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

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Modeling hardness of polycrystalline materials and bulk metallic glasses

Photovoltaic (PV) technologies for solar energy conversion represent promising routes to green and renewable energy generation. Despite relevant PV technologies being available for more than half a century, the production of solar energy remains costly, largely owing to low power conversion efficiencies of solar cells. The main difficulty in improving the efficiency of PV energy conversion lies in the spectral mismatch between the energy distribution of photons in the incident solar spectrum and the bandgap of a semiconductor material. In recent years, luminescent materials, which are capable of converting a broad spectrum of light into photons of a particular wavelength, have been synthesized and used to minimize the losses in the solar-cell-based energy conversion process. In this review, we will survey recent progress in the development of spectral converters, with a particular emphasis on lanthanide-based upconversion, quantum-cutting and down-shifting materials, for PV applications. In addition, we will also present technical challenges that arise in developing cost-effective high-performance solar cells based on these luminescent materials.

Enhancing solar cell efficiency: the search for luminescent materials as spectral converters

Owing to the unique mechanism of photoelectron storage and release, long persistent phosphorescence, also called long persistent luminescence or long lasting afterglow/phosphorescence, plays a pivotal role in the areas of spectroscopy, photochemistry, photonics and materials science. In recent years, more research has focused on the manipulation of the morphology, operational wavebands and persistent duration of long persistent phosphors (LPPs). These desired achievements stimulated the growing interest in designing bio-labels, photocatalysts, optical sensors, detectors and photonic devices. In this review, we present multidisciplinary research on synthetic methods, afterglow mechanisms, characterization techniques, materials system, and applications of LPPs. First, we introduce the recent developments in LPPs for the synthesis of nanoparticles from the aspects of particle sizes, monodispersity and homogeneity based on the urgent application of bio-imaging. In the later sections, we present the possible mechanisms, which involve the variation of trap distribution during the trapping and de-trapping process, complicated photo-ionization reaction of trap site levels and impurity centers together with their corresponding migration kinetics of carriers. Meanwhile, we emphasize the characterization techniques of defects, used to qualitatively or quantitatively describe the types, concentrations and depths of the traps. This review article also highlights the recent advances in suggested LPPs materials with a focus on the LPPs' hosts and optically active centers as well as their control, tuning and intrinsic links. We further discuss the classification of LPPs based on the different emission and excitation wavebands from the ultraviolet to the near-infrared region along with an overview of the activation mode of afterglow. Afterwards, we provide an exhibition of new products towards diverse application fields, including solar energy utilization, bio-imaging, diagnosis, and photocatalysts. Finally, we summarize the current achievements, discuss the problems and provide suggestions for potential future directions in the aforementioned parts.

Long persistent phosphors—from fundamentals to applications

Borosilicate glasses display a rich complexity of chemical behavior depending on the details of their composition and thermal history. Noted for their high chemical durability and thermal shock resistance, borosilicate glasses have found a variety of important uses from common household and laboratory glassware to high-tech applications such as liquid crystal displays. In this paper, we investigate the topological principles of borosilicate glass chemistry covering the extremes from pure borate to pure silicate end members. Based on NMR measurements, we present a two-state statistical mechanical model of boron speciation in which addition of network modifiers leads to a competition between the formation of nonbridging oxygen and the conversion of boron from trigonal to tetrahedral configuration. Using this model, we derive a detailed topological representation of alkali–alkaline earth–borosilicate glasses that enables the accurate prediction of properties such as glass transition temperature, liquid fragi...

Topological principles of borosilicate glass chemistry.

Understanding the composition dependence of glass hardness is of critical importance for both advanced glass applications and for revealing underlying fracture mechanisms. We present a topological approach for quantitative prediction of hardness in multicomponent glassy systems. We show that hardness is governed by the number of network constraints at room temperature and that a critical number of constraints is required for a material to display mechanical resistance. Applied to a series of soda lime borate glasses, the predicted values of hardness are in excellent agreement with experimental measurements. Our approach is generally applicable to any network glass and demonstrates the importance of accounting for the temperature dependence of the network constraints.

Prediction of Glass Hardness Using Temperature-Dependent Constraint Theory

Functional glasses play a critical role in current and developing technologies. These materials have traditionally been designed empirically through trial-and-error experimentation. However, here we report recent advancements in the design of new glass compositions starting at the atomic level, which have become possible through an unprecedented level of understanding of glass physics and chemistry. For example, new damage-resistant glasses have been developed using models that predict both manufacturing-related attributes (e.g., viscosity, liquidus temperature, and refractory compatibility), as well as the relevant end-use properties of the glass (e.g., elastic moduli, compressive stress, and damage resistance). We demonstrate how this approach can be used to accelerate the design of new industrial glasses for use in various applications. Through a combination of models at different scales, from atomistic through empirical modeling, it is now possible to decode the “glassy genome” and efficiently design ...

Accelerating the Design of Functional Glasses through Modeling

The computational design of new materials has long been a “holy grail” within the materials chemistry community. However, accurate prediction of glass properties from first principles is often impossible, because of computational restrictions. Here, we present an alternative analytical modeling approach that focuses on the topology of the glass network. Specifically, we demonstrate the use of a temperature-dependent constraint model to enable accurate prediction of dynamic properties, taking the ternary soda−lime−borate glassy system as an example. Borate glasses have posed a particular challenge for traditional molecular dynamics simulations, because of the change in boron coordination that occurs in the presence of network modifiers. Focusing on topological constraints instead of interatomic force fields, the calculated compositional trends with our model are in quantitative agreement with experimental measurements. Our modeling approach enables the exploration of new composition spaces of glassy materi...

Quantitative Design of Glassy Materials Using Temperature-Dependent Constraint Theory

Addition of alumina to sodium silicate glasses considerably improves the mechanical properties and chemical durability and changes other properties such as ionic conductivity and melt viscosity. As a result, aluminosilicate glasses find wide industrial and technological applications including the recent Corning® Gorilla® Glass. In this paper, the structures of sodium aluminosilicate glasses with a wide range of Al/Na ratios (from 1.5 to 0.6) have been studied using classical molecular dynamics simulations in a system containing around 3000 atoms, with the aim to understand the structural role of aluminum as a function of chemical composition in these glasses. The short- and medium-range structures such as aluminum coordination, bond angle distribution around cations, Qn distribution (n bridging oxygen per network forming tetrahedron), and ring size distribution have been systematically studied. In addition, the mechanical properties including bulk, shear, and Young's moduli have been calculated and compar...

Morten Mattrup Smedskjær

Papers

Topological principles of borosilicate glass chemistry.

Prediction of Glass Hardness Using Temperature-Dependent Constraint Theory

Accelerating the Design of Functional Glasses through Modeling

Quantitative Design of Glassy Materials Using Temperature-Dependent Constraint Theory

Structure and properties of sodium aluminosilicate glasses from molecular dynamics simulations