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Peter Maurer

Bio: Peter Maurer is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 202 citations.

Papers
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01 Jan 2016
TL;DR: The introduction to statistical thermodynamics is universally compatible with any devices to read and will help you to get the most less latency time to download any of the authors' books like this one.
Abstract: Thank you very much for reading introduction to statistical thermodynamics. Maybe you have knowledge that, people have search hundreds times for their favorite books like this introduction to statistical thermodynamics, but end up in harmful downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their laptop. introduction to statistical thermodynamics is available in our digital library an online access to it is set as public so you can download it instantly. Our book servers saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the introduction to statistical thermodynamics is universally compatible with any devices to read.

242 citations


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Journal ArticleDOI
TL;DR: The atomic simulation environment (ASE) provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.
Abstract: The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple "for-loop" construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

2,282 citations

Journal ArticleDOI
TL;DR: This review will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins.
Abstract: Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

474 citations

Journal ArticleDOI
TL;DR: An overview of the major known and proposed strategies for hydrogen adsorbents is provided, with the aim of guiding ongoing research as well as future new storage concepts.
Abstract: Nanoporous adsorbents are a diverse category of solid-state materials that hold considerable promise for vehicular hydrogen storage. Although impressive storage capacities have been demonstrated for several materials, particularly at cryogenic temperatures, materials meeting all of the targets established by the U.S. Department of Energy have yet to be identified. In this Perspective, we provide an overview of the major known and proposed strategies for hydrogen adsorbents, with the aim of guiding ongoing research as well as future new storage concepts. The discussion of each strategy includes current relevant literature, strengths and weaknesses, and outstanding challenges that preclude implementation. We consider in particular metal–organic frameworks (MOFs), including surface area/volume tailoring, open metal sites, and the binding of multiple H2 molecules to a single metal site. Two related classes of porous framework materials, covalent organic frameworks (COFs) and porous aromatic frameworks (PAFs), are also discussed, as are graphene and graphene oxide and doped porous carbons. We additionally introduce criteria for evaluating the merits of a particular materials design strategy. Computation has become an important tool in the discovery of new storage materials, and a brief introduction to the benefits and limitations of computational predictions of H2 physisorption is therefore presented. Finally, considerations for the synthesis and characterization of hydrogen storage adsorbents are discussed.

140 citations

Journal ArticleDOI
TL;DR: In this paper, the hydrogen capacities of 5309 MOFs drawn from databases of known compounds were predicted using empirical (Chahine rule) correlations and direct atomistic simulations, and IRMOF-20 was experimentally demonstrated to exhibit an uncommon combination of high usable volumetric and gravimetric capacities.
Abstract: Metal organic frameworks (MOFs) are promising materials for the storage of hydrogen fuel due to their high surface areas, tunable properties, and reversible gas adsorption. Although several MOFs are known to exhibit high hydrogen densities on a gravimetric basis, realizing high volumetric capacities – a critical attribute for maximizing the driving range of fuel cell vehicles – remains a challenge. Here, MOFs that achieve high gravimetric and volumetric H2 densities simultaneously are identified computationally, and demonstrated experimentally. The hydrogen capacities of 5309 MOFs drawn from databases of known compounds were predicted using empirical (Chahine rule) correlations and direct atomistic simulations. A critical assessment of correlations between these methods, and with experimental data, identified pseudo-Feynman–Hibbs-based grand canonical Monte Carlo calculations as the most accurate predictive method. Based on these predictions, promising MOF candidates were synthesized and evaluated with respect to their usable H2 capacities. Several MOFs predicted to exhibit high capacities displayed low surface areas upon activation, highlighting the need to understand the factors that control stability. Consistent with the computational predictions, IRMOF-20 was experimentally demonstrated to exhibit an uncommon combination of high usable volumetric and gravimetric capacities. Importantly, the measured capacities exceed those of the benchmark compound MOF-5, the record-holder for combined volumetric/gravimetric performance. Our study illustrates the value of computational screening in pinpointing materials that optimize overall storage performance.

104 citations