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At least 343 records · Page 19

Ab Initio Computation of Rotationally-Averaged Pump–Probe X-ray and Electron Diffraction Signals

We develop a new algorithm for the computation of the rotationally averaged elastic molecular diffraction signal for the cases of perpendicular or parallel pump–probe geometries. The algorithm first collocates the charge density from an arbitrary ab initio wave function onto a Becke quadrature grid [A. Becke, J. Chem. Phys. 1988, 88, 2457], providing a high-fidelity multiresolution representation of the charge density. A double sum is then performed over the Becke grid points, and the interaction between points computed using the scattering kernels of Williamson and Zewail [J. C. Williamson and A. H. Zewail, J. Phys. Chem. 1994, 98, 2766]. These kernels analytically average over the molecular orientations with the cos 2 γ selection factor appropriate for one-photon dipole absorption in a perpendicular pump–probe geometry. We demonstrate that the method is converged with small grids containing <500 points/atom. We implement the algorithm on a GPU for increased efficiency and emonstrate the algorithm for molecules with up to a few dozen atoms. We explore the accuracy of the independent atom model (IAM) by comparison with our new and more accurate method. We also investigate the possibility of detecting signatures of electronic transitions in polyatomic pump–probe diffraction experiments.

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Quantitative resonant soft x-ray reflectivity of ultrathin anisotropic organic layers: Simulation and experiment of PTCDA on Au

Resonant soft X-ray reflectivity at the carbon K edge, with linearly polarized light, was used to derive quantitative information of film morphology, molecular arrangement, and electronic orbital anisotropies of an ultrathin 3,4,9,10-perylene tetracarboxylic dianhydride (PTCDA) film on Au(111). The experimental spectra were simulated by computing the propagation of the electromagnetic field in a trilayer system (vacuum/PTCDA/Au), where the organic film was treated as an anisotropic medium. Optical constants were derived from the calculated (through density functional theory) absorption cross sections of the single molecule along the three principal molecular axes. These were used to construct the dielectric tensor of the film, assuming the molecules to be lying flat with respect to the substrate and with a herringbone arrangement parallel to the substrate plane. Resonant soft X-ray reflectivity proved to be extremely sensitive to film thickness, down to the single molecular layer. The best agreement between simulation and experiment was found for a film of 1.6 nm, with flat laying configuration of the molecules. The high sensitivity to experimental geometries in terms of beam incidence and light polarization was also clarified through simulations. The optical anisotropies of the organic film were experimentally determined and through the comparison with calculations, it was possible to relate them to the orbital symmetry of the empty electronic states.

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Computational Astrophysics Consortium (2006 - 2013)

The Computational Astrophysics Consortium was a SciDAC Science Application Project that operated during the period 2006 - 2013. The collaboration was headed by Stan Woosley at UC Santa Cruz, and (initially) included partners at UC Berkeley (UCB), LLNL, LANL, LBNL, Stonybrook, Arizona, Stanford, and Johns Hopkins. This report summarizes activities at UCB over the project period. More detailed information about the project accomplishments can be found in the collaboration final report submitted by PI Stan Woosley, and attached to this document. The CAC effort at UCB was originally led by PI Chris Mckee, and included participating faculty members Jon Arons, Peter Nugent, and Eliot Quataert. In 2010, Daniel Kasen moved from UCSC to a faculty position at UCB, and took over as UCB institution PI. The project supported several graduate students (Michael Childress, Siva Dharba, Andrew Myers, Janos Botyanszki, Jeffery Silverman) and postdocs (Dovi Poznanski, Antonino Cucchiarra, Jeffrey Oishi, Bradley Cenko, Eric Hsiao and Jason Dexter). Several codes were further developed by the UCB CAC group. The Orion code is a 3-dimensional radiation hydrodynamics code, used by McKee’s group and often applied to problems in star formation. As part of the CAC, an adaptive ray tracing ionization scheme was implemented, and a chemistry solver was incorporated for coupling the ionization state of the gas to its thermodynamics. The Sedona code is 3-dimensional monte carlo radiation transport code for calculation the light curves and spectra. As part of the CAC, the physics of the code was improved and domain decomposition techniques were implemented for scaling on massively parallel systems.

