£138.38

About as cheap as it gets — within 5% of the all-time low it hit 1 month ago.

£138 today · all-time low £138 (Sep 2026) · usually £138

Springer Materials Informatics I: Methods - Computational Chemistry

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£143.99 £137.67 £139.05 £140.43 £141.81 £143.19 £144.57 27 July 2026 13 August 2026 30 August 2026 16 September 2026 03 October 2026
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Price Distribution

Price distribution over 69 days • 4 price levels

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Current Price
37 days · current 13 days 11 days 8 days 0 9 19 28 37 £139 £140 £142 £144 Days at Price

Price Analysis

Most common price: £139 (37 days, 53.6%)

Price range: £139 - £144

Price levels: 4 different prices over 69 days

Description

Materials Informatics I: Methods is the 39th volume in Springer's Challenges and Advances in Computational Chemistry and Physics series. This comprehensive resource explores computational approaches to materials science, bridging theoretical chemistry, physics, and data-driven methodologies. Designed for researchers, academics, and professionals in materials science and computational chemistry, the book presents advanced techniques for predicting material properties, optimizing compositions, and accelerating discovery cycles. The volume combines fundamental principles with practical applications, offering insights into how machine learning and informatics tools transform traditional materials research. Whether you are developing new compounds, improving existing materials, or designing high-performance substances, this Springer publication provides essential knowledge for implementing computational strategies in materials science and gaining competitive advantage in materials development.

Key Features

Part of Springer's established Challenges and Advances in Computational Chemistry and Physics series, volume 39, ensuring scholarly credibility and rigorous peer review.

Covers computational methods essential for materials science research, including molecular modelling, simulation techniques, and data analysis approaches.

Bridges computational chemistry and physics with practical informatics applications for materials discovery and optimisation.

Suitable for academic researchers, industry professionals, and students advancing their knowledge in computational materials science and related fields.

Offers systematic framework for applying machine learning and computational tools to accelerate materials development and property prediction.

Published by Springer, a leading international publisher of scientific and technical books in chemistry, physics, and materials science.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
03 April 2025
Listed Since
23 October 2024

Barcode

No barcode data available

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