Patrick Rinke

Bio: Patrick Rinke is an academic researcher from Aalto University. The author has contributed to research in topics: Density functional theory & Band gap. The author has an hindex of 60, co-authored 185 publications receiving 10384 citations. Previous affiliations of Patrick Rinke include Fritz Haber Institute of the Max Planck Society & Helsinki University of Technology.

Resolution-of-identity approach to Hartree?Fock, hybrid density functionals, RPA, MP2 and GW with numeric atom-centered orbital basis functions

Abstract: The efficient implementation of electronic structure methods is essential for first principles modeling of molecules and solids. We present here a particularly efficient common framework for methods beyond semilocal density-functional theory (DFT), including Hartree-Fock (HF), hybrid density functionals, random-phase approximation (RPA), second-order Moller-Plesset perturbation theory (MP2) and the GW method. This computational framework allows us to use compact and accurate numeric atom-centered orbitals (NAOs), popular in many implementations of semilocal DFT, as basis functions. The essence of our framework is to employ the 'resolution of identity (RI)' technique to facilitate the treatment of both the two-electron Coulomb repulsion integrals (required in all these approaches) and the linear density-response function (required for RPA and GW). This is possible because these quantities can be expressed in terms of the products of single-particle basis functions, which can in turn be expanded in a set of auxiliary basis functions (ABFs). The construction of ABFs lies at the heart of the RI technique, and we propose here a simple prescription for constructing ABFs which can be applied regardless of whether the underlying radial functions have a specific analytical shape

Hybrid functional studies of the oxygen vacancy in TiO 2

Abstract: The electronic and structural properties of the oxygen vacancy $({V}_{\text{O}})$ in rutile ${\text{TiO}}_{2}$ are studied using generalized Kohn-Sham theory with the Heyd, Scuseria, and Ernzerhof (HSE) hybrid functional for exchange and correlation. The HSE approach corrects the band gap and allows for a proper description of defects with energy levels close to the conduction band. According to the HSE calculations, ${V}_{\text{O}}$ is a shallow donor for which the $+2$ charge state is lower in energy than the neutral and $+1$ charge states for all Fermi-level positions in the band gap. The formation energy of ${V}_{\text{O}}^{2+}$ is relatively low in $n$-type ${\text{TiO}}_{2}$ under O-poor conditions but it rapidly increases with the oxygen chemical potential. This is consistent with experimental observations where the electrical conductivity decreases with oxygen partial pressure.

Indirect Auger recombination as a cause of efficiency droop in nitride light-emitting diodes

Abstract: InGaN-based light-emitting diodes(LEDs) exhibit a significant efficiency loss (droop) when operating at high injected carrier densities, the origin of which remains an open issue. Using atomistic first-principles calculations, we show that this efficiency droop is caused by indirect Auger recombination, mediated by electron-phonon coupling and alloy scattering. By identifying the origin of the droop, our results provide a guide to addressing the efficiency issues in nitride LEDs and the development of efficient solid-state lighting.

Resolution-of-identity approach to Hartree-Fock, hybrid density functionals, RPA, MP2, and \textit{GW} with numeric atom-centered orbital basis functions

Abstract: Efficient implementations of electronic structure methods are essential for first-principles modeling of molecules and solids. We here present a particularly efficient common framework for methods beyond semilocal density-functional theory, including Hartree-Fock (HF), hybrid density functionals, random-phase approximation (RPA), second-order Moller-Plesset perturbation theory (MP2), and the $GW$ method. This computational framework allows us to use compact and accurate numeric atom-centered orbitals (popular in many implementations of semilocal density-functional theory) as basis functions. The essence of our framework is to employ the "resolution of identity (RI)" technique to facilitate the treatment of both the two-electron Coulomb repulsion integrals (required in all these approaches) as well as the linear density-response function (required for RPA and $GW$). This is possible because these quantities can be expressed in terms of products of single-particle basis functions, which can in turn be expanded in a set of auxiliary basis functions (ABFs). The construction of ABFs lies at the heart of the RI technique, and here we propose a simple prescription for constructing the ABFs which can be applied regardless of whether the underlying radial functions have a specific analytical shape (e.g., Gaussian) or are numerically tabulated. We demonstrate the accuracy of our RI implementation for Gaussian and NAO basis functions, as well as the convergence behavior of our NAO basis sets for the above-mentioned methods. Benchmark results are presented for the ionization energies of 50 selected atoms and molecules from the G2 ion test set as obtained with $GW$ and MP2 self-energy methods, and the G2-I atomization energies as well as the S22 molecular interaction energies as obtained with the RPA method.

Random-phase approximation and its applications in computational chemistry and materials science

Abstract: The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.

Fast parallel algorithms for short-range molecular dynamics

Abstract: 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.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Pattern Recognition and Machine Learning

Abstract: 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.

Nano‐photocatalytic Materials: Possibilities and Challenges

Abstract: Semiconductor photocatalysis has received much attention as a potential solution to the worldwide energy shortage and for counteracting environmental degradation. This article reviews state-of-the-art research activities in the field, focusing on the scientific and technological possibilities offered by photocatalytic materials. We begin with a survey of efforts to explore suitable materials and to optimize their energy band configurations for specific applications. We then examine the design and fabrication of advanced photocatalytic materials in the framework of nanotechnology. Many of the most recent advances in photocatalysis have been realized by selective control of the morphology of nanomaterials or by utilizing the collective properties of nano-assembly systems. Finally, we discuss the current theoretical understanding of key aspects of photocatalytic materials. This review also highlights crucial issues that should be addressed in future research activities.