79 ASTRONOMY AND ASTROPHYSICS↗

Non-Empirical and Self-Interaction Corrections for DFTB: Towards Accurate Quantum Simulations for Large Mesoscale Systems (Final Report)

This project was comprised of two complementary (but parallel) thrusts: (1) implementing massively-parallelized computing hardware (with new computational hardware that may replace GPUs) in the density functional tight binding (DFTB) approach and (2) developing new capabilities in DFTB to calculate the electronic structure and dynamics of large chemical systems. While classical molecular dynamics can handle hundreds of thousands of atoms, it cannot provide a first-principles based description of chemical systems at the quantum level. At the other extreme, conventional Kohn-Sham DFT methods can probe the true quantum mechanical nature of chemical systems; however, these methods cannot tackle the large sizes and length scales relevant to dynamics simulations of realistic systems. The DFTB formalism utilized in this project provides a viable approach for probing these large systems at a quantum mechanical level of detail. However, to utilize the DFTB approach for accurate calculations of electronic properties, it is crucial to incorporate quantum-based corrections in DFTB since exchange-correlation effects can still remain very strong in these large systems. At the same time, enhancing the computational efficiency of DFTB is also essential since optimal computational performance is required for addressing the large size scales associated with realistic chemical systems. As such, the new non-empirical corrections and computing hardware enhancements implemented in this project will enable accurate and computationally efficient approaches to directly probe electronic properties in these large, complex systems.

36 MATERIALS SCIENCE↗

Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals

In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and electronic gap of rutile titania nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Angstrom (24 atoms) to 10.3 Angstrom (384 atoms) using a highly-parallel real-space DFT code to enable hybrid level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy, and evaluate the influence of defects on electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Angstrom. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS is highly dependent on the shape and size of these particles. Furthermore, the DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigen value distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated.

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Insights into the Ring‐Opening of Biomass‐Derived Furanics over Carbon‐Supported Ruthenium

Abstract The selective ring‐opening of cellulose‐derived furanic molecules is a promising pathway for the production of industrially relevant linear oxygenates, such as 1,6‐hexanediol. 2,5‐Dimethylfuran (DMF) is employed as a model compound in a combined experimental and computational investigation to provide insights into the metal‐catalyzed ring‐opening. Ring‐opening to 2‐hexanol and 2‐hexanone and ring‐saturation to 2,5‐dimethyltetrahydrofuran (DMTHF) are identified as two main parallel pathways. DFT calculations and microkinetic modeling indicate that DMF adsorbs on Ru in an open‐ring configuration, which is potentially a common surface intermediate that leads to both ring‐opening and ring‐saturation products. Although the activation barriers for the two pathways are comparable, the formation of DMTHF is more thermodynamically favorable. In addition, steric interactions with co‐adsorbed 2‐propoxyl, derived from the solvent, and the oxophilic nature of Ru play key roles to determine the product distribution: the former favors less bulky, that is, ring‐closed, intermediates, and the latter retards O−H bond formation. Finally, we show that the hydrodeoxygenation of oxygenated furanics, such as 5‐methylfurfural and (5‐methyl‐2‐furyl)methanol, on Ru occurs preferentially at oxygen‐containing side groups to form DMF, followed by either ring‐opening or ring‐saturation.

Gilkey, Matthew J.↗

How the Size and Density of Charge-Transfer Excitons Depend on Heterojunction’s Architecture

We have characterized the size, intensity, density, and distribution of charge-transfer (CT) excitons as a function of the acceptor–donor architecture of prototypical organic interfaces. This characterization was done by computational analysis of 17 models of varying numbers, positions, and orientations of the donor and acceptor molecules. The models’ building blocks were phenyl-C61-butyric acid methyl ester (PCBM) fullerene acceptors and dual-band donor polymers composed of thiophene, benzothiadiazole, and benzotriazole subunits. The electronic structure of the donor–acceptor complexes was computed with the time-dependent long-range-corrected density-functional tight-binding method and analyzed with the fragment-based one-electron transition density matrix. In all models, the complexes with edge-on orientation have denser spectra of low-energy CT states lying below the absorption bands compared to the complexes with face-on orientation. This CT-state distribution in edge-on complexes provides a gate to efficiently populate cold CT excitons. Moreover, the cold CT excitons have a higher degree of charge separation in the edge-on than in the face-on complexes. The CT amount and the CT exciton size generally increase with the energy of the CT states, although the electron remains localized on a single molecule in cold CT states. Delocalization over two PCBM molecules was observed for high-energy CT states. The exciton size also depends on the orientation. Larger excitons are produced by the delocalization of the electrons perpendicularly to the interface. When the delocalization is parallel, the smaller electron–hole distances yield moderately sized CT excitons.

