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Sustainable Materials The Role of Artificial Intelligence and Machine Learning - Akshansh Mishra, Vijaykumar S Jatti, Shivangi Paliwal 2025 PDF CRC Press BOOKS
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Sustainable Materials The Role of Artificial Intelligence and Machine Learning
Author: Akshansh Mishra, Vijaykumar S Jatti, Shivangi Paliwal
Year: 2025
Pages: 215
Format: PDF
File size: 16.5 MB
Language: ENG



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The Role of Artificial Intelligence and Machine Learning in Sustainable Materials Development As technology continues to evolve at an unprecedented pace, it is crucial that we understand the process of technological advancement and its impact on humanity's survival. In the field of materials science, artificial intelligence (AI) and machine learning (ML) are revolutionizing the way we develop and understand sustainable materials. This book delves into the role of AI and ML in the development of sustainable polymer composites, highlighting their self-learning ability and potential to accommodate complex requirements. The book begins by exploring the current state of AI and ML in material science, discussing their history, applications, and limitations. It then delves into the specific techniques used in the development of prediction analysis of sustainable polymer composites, including neural networks and deep learning algorithms. These techniques enable the accurate characterization of materials at the molecular level, expediting simulations and discovering new materials with desirable properties.
Роль искусственного интеллекта и машинного обучения в устойчивом развитии материалов Поскольку технологии продолжают развиваться беспрецедентными темпами, крайне важно, чтобы мы понимали процесс технологического прогресса и его влияние на выживание человечества. В области материаловедения искусственный интеллект (ИИ) и машинное обучение (ML) революционизируют способы разработки и понимания устойчивых материалов. Эта книга углубляется в роль AI и ML в разработке устойчивых полимерных композитов, подчеркивая их способность к самообучению и потенциал для удовлетворения сложных требований. Книга начинается с изучения современного состояния ИИ и МЛ в материаловедении, обсуждения их истории, применения и ограничений. Затем он углубляется в конкретные методы, используемые при разработке прогнозного анализа устойчивых полимерных композитов, включая нейронные сети и алгоритмы глубокого обучения. Эти методы позволяют точно характеризовать материалы на молекулярном уровне, ускоряя моделирование и открывая новые материалы с желательными свойствами.
rôle de l'intelligence artificielle et de l'apprentissage automatique dans le développement durable des matériaux Alors que la technologie continue d'évoluer à un rythme sans précédent, il est essentiel que nous comprenions le processus de progrès technologique et son impact sur la survie de l'humanité. Dans le domaine de la science des matériaux, l'intelligence artificielle (IA) et l'apprentissage automatique (ML) révolutionnent le développement et la compréhension de matériaux durables. Ce livre approfondit le rôle de l'AI et de la ML dans le développement de composites polymères résistants, soulignant leur capacité d'auto-apprentissage et leur capacité à répondre à des exigences complexes. livre commence par une étude de l'état actuel de l'IA et de la LM en science des matériaux, une discussion de leur histoire, de leur application et de leurs limites. Il s'oriente ensuite vers les méthodes spécifiques utilisées dans le développement de l'analyse prédictive des composites polymères résistants, y compris les réseaux neuronaux et les algorithmes d'apprentissage profond. Ces techniques permettent de caractériser avec précision les matériaux au niveau moléculaire, d'accélérer la modélisation et de découvrir de nouveaux matériaux avec les propriétés souhaitées.
papel de la inteligencia artificial y el aprendizaje automático en el desarrollo sostenible de los materiales A medida que la tecnología continúa evolucionando a un ritmo sin precedentes, es esencial que comprendamos el proceso de progreso tecnológico y su impacto en la supervivencia de la humanidad. En el campo de la ciencia de los materiales, la inteligencia artificial (IA) y el aprendizaje automático (ML) están revolucionando las formas de desarrollar y entender materiales sostenibles. Este libro profundiza en el papel de AI y ML en el desarrollo de compuestos de polímeros resistentes, destacando su capacidad de autoaprendizaje y su potencial para cumplir requisitos complejos. libro comienza con un estudio del estado moderno de la IA y el ML en la ciencia de los materiales, discutiendo su historia, aplicación y limitaciones. Luego se profundiza en las técnicas específicas utilizadas en el desarrollo del análisis predictivo de compuestos de polímeros resistentes, incluyendo redes neuronales y algoritmos de aprendizaje profundo. Estas técnicas permiten caracterizar con precisión los materiales a nivel molecular, acelerando la simulación y descubriendo nuevos materiales con propiedades deseables.
Il ruolo dell'intelligenza artificiale e dell'apprendimento automatico nello sviluppo sostenibile dei materiali Poiché la tecnologia continua a crescere a un ritmo senza precedenti, è fondamentale che comprendiamo il processo di progresso tecnologico e il suo impatto sulla sopravvivenza dell'umanità. Nel campo della scienza dei materiali, l'intelligenza artificiale (IA) e l'apprendimento automatico (ML) rivoluzionano le modalità di sviluppo e comprensione dei materiali sostenibili. Questo libro approfondisce il ruolo di AI e ML nello sviluppo di compositi polimerici sostenibili, sottolineando la loro capacità di apprendimento autonomo e il potenziale per soddisfare esigenze complesse. Il libro inizia studiando lo stato attuale dell'IA e dell'ML nella scienza dei materiali, discutendo la loro storia, applicazione e restrizioni. Viene poi approfondito in metodi specifici utilizzati per lo sviluppo di analisi predittive di compositi polimerici resistenti, tra cui reti neurali e algoritmi di apprendimento profondo. Questi metodi consentono di caratterizzare in modo preciso i materiali a livello molecolare, accelerando la simulazione e aprendo nuovi materiali con proprietà desiderabili.
