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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 61,48
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 51,82
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 54,52
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 59,52
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 77,56
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Añadir al carritoCondición: New. 1st ed. 2024 edition NO-PA16APR2015-KAP.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 83,85
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EUR 77,07
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Añadir al carritoPaperback. Condición: Brand New. 101 pages. 9.25x6.10x0.22 inches. In Stock.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 77,21
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Añadir al carritoPaperback. Condición: Brand New. 96 pages. 9.25x6.10x9.24 inches. In Stock.
Idioma: Inglés
Publicado por Springer Nature Switzerland, Springer Nature Switzerland, 2024
ISBN 10: 3031520564 ISBN 13: 9783031520563
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 53,49
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data gap-filling methods. It discusses the genesis and model development of q-RASAR models demonstrating practical examples. It also showcases successful case studies on the application of q-RASAR modeling in medicinal chemistry, predictive toxicology, and materials sciences. The book also includes the tools used for q-RASAR model development for new users. It is a valuable resource for researchers and students interested in grasping the development algorithm of q-RASAR models and their application within specific research domains.
EUR 22,22
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This brief offers an introduction to the fascinating new field of quantitative read-across structure-activity relationships (q-RASAR) as a cheminformatics modeling approach in the background of quantitative structure-activity relationships (QSAR) and read-across (RA) as data gap-filling methods. It discusses the genesis and model development of q-RASAR models demonstrating practical examples. It also showcases successful case studies on the application of q-RASAR modeling in medicinal chemistry, predictive toxicology, and materials sciences. The book also includes the tools used for q-RASAR model development for new users. It is a valuable resource for researchers and students interested in grasping the development algorithm of q-RASAR models and their application within specific research domains.
Idioma: Inglés
Publicado por Elsevier - Health Sciences Division, Philadelphia, 2026
ISBN 10: 0443364745 ISBN 13: 9780443364747
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 192,10
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Añadir al carritoPaperback. Condición: new. Paperback. Cheminformatic Modelling and Data Gap Filling for a Green and Sustainable Environment Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 184,37
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 182,59
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Añadir al carritoPaperback. Condición: Brand New. 350 pages. In Stock.
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 203,52
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Idioma: Inglés
Publicado por Springer International Publishing AG, Cham, 2025
ISBN 10: 3031787234 ISBN 13: 9783031787232
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 235,39
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Añadir al carritoHardcover. Condición: new. Hardcover. This contributed volume focuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key properties of polymers, deep eutectic solvents, and ionic liquids, as well as to improve safety and performance in the study of energetic and reactive materials. With chapters covering polymer informatics, quantitative structureproperty relationship (QSPR) modeling, and computational approaches, the book serves as a comprehensive resource for researchers applying predictive modeling techniques to advance materials science and improve material safety and performance. This contributed volume focuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 233,02
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Librería: moluna, Greven, Alemania
EUR 205,17
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Añadir al carritoCondición: New. Presents multiple algorithms for QSPR models and machine learning methods for modeling environmental endpointsDiscusses crucial emerging topics in sustainable chemistry, such as mixture property modeling, microplastic toxicity modeling, and.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 279,08
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Librería: preigu, Osnabrück, Alemania
EUR 202,80
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Añadir al carritoTaschenbuch. Condición: Neu. Materials Informatics III | Polymers, Solvents and Energetic Materials | Kunal Roy (u. a.) | Taschenbuch | Challenges and Advances in Computational Chemistry and Physics | Englisch | 2026 | Springer | EAN 9783031787263 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.
EUR 202,80
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Añadir al carritoTaschenbuch. Condición: Neu. Materials Informatics II | Software Tools and Databases | Kunal Roy (u. a.) | Taschenbuch | Challenges and Advances in Computational Chemistry and Physics | Englisch | 2026 | Springer | EAN 9783031787300 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 277,18
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Añadir al carritoPaperback. Condición: Brand New. 350 pages. 5.81x2.11x9.01 inches. In Stock.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 235,39
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volumefocuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key properties of polymers, deep eutectic solvents, and ionic liquids, as well as to improve safety and performance in the study of energetic and reactive materials. With chapters covering polymer informatics, quantitative structure property relationship (QSPR) modeling, and computational approaches, the book serves as a comprehensive resource for researchers applying predictive modeling techniques to advance materials science and improve material safety and performance.
EUR 235,39
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volumeexplores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.
EUR 244,86
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volumeexplores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 244,86
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volumefocuses on the application of machine learning and cheminformatics in predictive modeling for organic materials, polymers, solvents, and energetic materials. It provides an in-depth look at how machine learning is utilized to predict key properties of polymers, deep eutectic solvents, and ionic liquids, as well as to improve safety and performance in the study of energetic and reactive materials. With chapters covering polymer informatics, quantitative structure property relationship (QSPR) modeling, and computational approaches, the book serves as a comprehensive resource for researchers applying predictive modeling techniques to advance materials science and improve material safety and performance.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 315,72
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Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 318,39
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