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Uncovering I/O demands on HPC platforms: Peeking under the hood of Santos Dumont

High-Performance Computing (HPC) platforms are required to solve the most diverse large-scale scientific problems in various research areas, such as biology, chemistry, physics, and health sciences. Researchers use a multitude of scientific softwares, which have different requirements. These include input and output operations, which directly impact performance due to the existing difference in processing and data access speeds. Thus, supercomputers must efficiently handle mixed workload when storing data from the applications. Understanding the set of applications and their performance running in a supercomputer is paramount to understanding the storage system's usage, pinpointing possible bottlenecks, and guiding optimization techniques. This research proposes a methodology and visualization tool to evaluate a supercomputer's data storage infrastructure's performance, taking into account the diverse workload and demands of the system over a long period of operation. As a study case, we focus on the Santos Dumont supercomputer, identifying inefficient usage, problematic performance factors, and providing guidelines on how to tackle those issues.

97 MATHEMATICS AND COMPUTING↗

Improved scaling of temperature-accelerated dynamics using localization

While temperature-accelerated dynamics (TAD) is a powerful method for carrying out non-equilibrium simulations of systems over extended time scales, the computational cost of serial TAD increases approximately as N{sup 3} where N is the number of atoms. In addition, although a parallel TAD method based on domain decomposition [Y. Shim et al., Phys. Rev. B 76, 205439 (2007)] has been shown to provide significantly improved scaling, the dynamics in such an approach is only approximate while the size of activated events is limited by the spatial decomposition size. Accordingly, it is of interest to develop methods to improve the scaling of serial TAD. As a first step in understanding the factors which determine the scaling behavior, we first present results for the overall scaling of serial TAD and its components, which were obtained from simulations of Ag/Ag(100) growth and Ag/Ag(100) annealing, and compare with theoretical predictions. We then discuss two methods based on localization which may be used to address two of the primary “bottlenecks” to the scaling of serial TAD with system size. By implementing both of these methods, we find that for intermediate system-sizes, the scaling is improved by almost a factor of N{sup 1/2}. Some additional possible methods to improve the scaling of TAD are also discussed.

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Acceleration of Semiempirical QM/MM Methods through Message Passage Interface (MPI), Hybrid MPI/Open Multiprocessing, and Self-Consistent Field Accelerator Implementations

The strategy and implementation of scalable and efficient semiempirical (SE) QM/MM methods in CHARMM are described. The serial version of the code was first profiled to identify routines that required parallelization. Afterward, the code was parallelized and accelerated with three approaches. The first approach was the parallelization of the entire QM/MM routines, including the Fock matrix diagonalization routines, using the CHARMM message passage interface (MPI) machinery. In the second approach, two different self-consistent field (SCF) energy convergence accelerators were implemented using density and Fock matrices as targets for their extrapolations in the SCF procedure. In the third approach, the entire QM/MM and MM energy routines were accelerated by implementing the hybrid MPI/open multiprocessing (OpenMP) model in which both the task- and loop-level parallelization strategies were adopted to balance loads between different OpenMP threads. The present implementation was tested on two solvated enzyme systems (including <100 QM atoms) and an S N 2 symmetric reaction in water. The MPI version exceeded existing SE QM methods in CHARMM, which include the SCC-DFTB and SQUANTUM methods, by at least 4-fold. The use of SCF convergence accelerators further accelerated the code by ~12–35% depending on the size of the QM region and the number of CPU cores used. Although the MPI version displayed good scalability, the performance was diminished for large numbers of MPI processes due to the overhead associated with MPI communications between nodes. This issue was partially overcome by the hybrid MPI/OpenMP approach which displayed a better scalability for a larger number of CPU cores (up to 64 CPUs in the tested systems).

