£127.59

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£128 today · previous high £128 · all-time low £105

Springer Artificial Intelligence for Materials Science - Springer Series 312

Amazon

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£127.59 £102.61 £108.06 £113.51 £118.96 £124.41 £129.86 28 July 2026 15 August 2026 02 September 2026 20 September 2026 08 October 2026
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9 days 64 days · current 0 16 32 48 64 £105 £128 Days at Price

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Most common price: £128 (64 days, 87.7%)

Price range: £105 - £128

Price levels: 2 different prices over 73 days

Description

Discover how machine learning transforms materials science research and development. This Springer Series volume explores cutting-edge methods for predicting properties of new compounds, reducing experimental costs, and accelerating discovery of advanced materials. Machine learning techniques enable researchers to explore unknown material structures efficiently, with predictions validated through experimental work. The book covers recent progress in integrating AI tools with materials science and engineering, including searchable and interactive databases that drive research on emerging materials. With high-quality materials property databases now available, this comprehensive guide presents essential knowledge for scientists and engineers seeking to leverage artificial intelligence for faster, more cost-effective materials innovation and development.

Key Features

Springer Series in Materials Science volume 312 covers machine learning applications specifically designed for materials science research and discovery.

Machine learning methods significantly reduce the cost and time required to explore new structures and unknown chemical compounds.

Interactive and searchable databases enable efficient research on emerging materials and accelerate access to high-quality materials property data.

Combines recent AI insights and tools developed for materials science engineering to bridge computational prediction and experimental validation.

Presents validated approaches for predicting reasonable material properties before conducting costly laboratory experiments.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 March 2021
Listed Since
19 December 2020

Barcode

No barcode data available

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