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The rapid advancement of machine learning and artificial intelligence (AI)-driven techniques is revolutionizing materials discovery, property prediction, and material design by minimizing human intervention and accelerating scientific…

Materials Science · Physics 2026-01-06 Dilshod Nematov , Mirabbos Hojamberdiev

It is important to develop sustainable processes in materials science and manufacturing that are environmentally friendly. AI can play a significant role in decision support here as evident from our earlier research leading to tools…

Artificial Intelligence · Computer Science 2023-03-27 Aparna S. Varde , Jianyu Liang

Artificial intelligence (AI) raises expectations of substantial increases in rates of technological and scientific progress, but such anticipations are often not connected to detailed ground-level studies of AI use in innovation processes.…

Computers and Society · Computer Science 2025-11-21 John P. Nelson , Olajide Olugbade , Philip Shapira , Justin B. Biddle

In the pursuit of novel catalyst development to address pressing environmental concerns and energy demand, conventional design and optimization methods often fall short due to the complexity and vastness of the catalyst parameter space. The…

Chemical Physics · Physics 2024-02-08 Nung Siong Lai , Yi Shen Tew , Xialin Zhong , Jun Yin , Jiali Li , Binhang Yan , Xiaonan Wang

High throughput experimentation tools, machine learning (ML) methods, and open material databases are radically changing the way new materials are discovered. From the experimentally driven approach in the past, we are moving quickly…

Materials Science · Physics 2025-08-06 Albertus Denny Handoko , Riko I Made

Artificial intelligence is transforming molecular and materials science, but its growing computational and data demands raise critical sustainability challenges. In this Perspective, we examine resource considerations across the AI-driven…

This paper presents the first comprehensive literature review of deep learning (DL) applications in additive manufacturing (AM). It addresses the need for a thorough analysis in this rapidly growing yet scattered field, aiming to bring…

Machine Learning · Computer Science 2024-12-25 Amirul Islam Saimon , Emmanuel Yangue , Xiaowei Yue , Zhenyu James Kong , Chenang Liu

This chapter is a preprint from our book by , focusing on leveraging machine learning (ML) in chemical and polyolefin manufacturing optimization. It's crafted for both novices and seasoned professionals keen on the latest ML applications in…

Machine Learning · Computer Science 2024-01-23 Niket Sharma , Y. A. Liu

Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it demands advances at the levels of materials, devices, and systems for the efficient harvesting, storage, conversion, and management of renewable…

Additive manufacturing has become one of the forefront technologies in fabrication, enabling new products impossible to manufacture before. Although many materials exist for additive manufacturing, they typically suffer from performance…

Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development. The enormous complexity involved in existing multi-variable synthesis methods…

Materials Science · Physics 2020-11-02 Bijun Tang , Yuhao Lu , Jiadong Zhou , Han Wang , Prafful Golani , Manzhang Xu , Quan Xu , Cuntai Guan , Zheng Liu

Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various…

Emerging Technologies · Computer Science 2022-12-23 Sasitharan Balasubramaniam , Samitha Somathilaka , Sehee Sun , Adrian Ratwatte , Massimiliano Pierobon

Artificial intelligence is gaining strength and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems and processes can be devised and optimized thanks to machine learning…

Materials Science · Physics 2022-09-29 Cefe López

Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial-and-error and can be inefficient. Computational techniques, enhanced by modern artificial intelligence (AI), have…

An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the…

Machine Learning · Computer Science 2023-02-16 Deepthi Amuru , Harsha V. Vudumula , Pavan K. Cherupally , Sushanth R. Gurram , Amir Ahmad , Andleeb Zahra , Zia Abbas

Materials discovery is a cornerstone of modern technological advancement, yet it remains constrained by traditional trial-and-error paradigms and the inherent bias of human intuition. Artificial intelligence (AI) has emerged as a…

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has…

Machine Learning · Computer Science 2024-07-26 Mohammad Karimzadeh , Deekshith Basvoju , Aleksandar Vakanski , Indrajit Charit , Fei Xu , Xinchang Zhang

Purpose- The significance of business processes has fostered a close collaboration between academia and industry. Moreover, the business landscape has witnessed continuous transformation, closely intertwined with technological advancements.…

Plastic injection molding remains essential to modern manufacturing. However, optimizing process parameters to balance product quality and profitability under dynamic environmental and economic conditions remains a persistent challenge.…

Artificial Intelligence · Computer Science 2025-05-19 Joon-Young Kim , Jecheon Yu , Heekyu Kim , Seunghwa Ryu
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