This primer will equip the reader to ask the right questions about the application of machine learning in their areas of interest, as well as critically interpret publications leveraging machine learning methods. The authors encourage readers to try machine learning techniques when they have sufficient data in their area of interest. The development of machine learning has far exceeded human imagination, and with sufficient data, everything is full of possibilities.

Download or read book Advanced Machine Learning with Evolutionary and Metaheuristic Techniques written by Jayaraman Valadi and published by Springer Nature. This book was released on with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automatic Analysis and Validation of Open Polymer Data written by Nicholas William England and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A system to automatically extract, analyse, validate and model polymer data has been produced. This system is called the Polymer Informatics Knowledge System (PIKS). Methods of storing polymer data electronically are examined. The majority of data-formats are only capable of representing an idealised structure of a macromolecule rather than the actual distribution of structures present in the polymer. Polymer markup language (PML) is the only data-format capable of storing this information. A novel extension to the PML language, allowing copolymers produced with a depletion of reactants is introduced. Without the extension only Markov-chains can be produced. An informatics analysis of Unilever data of cleaning efficacy of polymers is performed. A representative macromolecule was produced for each polymer sample. Descriptors were calculated over these and used for machine learning to predict the cleaning efficacy. From these models a monomer was identified which was very strongly correlated with good cleaning performance. The monomer in question cannot be revealed as it is a trade secret. Polymer data from the PoLyInfo database are extracted and converted into XML. A summary of the data available in the PoLyInfo Database is presented. The PIKS tools were used to automatically validate this data for internal consistency, as well as against another data source. The monomers and polymers were analysed for consistency, as well as CML reactions being produced for the polymerisation reactions in the database which were also checked for constancy. The error in the structures was found to be 5.8% for the monomers, 7.3% for the polymers and 2.9% for the reactions. Some of the causes of the discrepancies are presented. The property data from the PoLyInfo database was then used for machine learning. Support Vector Regression (SVR) models of the glass transition temperature were produced both with and without the inclusion of sample characterisation data. Both methods performed similarly, with the model without producing an RMS error of 19.1K (r 2=0.96), while the model with produced an RMS error of 20.1K (r 2=0.96). This means that more sample characterisation data is required than the M-w and M-w/M-n.

Download or read book Machine Learning in Materials Informatics written by Yuling An and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about machine learning in materials informatics

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.

Download or read book Artificial Intelligence for Materials Science written by Yuan Cheng and published by Springer Nature. This book was released on 2021-03-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results. As new insights and several elaborative tools have been developed for materials science and engineering in recent years, it is an appropriate time to present a book covering recent progress in this field. Searchable and interactive databases can promote research on emerging materials. Recently, databases containing a large number of high-quality materials properties for new advanced materials discovery have been developed. These approaches are set to make a significant impact on human life and, with numerous commercial developments emerging, will become a major academic topic in the coming years. This authoritative and comprehensive book will be of interest to both existing researchers in this field as well as others in the materials science community who wish to take advantage of these powerful techniques. The book offers a global spread of authors, from USA, Canada, UK, Japan, France, Russia, China and Singapore, who are all world recognized experts in their separate areas. With content relevant to both academic and commercial points of view, and offering an accessible overview of recent progress and potential future directions, the book will interest graduate students, postgraduate researchers, and consultants and industrial engineers.

Download or read book Machine Learning in Chemistry written by Jon Paul Janet and published by American Chemical Society. This book was released on 2020-05-28 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important

Download or read book Advanced Polymer Structures written by Omar Mukbaniani and published by CRC Press. This book was released on 2023-10-06 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taking an interdisciplinary approach, this new book considers state-of-the-art developments and research in polymer science, such as advanced polymers, composites and nanocomposites, and the role of polymers in the progress of green chemistry and medicine. Polymers are studied in fields as diverse as polymer science (polymer chemistry and polymer physics), biophysics, biochemistry, and more generally in materials science and engineering. Polymer matrix composites (PMCs) and nanocomposites (PMNCs) are widely used in hightech material structures such as in the automotive, marine, and aerospace industries. Their impact on the physical and mechanical performance is mainly due to their reinforcing agents, fibers (glass, carbon, aramid) or nanofibers (MMT, CNTs, graphene, etc) but also due to a perfect mastery of the matrix/reinforcement interface.

Download or read book Recent Advances in Smart Self Healing Polymers and Composites written by Guoqiang Li and published by Woodhead Publishing. This book was released on 2022-06-08 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: There have been many new developments since the first edition of this book was published back in 2015. These can be summarized as follows: integration of multiple properties into self-healing polymer materials, such as the shape memory effect and flame retardancy; beyond self-healing and the development of recyclable thermoset polymers; and the application of self-healing polymers in both 3D and 4D printing. Recent Advances in Smart Self-healing Polymers and Composites, Second Edition provides a comprehensive introduction to the fascinating field of smart self-healing polymers and composites. All chapters are brought fully-up-to-date with the addition of six brand new contributions on the characterization of self-healing polymers, light-triggered self-healing, additive manufacturing, multifunctional thermoset polymers with self-healing ability, and recyclable thermoset polymers and 4D printing. It is written for a large readership including not only R&D researchers from diverse backgrounds such as chemistry, materials science, aerospace, physics, and biological science, but also for graduate student working on self-healing technologies as well as their newly developed applications. Features new chapters on characterization of self-healing polymers, light-triggered self-healing, additive manufacturing, multifunctional thermoset polymers with self-healing ability, recyclable thermoset polymers and 4D printing All chapters have been significantly updated from the previous edition Provides a grounding in all key areas of research to bring people up to speed with the latest developments