Die Rolle von künstlicher Intelligenz und maschinellem rnen bei der nachhaltigen Entwicklung von Materialien Da sich die Technologie in einem beispiellosen Tempo weiterentwickelt, ist es unerlässlich, dass wir den Prozess des technologischen Fortschritts und seine Auswirkungen auf das Überleben der Menschheit verstehen. In der Materialwissenschaft revolutionieren künstliche Intelligenz (KI) und maschinelles rnen (ML) die Art und Weise, wie nachhaltige Materialien entwickelt und verstanden werden. Dieses Buch befasst sich mit der Rolle von AI und ML bei der Entwicklung nachhaltiger Polymerverbundwerkstoffe und betont deren Fähigkeit zum Selbstlernen und das Potenzial, komplexe Anforderungen zu erfüllen. Das Buch beginnt mit einer Untersuchung des aktuellen Zustands von KI und ML in der Materialwissenschaft, einer Diskussion über ihre Geschichte, Anwendung und Einschränkungen. Anschließend geht er tiefer in die spezifischen Techniken ein, die bei der Entwicklung von prädiktiven Analysen resistenter Polymerverbundwerkstoffe verwendet werden, einschließlich neuronaler Netzwerke und Deep-arning-Algorithmen. Diese Methoden ermöglichen die präzise Charakterisierung von Materialien auf molekularer Ebene, beschleunigen die Modellierung und erschließen neue Materialien mit gewünschten Eigenschaften.
Rola sztucznej inteligencji i uczenia maszynowego w zrównoważonym rozwoju materiałów Ponieważ technologia nadal rozwija się w bezprecedensowym tempie, musimy zrozumieć proces postępu technologicznego i jego wpływ na ludzkie przetrwanie. W nauce o materiałach sztuczna inteligencja (AI) i uczenie maszynowe (ML) rewolucjonizują sposób rozwoju i zrozumienia zrównoważonych materiałów. Książka ta zagłębia się w rolę AI i ML w rozwoju zrównoważonych kompozytów polimerowych, podkreślając ich zdolność do samodzielnego uczenia się i potencjał do spełnienia złożonych wymagań. Książka rozpoczyna się badaniem obecnego stanu AI i ML w nauce o materiałach, omówieniem ich historii, zastosowania i ograniczeń. Następnie zagłębia się w konkretne metody stosowane przy opracowywaniu analizy prognostycznej odpornych kompozytów polimerowych, w tym sieci neuronowych i algorytmów głębokiego uczenia się. Techniki te umożliwiają precyzyjną charakterystykę materiałów na poziomie molekularnym, przyspieszając symulacje i odkrywając nowe materiały o pożądanych właściwościach.
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Malzemelerin Sürdürülebilir Gelişiminde Yapay Zeka ve Makine Öğreniminin Rolü Teknoloji, benzeri görülmemiş bir hızda ilerlemeye devam ederken, teknolojik ilerleme sürecini ve bunun insanın hayatta kalması üzerindeki etkisini anlamamız zorunludur. Malzeme biliminde, yapay zeka (AI) ve makine öğrenimi (ML), sürdürülebilir malzemelerin geliştirilme ve anlaşılma biçiminde devrim yaratıyor. Bu kitap, AI ve ML'nin sürdürülebilir polimer kompozitlerin geliştirilmesindeki rolünü, kendi kendine öğrenme yeteneklerini ve karmaşık gereksinimleri karşılama potansiyellerini vurgulamaktadır. Kitap, malzeme biliminde AI ve ML'nin mevcut durumunun incelenmesi, tarihlerinin, uygulamalarının ve sınırlamalarının tartışılmasıyla başlar. Daha sonra, sinir ağları ve derin öğrenme algoritmaları da dahil olmak üzere dirençli polimer kompozitlerin öngörücü analizinin geliştirilmesinde kullanılan belirli yöntemleri araştırıyor. Bu teknikler, malzemelerin moleküler düzeyde kesin karakterizasyonuna izin verir, simülasyonları hızlandırır ve istenen özelliklere sahip yeni malzemeler keşfeder.
دور الذكاء الاصطناعي والتعلم الآلي في التنمية المستدامة للمواد مع استمرار التكنولوجيا في التقدم بوتيرة غير مسبوقة، من الضروري أن نفهم عملية التقدم التكنولوجي وتأثيرها على بقاء الإنسان. في علم المواد، يحدث الذكاء الاصطناعي (AI) والتعلم الآلي (ML) ثورة في طريقة تطوير وفهم المواد المستدامة. يتعمق هذا الكتاب في دور الذكاء الاصطناعي و ML في تطوير مركبات البوليمر المستدامة، مما يسلط الضوء على قدرتها على التعلم الذاتي وإمكاناتها لتلبية المتطلبات المعقدة. يبدأ الكتاب بدراسة الحالة الحالية للذكاء الاصطناعي و ML في علم المواد، ومناقشة تاريخهما وتطبيقهما وقيودهما. ثم يتعمق في طرق محددة تستخدم في تطوير التحليل التنبؤي لمركبات البوليمر المقاومة، بما في ذلك الشبكات العصبية وخوارزميات التعلم العميق. تسمح هذه التقنيات بتوصيف دقيق للمواد على المستوى الجزيئي، وتسريع عمليات المحاكاة واكتشاف مواد جديدة ذات خصائص مرغوبة.

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