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Cell-Inspired Materials and Engineering (Hardcover, 1st ed. 2021): Dan Ohtan Wang, Daniel Packwood Cell-Inspired Materials and Engineering (Hardcover, 1st ed. 2021)
Dan Ohtan Wang, Daniel Packwood
R5,232 Discovery Miles 52 320 Ships in 12 - 17 working days

This book highlights cutting-edge studies in the development of cell-inspired biomaterials and synthetic materials that manipulate cell functions and provide the next generation with contemporary tools for treating complex human diseases. It explores the convergence of synthetic materials with cell and molecular biology and surveys how functional materials, when patterned with spatial and temporal precision, can be used effectively to maintain cell proliferation and phenotype in vitro, to trigger specific cell functions, and to redirect cell-fate decisions. Human stem cells are a frequently discussed subject in this book. This is an ideal book for students, cell biologists, researchers interested in interdisciplinary research, and biomedical engineers. This book also: Highlights successfully developed technologies in cell engineering that make possible new therapeutic development for previously untreatable conditions Covers topics including bio-inspired micro patterning, DNA origami technology, synthetic NOS inspired by compartmentalized signaling in cells, and light-induced depolarization of the cell membrane Illustrates in detail the use of stem cells and synthetic scaffolds to model ethically sensitive embryonic tissues and organs

Cell-Inspired Materials and Engineering (Paperback, 1st ed. 2021): Dan Ohtan Wang, Daniel Packwood Cell-Inspired Materials and Engineering (Paperback, 1st ed. 2021)
Dan Ohtan Wang, Daniel Packwood
R4,432 R4,052 Discovery Miles 40 520 Save R380 (9%) Out of stock

This book highlights cutting-edge studies in the development of cell-inspired biomaterials and synthetic materials that manipulate cell functions and provide the next generation with contemporary tools for treating complex human diseases. It explores the convergence of synthetic materials with cell and molecular biology and surveys how functional materials, when patterned with spatial and temporal precision, can be used effectively to maintain cell proliferation and phenotype in vitro, to trigger specific cell functions, and to redirect cell-fate decisions. Human stem cells are a frequently discussed subject in this book. This is an ideal book for students, cell biologists, researchers interested in interdisciplinary research, and biomedical engineers. This book also: Highlights successfully developed technologies in cell engineering that make possible new therapeutic development for previously untreatable conditions Covers topics including bio-inspired micro patterning, DNA origami technology, synthetic NOS inspired by compartmentalized signaling in cells, and light-induced depolarization of the cell membrane Illustrates in detail the use of stem cells and synthetic scaffolds to model ethically sensitive embryonic tissues and organs

Bayesian Optimization for Materials Science (Paperback, 1st ed. 2017): Daniel Packwood Bayesian Optimization for Materials Science (Paperback, 1st ed. 2017)
Daniel Packwood
R1,542 R1,455 Discovery Miles 14 550 Save R87 (6%) Out of stock

This book provides a short and concise introduction to Bayesian optimization specifically for experimental and computational materials scientists. After explaining the basic idea behind Bayesian optimization and some applications to materials science in Chapter 1, the mathematical theory of Bayesian optimization is outlined in Chapter 2. Finally, Chapter 3 discusses an application of Bayesian optimization to a complicated structure optimization problem in computational surface science.Bayesian optimization is a promising global optimization technique that originates in the field of machine learning and is starting to gain attention in materials science. For the purpose of materials design, Bayesian optimization can be used to predict new materials with novel properties without extensive screening of candidate materials. For the purpose of computational materials science, Bayesian optimization can be incorporated into first-principles calculations to perform efficient, global structure optimizations. While research in these directions has been reported in high-profile journals, until now there has been no textbook aimed specifically at materials scientists who wish to incorporate Bayesian optimization into their own research. This book will be accessible to researchers and students in materials science who have a basic background in calculus and linear algebra.

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