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Liquid–Liquid Microfluidic Flows for Ultrafast 5-Hydroxymethyl Furfural Extraction

We study the effects of liquid–liquid flow patterns on the extraction of 5-hydroxymethyl furfural from the aqueous phase into an organic phase (methyl isobutyl ketone, ethyl acetate, and 2-pentanol) at ultrashort residence times of 0.2–20 s in a coiled capillary microchannel. Slug, droplet, slug-droplet, dispersed, parallel, annular, and irregular two-phase flow patterns are generated. We evaluate the extraction efficiency and the volumetric mass transfer coefficient via experiments and computational fluid dynamics (CFD). The CFD predictions are in quantitative agreement with the experimental data. The convective and diffusive contributions to the mass transfer of different flow patterns are analyzed. For all solvent pairs, the extraction efficiency varies irregularly with increasing flow rate due to changes in the mass transfer mechanism caused by a transition between flow regimes. Overall, we demonstrate >90% extraction efficiencies with high volumetric mass transfer coefficients ranging from 0.006 to 2.17 s–1. Furthermore, a merit index is defined to assess the trade-off between the fast mass transfer and the pressure drop in biphasic microchannels. In general, the mass transfer rate increases significantly at high flow rates at the expense of a high-pressure drop. Furthermore, the ethyl acetate/water irregular flow pattern is optimal due to a large throughput, extraction efficiency, and mass transfer coefficient, with a minimal pressure drop.

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A generalized Poisson and Poisson-Boltzmann solver for electrostatic environments

The computational study of chemical reactions in complex, wet environments is critical for applications in many fields. It is often essential to study chemical reactions in the presence of applied electrochemical potentials, taking into account the non-trivial electrostatic screening coming from the solvent and the electrolytes. As a consequence, the electrostatic potential has to be found by solving the generalized Poisson and the Poisson-Boltzmann equations for neutral and ionic solutions, respectively. In the present work, solvers for both problems have been developed. A preconditioned conjugate gradient method has been implemented for the solution of the generalized Poisson equation and the linear regime of the Poisson-Boltzmann, allowing to solve iteratively the minimization problem with some ten iterations of the ordinary Poisson equation solver. In addition, a self-consistent procedure enables us to solve the non-linear Poisson-Boltzmann problem. Both solvers exhibit very high accuracy and parallel efficiency and allow for the treatment of periodic, free, and slab boundary conditions. The solver has been integrated into the BigDFT and Quantum-ESPRESSO electronic-structure packages and will be released as an independent program, suitable for integration in other codes.

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Exploring Anomalous Photoelectron Angular Distributions in the Photoelectron Spectra of Gd 3 O 3 – : Study of Gd 3 O 2 – and Gd 3 O 3 – Using Photoelectron Spectroscopy and Density Functional Theory Calculations

Anion photoelectron (PE) spectra of lanthanide oxide clusters obtained previously have exhibited anomalous photoelectron angular distributions which were attributed to strong PE–valence electron (PEVE) interactions. Here, to further explore this effect, we have obtained the PE spectra of Gd 3 O 2 – and Gd 3 O 3 – , two clusters that have similarly complex electronic structures but contrasting symmetries. The spectra exhibit manifolds of detachment transitions at similar binding energies in a 0.5 eV window of energy. The electron affinity of Gd 3 O 2 is measured to be 1.29 ± 0.05 eV, and that of Gd 3 O 3 is 1.31 ± 0.05 eV. As seen in previous studies on lanthanide oxide cluster anions in lower than conventional oxidation states, transitions in spectra obtained lower photon energies are more congested than those obtained with higher photon energy, a signature of strong PEVE interactions. While the detachment transitions have predominantly parallel photoelectron angular distributions (PAD), the PAD varies across the manifold of transitions in the PE spectrum of Gd 3 O 3 – in a way that suggests four different subgroups of transitions. Results of calculations on Gd 3 O 2 – suggest kite or V-shape structures with antiferromagnetic coupling between one of the 4f 7 subshells with the two others. Calculations on Gd 3 O 3 – more definitively point to ring structures with a nearly isoenergetic ferromagnetically coupled high spin (24-tet) state and a dectet state in which one of the 4f 7 subshells is antiferromagnetically coupled with the other two. Taking these results as qualitative, we propose that strong mixing between the unperturbed states predicted computationally leads to overlapping transitions with different PADs.