Download or read book Explainable AI XAI for Sustainable Development written by Lakshmi D and published by CRC Press. This book was released on 2024-06-26 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents innovative research works to automate, innovate, design, and deploy AI fo real-world applications. It discusses AI applications in major cutting-edge technologies and details about deployment solutions for different applications for sustainable development. The application of Blockchain techniques illustrates the ways of optimisation algorithms in this book. The challenges associated with AI deployment are also discussed in detail, and edge computing with machine learning solutions is explained. This book provides multi-domain applications of AI to the readers to help find innovative methods towards the business, sustainability, and customer outreach paradigms in the AI domain. • Focuses on virtual machine placement and migration techniques for cloud data centres • Presents the role of machine learning and meta-heuristic approaches for optimisation in cloud computing services • Includes application of placement techniques for quality of service, performance, and reliability improvement • Explores data centre resource management, load balancing and orchestration using machine learning techniques • Analyses dynamic and scalable resource scheduling with a focus on resource management The reference work is for postgraduate students, professionals, and academic researchers in computer science and information technology.

Download or read book Machine Learning and Data Mining in Materials Science written by Norbert Huber and published by Frontiers Media SA. This book was released on 2020-04-22 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Substance of Civilization written by Stephen L. Sass and published by Skyhorse Publishing Inc.. This book was released on 2011-08 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrates the way in which the discovery, application, and adaptation of materials has shaped the course of human history and the routines of our daily existence.

Download or read book Analysis of Machine Engineered Representations for Polymer Quantitative Structure Property Prediction written by Deepa Korani and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Obtaining effective polymer representations for quantitative structure propertyprediction is a challenging task, but deep learning techniques has progressed remarkably in learning such contextual representations from unlabeled polymeric data. In the field of cheminformatics, significant advances were made in Deep Learning Architecture Transformers, but development in effective polymer representations through Transformers in the field of Polymer Informatics is limited. In my thesis, I highlight the performance of Transformer learned representations in relation to prior techniques i.e. both handcrafted and deep learning-based approaches. Next, I detail how increasing the size of the Transformer affects the downstream task performance on the Glass Transition Temperature dataset. Finally, I identify several challenges and discuss promising future research directions.

Download or read book Polymer Libraries written by Michael A. R. Meier and published by Springer Science & Business Media. This book was released on 2010-05-21 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is truly an exciting time to be in the ?eld of polymer science. Advances in polymerization methods are providing polymer scientists with the ability to specify and control polymer composition, structure, architecture, and molecular weight to a degree that was not possible just a decade ago. This, in turn, is resulting in many novel application possibilities of polymers ranging from drug delivery systems and nanolithographyto stimuli-responsivematerials and many others. In addition,many of the application areas of polymers – such as coatings, adhesives, thermoplastics, composites, and personal care – are also taking advantage of the ability to design polymersduringtheir developmentefforts. Not to forget,manyof these applications of polymers involve mixing polymers with solvents, catalysts, colorants, and many other ingredients to prepare a formulated product. However, the tuning of polymer composition and structure as well as polymer formulations to optimize the ?nal performance properties can be challenging, - pecially since in many cases several interacting variables need to be optimized simultaneously. This is where the methodologies and techniques of combinatorial and high-throughput experimentation to synthesize and characterize polymer - braries can be an invaluable approach. Simply put, a polymer library is a collection of multiple polymer samples having a systematic variation in one or more variables related to composition, structure, or process. Various methods and strategies have been explored to ef?ciently prepare a large number of polymer samples and also to screen these samples for key properties of interest.

Download or read book Ecotoxicological QSARs written by Kunal Roy and published by Humana. This book was released on 2021-01-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on computational modeling of the ecotoxicity of chemicals and presents applications of quantitative structure–activity relationship models (QSARs) in the predictive toxicology field in a regulatory context. The extensive book covers a variety of protocols for descriptor computation, data curation, feature selection, learning algorithms, validation of models, applicability domain assessment, confidence estimation for predictions, and much more, as well as case studies and literature reviews on a number of hot topics. Written for the Methods in Pharmacology and Toxicology series, chapters include the kind of practical advice that is essential for researchers everywhere. Authoritative and comprehensive, Ecotoxicological QSARs is an ideal source to update readers in the field with current practices and introduce to them new developments and should therefore be very useful for researchers in academia, industries, and regulatory bodies.

Download or read book Information Processing and Management of Uncertainty in Knowledge Based Systems Applications written by Jesús Medina and published by Springer. This book was released on 2018-05-29 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).

Download or read book Forcefields for Atomistic Scale Simulations Materials and Applications written by Akarsh Verma and published by Springer Nature. This book was released on 2022-08-19 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the forcefields/interatomic potentials that are used in the atomistic-scale and molecular dynamics simulations. It covers mechanisms, salient features, formulations, important aspects and case studies of various forcefields utilized for characterizing various materials (such as nuclear materials and nanomaterials) and applications. This book gives many help to students and researchers who are studying the forcefield potentials and introduces various applications of atomistic-scale simulations to professors who are researching molecular dynamics.