Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

We present the theoretical and technical foundations of the Amsterdam Density Functional (ADF) program with a survey of the characteristics of the code (numerical integration, density fitting for the Coulomb potential, and STO basis functions). Recent developments enhance the efficiency of ADF (e.g., parallelization, near order-N scaling, QM/MM) and its functionality (e.g., NMR chemical shifts, COSMO solvent effects, ZORA relativistic method, excitation energies, frequency-dependent (hyper)polarizabilities, atomic VDD charges). In the Applications section we discuss the physical model of the electronic structure and the chemical bond, i.e., the Kohn–Sham molecular orbital (MO) theory, and illustrate the power of the Kohn–Sham MO model in conjunction with the ADF-typical fragment approach to quantitatively understand and predict chemical phenomena. We review the “Activation-strain TS interaction” (ATS) model of chemical reactivity as a conceptual framework for understanding how activation barriers of various types of (competing) reaction mechanisms arise and how they may be controlled, for example, in organic chemistry or homogeneous catalysis. Finally, we include a brief discussion of exemplary applications in the field of biochemistry (structure and bonding of DNA) and of time-dependent density functional theory (TDDFT) to indicate how this development further reinforces the ADF tools for the analysis of chemical phenomena. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 931–967, 2001

Chemistry with ADF

Energy harvested directly from sunlight offers a desirable approach toward fulfilling, with minimal environmental impact, the need for clean energy. Solar energy is a decentralized and inexhaustible natural resource, with the magnitude of the available solar power striking the earth’s surface at any one instant equal to 130 million 500 MW power plants.1 However, several important goals need to be met to fully utilize solar energy for the global energy demand. First, the means for solar energy conversion, storage, and distribution should be environmentally benign, i.e. protecting ecosystems instead of steadily weakening them. The next important goal is to provide a stable, constant energy flux. Due to the daily and seasonal variability in renewable energy sources such as sunlight, energy harvested from the sun needs to be efficiently converted into chemical fuel that can be stored, transported, and used upon demand. The biggest challenge is whether or not these goals can be met in a costeffective way on the terawatt scale.2

http://pubs.acs.org/doi/pdf/10.1021/cr1002326

Solar Water Splitting Cells

BACKGROUND With a rising global population, increasing energy demands, and impending climate change, major concerns have been raised over the security of our energy future. Developing sustainable, fossil-free pathways to produce fuels and chemicals of global importance could play a major role in reducing carbon dioxide emissions while providing the feedstocks needed to make the products we use on a daily basis. One prospective goal is to develop electrochemical conversion processes that can convert molecules in the atmosphere (e.g., water, carbon dioxide, and nitrogen) into higher-value products (e.g., hydrogen, hydrocarbons, oxygenates, and ammonia) by coupling to renewable energy. Electrocatalysts play a key role in these energy conversion technologies because they increase the rate, efficiency, and selectivity of the chemical transformations involved. Today’s electrocatalysts, however, are inadequate. The grand challenge is to develop advanced electrocatalysts with the enhanced performance needed to enable widespread penetration of clean energy technologies. ADVANCES Over the past decade, substantial progress has been made in understanding several key electrochemical transformations, particularly those that involve water, hydrogen, and oxygen. The combination of theoretical and experimental studies working in concert has proven to be a successful strategy in this respect, yielding a framework to understand catalytic trends that can ultimately provide rational guidance toward the development of improved catalysts. Catalyst design strategies that aim to increase the number of active sites and/or increase the intrinsic activity of each active site have been successfully developed. The field of hydrogen evolution, for example, has seen important breakthroughs over the years in the development of highly active non–precious metal catalysts in acid. Notable advancements have also been made in the design of oxygen reduction and evolution catalysts, although there remains substantial room for improvement. The combination of theory and experiment elucidates the remaining challenges in developing further improved catalysts, often involving scaling relations among reactive intermediates. This understanding serves as an initial platform to design strategies to circumvent technical obstacles, opening up opportunities and approaches to develop higher-performance electrocatalysts for a wide range of reactions. OUTLOOK A systematic framework of combining theory and experiment in electrocatalysis helps to uncover broader governing principles that can be used to understand a wide variety of electrochemical transformations. These principles can be applied to other emerging and promising clean energy reactions, including hydrogen peroxide production, carbon dioxide reduction, and nitrogen reduction, among others. Although current paradigms for catalyst development have been helpful to date, a number of challenges need to be successfully addressed in order to achieve major breakthroughs. One important frontier, for example, is the development of both experimental and computational methods that can rapidly elucidate reaction mechanisms on broad classes of materials and in a wide range of operating conditions (e.g., pH, solvent, electrolyte). Such efforts would build on current frameworks for understanding catalysis to provide the deeper insights needed to fine-tune catalyst properties in an optimal manner. The long-term goal is to continue improving the activity and selectivity of these catalysts in order to realize the prospects of using renewable energy to provide the fuels and chemicals that we need for a sustainable energy future.

