Chemistry Books

Any prospective teacher will say that studying for your teacher certification exam is nerve wracking. We have taken the pain out of the equation. Our team includes a textbook editor, college professors, and a biochemist. We have done all of the research, all you need to do is learn the material we generated. We even included problems within the chapters and a test at the back so you can check on your learning. Good luck!

The most comprehensive book I've seen for describing and explaining the whys, wherefores, and hows of the geology, chemistry and practical studio concerns of clay. As it is set up as a textbook, it would be great for college or university students who want to be sure they really know their ceramic science inside and out. It is readable and had many illustrations. One of the most interesting aspects for me is the repeated reference to the artist's reverse re-creation of the natural geologic process which form the clay. The chemistry all works in reverse as we form and fire our work. I think that's sort of romantic!

One and only kind of practical book. Every thing that we need to know regarding TCD waveforms are in here. Very easy to read and understand .Please read the Editorial to understand the importence of TCD and all the modern technical tools in the management of stroke and CNS problems in the current Era of modern medicine.

I took a course this summer (two semesters of chemistry in two months) where the required book was the ACS one. It was terrible, and I bought this book so that I could actually have a reference with actual facts in it (which the ACS book lacked).

However, I got SO much more out of this book than just as a mere reference. I never thought I'd say this about a textbook, but this book is actually a pleasure to read! The illustrations are appealing, the facts are organized in a concise manner so that you don't even really have to take notes (major concepts or facts tend to be listed as bullet points), and Chang has a way of pushing things a little farther than "necessary." A great book. Straightforward and to the point, but very accessible. If you want to teach yourself chemistry on your own, this is the book for you. If you got stuck with a bad textbook for a course (as I did), then again this is the book for you. (In all seriousness, all 40 people in my class ended up buying this - and loving it - after the first couple weeks of class).

It all boils down to this: do you want to learn chemistry? Then buy this book!

This is a very good book. Has a lot of relevant stuffs covered and it's at least light years ahead of similar books in terms of digestibility. Tightly-written yet not patronisingly simple. Check it out.

This book comes out with much anticipation from two of the world-renowned experts on nonlinear time series. Indeed, the once superhot chaos theory (cf The Theory of Chaotic Attractors) in physics and math in the 80s was only introduced to statistics by Howell Tong in his 1990 book on Non-Linear Time Series: A Dynamical System Approach (Oxford Statistical Science Series, Vol 6), H. Tong and R. L. Smith's 1992 RSS Chaos Day workshop and subsequent JRSS B special issue on chaos and L M Berliner and others's 1992 review articles in Statistical Science. Now 10 years after, what has achieved in between and what has not materialized as once seemed so promising? There are several PhD theses written in this area and there are continuing applications of chaos theory in science, from physics, mechanics, atmospheric sciences to biomedical and physiological data analysis. We can safely say that chaos theory is probably just another area or another tool that one can use to understand or interprete apparent randomness in simulations or in observed data. With purely stochastic tools that are dominant in modeling high-dimenional and un-parameterizable processes, chaos theory provides the crucial link between deterministic and computer modeling, and uncertainty in observed output and model simulations. Maybe with the ever closer collaboration between statisticians, mathematicians, and physical scientists in understanding and using the most daunting PDE and large scale models or computer models, chaos theory may finally come to be appreiated more by statisticians, who have traditionally been over-concerned with modeling noise, while overlooking modeling the overall deterministic patterns and structures in data.

Finally, some words about the book itself. I think it is a fairly comprehensive survey on the statistical work in the last decade, though understandably it is biased toward the authors' own research and collaborators' work. I think in order for it to be used as a textbook, it needs to be supplemented by a more balanced account of other aspects of chaos theory, such as geometrical theory and dimension reduction techniques. For example, the review chapter of dimension theory by C. Cutler in a book Dimension Estimation and Models (Nonlinear Time Series and Chaos, Vol 1) edited by H. Tong himself in 1990 (published by World Scientific) and Michael Kirby's recent book:Geometric Data Analysis: An Empirical Approach to Dimensionality Reduction and the Study of Patterns. The significance of fractal geometry theory on multivariate data analysis and time series statespace when the vector may lie on an manifold or lower-dimensional intrinsic space has recently been demonstrated by Z.Q. Lu in Nonparametric Regression With Singular Design in J. of Multivariate Analysis 1999, vol. 70, pp.177-201. It appears that the potentials of chaos theory for motivating newer statistical techniques and developing new statistical theory to understand better deterministic systems and related data analysis remain to be explored, see Modelling and Forecasting Financial Data: Techniques of Nonlinear Dynamics (Studies in Computational Finance, Volume 2) (Studies in Computational Finance). In conclusion, I warmly recomend this book to next generation students and time series lovers, and to scientists who might be wondering what statisticians are up to in this important area.

This is the first book that introduces a variety of characterizations techniques for nanomaterials:

Chapter 1. Nanomaterials for Nanoscience and Nanotechnology Chapter 2: X-ray characterization of nanoparticles Chapter 3: Transmission Electron Microscopy and Spectroscopy of Nanoparticles Chapter 4: Scanning Transmission Electron Microscopy of Nanoparticles Chapter 5: Scanning probe microscopy of nanoclusters Chapter 6. Electrical and electrochemical analysis of nanophase materials Chapter 7. Optical spectroscopy of nanophase materials Chapter 8: Nuclear Magnetic Resonance - characterization of self-assembled nanostructural materials Chapter 9: Photoluminescence from single semiconductor nanostructures Chapter 10: Nanomagnetism Chapter 11: Oxide and -sulfide nanocrystals and nanostructures Chapter 12: Electron Microscopy of Fullerenes and Related Materials

The book was organized in a way that serves the entire field from materials science, chemistry, physics to biology. If you are interested in nanotechnology, this is the first book you should start with.

Truly an epic work, this is by far the most interesting book on characterizing sources of indoor air pollution and related sink effects available today.

I thought I knew everything on this topic, but this book opened my eyes to a terrifying new area of the field.....

Electron transfer, a fundamental chemical process underlying all redox reactions, has been explained in detail, experimentally and theoretically.i have to say that it is an excellent book concerning quantum electrochemistry and quantum biology based on fundamental physics. After i have reviewed this book i wish i could be a electron, as a graduate student majoring electrochemistry.

And i wish i had cherished one, too.

This book contains a selected papers published in NLP. Papers describe current research in Thesaurus, IR, Multilingual IR and Corpus annotation.

This is a avaliable book for people interested in NLP research.