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دسته بندی:
یادگیری ماشین - machine learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Big Data Creates New Opportunities for Materials Research: A Review on Methods and Applications of Machine Learning for Materials Design
ترجمه فارسی عنوان مقاله:
داده های بزرگ فرصت های جدیدی را برای تحقیقات مواد ایجاد می کنند: مروری بر روش ها و کاربردهای یادگیری ماشین برای طراحی مواد
منبع:
Sciencedirect - Elsevier - Engineering, Corrected proof: doi:10:1016/j:eng:2019:02:011
نویسنده:
Teng Zhou a,b,⇑, Zhen Song a, Kai Sundmacher a,b
چکیده انگلیسی:
Materials development has historically been driven by human needs and desires, and this is likely to continue
in the foreseeable future. The global population is expected to reach ten billion by 2050, which will
promote increasingly large demands for clean and high-efficiency energy, personalized consumer products,
secure food supplies, and professional healthcare. New functional materials that are made and tailored
for targeted properties or behaviors will be the key to tackling this challenge. Traditionally,
advanced materials are found empirically or through experimental trial-and-error approaches. As big
data generated by modern experimental and computational techniques is becoming more readily available,
data-driven or machine learning (ML) methods have opened new paradigms for the discovery and
rational design of materials. In this review article, we provide a brief introduction on various ML methods
and related software or tools. Main ideas and basic procedures for employing ML approaches in materials
research are highlighted. We then summarize recent important applications of ML for the large-scale
screening and optimal design of polymer and porous materials, catalytic materials, and energetic materials.
Finally, concluding remarks and an outlook are provided.
Keywords: Big data | Data-driven | Machine learning | Materials screening | Materials design
قیمت: رایگان
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