Results 21 to 30 of about 16,538,551 (301)
Small data machine learning in materials science
npj Computational Materials, 2023 This review discussed the dilemma of small data faced by materials machine learning. First, we analyzed the limitations brought by small data. Then, the workflow of materials machine learning has been introduced.
Pengcheng Xu +3 more
semanticscholar +1 more source
Green economy and waste management: An inevitable plan for materials science
Progress in Natural Science: Materials International, 2022 Covid is giving us many lessons among which one must be to realize that this is the time to act for sustainable future. The smart world around us has made it inevitable to have an alarming situation regarding the uncontrolled growth of waste products ...
S. Nandy, E. Fortunato, R. Martins
semanticscholar +1 more source
Opportunities and Challenges for Machine Learning in Materials Science [PDF]
Annual review of materials research (Print), 2020 Advances in machine learning have impacted myriad areas of materials science, such as the discovery of novel materials and the improvement of molecular simulations, with likely many more important developments to come.
D. Morgan, R. Jacobs
semanticscholar +1 more source
The Encyclopedia of the History of Science, 2020 Materials are everywhere. Imagine a common morning routine in the industrialized world. We arise from the synthetic sheets covering our memory-foam mattresses to cook our eggs in Teflon-coated pans while sipping coffee from ceramic mugs. We peer at newspapers through eyeglasses made from light-weight plastics with high refractive indexes. We commute to
Mody, Cyrus C. M., Martin, Joseph D.
openaire +4 more sources
Big data and machine learning for materials science
Discover Materials, 2021 Herein, we review aspects of leading-edge research and innovation in materials science that exploit big data and machine learning (ML), two computer science concepts that combine to yield computational intelligence.
J. F. Rodrigues +4 more
semanticscholar +1 more source
Kadi4Mat: A Research Data Infrastructure for Materials Science
Data Science Journal, 2021 The concepts and current developments of a research data infrastructure for materials science are presented, extending and combining the features of an electronic lab notebook and a repository.
Nico Brandt +7 more
semanticscholar +1 more source
Recent advances and applications of machine learning in solid-state materials science
npj Computational Materials, 2019 One of the most exciting tools that have entered the material science toolbox in recent years is machine learning. This collection of statistical methods has already proved to be capable of considerably speeding up both fundamental and applied research ...
Jonathan Schmidt +3 more
semanticscholar +1 more source
Digital Transformation in Materials Science: A Paradigm Change in Material's Development
Advances in Materials, 2021 The ongoing digitalization is rapidly changing and will further revolutionize all parts of life. This statement is currently omnipresent in the media as well as in the scientific community; however, the exact consequences of the proceeding digitalization
Julian Kimmig, S. Zechel, U. Schubert
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction Characterizing stressful events reported by childhood cancer survivors experienced throughout the lifespan may help improve trauma‐informed care relevant to the survivor experience. Methods Participants included 2552 survivors (54% female; 34 years of age) and 469 community controls (62% female; 33 years of age) from the St.
Megan E. Ware +13 more
wiley +1 more source