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Combining theory and experiment in electrocatalysis: Insights into materials design

TiO2 photocatalysis and related surface phenomena

Electrolysis of water on oxide surfaces

The oxidation and photo-oxidation of water on the rutile TiO2(110) surface is investigated using density functional theory (DFT) calculations. We investigate the relative stability of different surface terminations of TiO2 interacting with H2O and analyze the overpotential needed for the electrolysis and photoelectrolysis of water. We found that the most difficult step in the splitting of water process is the reaction of a H2O molecule with a vacancy in the surface to form an adsorbed hydroxyl group (OH*). Comparison to experiment shows that the computed overpotential for O2 evolution (0.78 V) is available under the experimental conditions required for both oxygen and hydrogen evolution.

Oxidation and Photo-Oxidation of Water on TiO2 Surface

Within the harmonic approximation to transition state theory, the biggest challenge involved in finding the mechanism or rate of transitions is the location of the relevant saddle points on the multidimensional potential energy surface. The saddle point search is particularly challenging when the final state of the transition is not specified. In this article we report on a comparison of several methods for locating saddle points under these conditions and compare, in particular, the well-established rational function optimization (RFO) methods using either exact or approximate Hessians with the more recently proposed minimum mode following methods where only the minimum eigenvalue mode is found, either by the dimer or the Lanczos method. A test problem involving transitions in a seven-atom Pt island on a Pt(111) surface using a simple Morse pairwise potential function is used and the number of degrees of freedom varied by varying the number of movable atoms. In the full system, 175 atoms can move so 525 degrees of freedom need to be optimized to find the saddle points. For testing purposes, we have also restricted the number of movable atoms to 7 and 1. Our results indicate that if attempting to make a map of all relevant saddle points for a large system (as would be necessary when simulating the long time scale evolution of a thermal system) the minimum mode following methods are preferred. The minimum mode following methods are also more efficient when searching for the lowest saddle points in a large system, and if the force can be obtained cheaply. However, if only the lowest saddle points are sought and the calculation of the force is expensive but a good approximation for the Hessian at the starting position of the search can be obtained at low cost, then the RFO approaches employing an approximate Hessian represent the preferred choice. For small and medium sized systems where the force is expensive to calculate, the RFO approaches employing an approximate Hessian is also the more efficient, but when the force and Hessian can be obtained cheaply and only the lowest saddle points are sought the RFO approach using an exact Hessian is the better choice. These conclusions have been reached based on a comparison of the total computational effort needed to find the saddle points and the number of saddle points found for each of the methods. The RFO methods do not perform very well with respect to the latter aspect, but starting the searches further away from the initial minimum or using the hybrid RFO version presented here improves this behavior considerably in most cases.

/pdf/comparison-of-methods-for-finding-saddle-points-without-24rw9x6qi8.pdf

Comparison of methods for finding saddle points without knowledge of the final states

Methods for accurately computing the interaction of molecules with metal surfaces are critical to understanding and thereby improving heterogeneous catalysis. We introduce an implementation of the specific reaction parameter (SRP) approach to density functional theory (DFT) that carries the method forward from a semiquantitative to a quantitative description of the molecule-surface interaction. Dynamics calculations on reactive scattering of hydrogen from the copper (111) surface using an SRP-DFT potential energy surface reproduce data on the dissociative adsorption probability as a function of incidence energy and reactant state and data on rotationally inelastic scattering with chemical accuracy (within ~4.2 kilojoules per mole).

https://science.sciencemag.org/content/sci/326/5954/832.full.pdf

Geert-Jan Kroes

Papers

Electrolysis of water on oxide surfaces

Oxidation and Photo-Oxidation of Water on TiO2 Surface

Comparison of methods for finding saddle points without knowledge of the final states

Chemically accurate simulation of a prototypical surface reaction: H2 dissociation on Cu(111).

Six-dimensional quantum dynamics of dissociative chemisorption of H2 on metal surfaces