anions↗

PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method

Abstract A new phase-field modeling framework with an emphasis on performance, flexibility, and ease of use is presented. Foremost among the strategies employed to fulfill these objectives are the use of a matrix-free finite element method and a modular, application-centric code structure. This approach is implemented in the new open-source PRISMS-PF framework. Its performance is enabled by the combination of a matrix-free variant of the finite element method with adaptive mesh refinement, explicit time integration, and multilevel parallelism. Benchmark testing with a particle growth problem shows PRISMS-PF with adaptive mesh refinement and higher-order elements to be up to 12 times faster than a finite difference code employing a second-order-accurate spatial discretization and first-order-accurate explicit time integration. Furthermore, for a two-dimensional solidification benchmark problem, the performance of PRISMS-PF meets or exceeds that of phase-field frameworks that focus on implicit/semi-implicit time stepping, even though the benchmark problem’s small computational size reduces the scalability advantage of explicit time-integration schemes. PRISMS-PF supports an arbitrary number of coupled governing equations. The code structure simplifies the modification of these governing equations by separating their definition from the implementation of the numerical methods used to solve them. As part of its modular design, the framework includes functionality for nucleation and polycrystalline systems available in any application to further broaden the phenomena that can be used to study. The versatility of this approach is demonstrated with examples from several common types of phase-field simulations, including coarsening subsequent to spinodal decomposition, solidification, precipitation, grain growth, and corrosion.

36 MATERIALS SCIENCE↗

Two-Fluid and Discrete Element Modeling of a Parallel Plate Fluidized Bed Heat Exchanger for Concentrating Solar Power

A novel high-temperature particle solar receiver is developed using a light trapping planar cavity configuration. As particles fall through the cavity, the concentrated solar radiation warms the boundaries of the receiver and in turn heats the particles. Particles flow through the system, forming a fluidized bed at the lower section, leaving the system from the bottom at a constant flowrate. Air is introduced to the system as the fluidizing medium to improve particle heat transfer and mixing. A laboratory scale cavity receiver is built by collaborators at the Colorado School of Mines and their data are used for model validation. In this experimental setup, near IR quartz lamp is used to provide flux to the vertical wall of the heat exchanger. The system is modeled using the discrete element method and a continuum two-fluid method. The computational model matches the experimental system size and the particle size distribution is assumed monodisperse. A new continuum conduction model that accounts for the effects of solid concentration is implemented, and the heat flux boundary condition matches the experimental setup. Radiative heat transfer is estimated using a widely used correlation during the post-processing step to determine an overall heat transfer coefficient. The model is validated against testing data and achieves less than 30% discrepancy and a heat transfer coefficient greater than 1000 W/m2 K.

concentrating solar power↗

Transport Studies and Modeling in PEM Fuel Cells

This project’s aim was to develop fuel cell components (i.e. membranes, gas-diffusion media (GDM), bipolar plates and flow fields) that possess specific properties (i.e. water transport and conductivity). A computational fluid dynamics model was developed to elucidate the effect of certain parameters on these specific properties. Ultimately, the model will be used to determine sensitivity of fuel cell performance to component properties to determine limiting components and to guide research. We have successfully reached our objectives and achieved most of the milestones of this project. We have designed and synthesized a variety of hydrocarbon block polymer membranes with lower equivalent weight, structure, chemistry, phase separation and process conditions. These membranes provide a broad selection with optimized water transport properties. We have also designed and constructed a variety of devices that are capable of accurately measuring the water transport properties (water uptake, water diffusivity and electro-osmatic drag) of these membranes. These transport properties are correlated to the membranes’ structures derived from X-ray and microscopy techniques to determine the structure-property relationship. We successfully integrated hydrocarbon membrane MEAs with a current distribution board (CBD) to study the impact of hydrocarbon membrane on water transport in fuel cells. We have designed and fabricated various GDM with varying substrate, diffusivity and micro-porous layers (MPL) and characterized their pore structure, tortuosity and hydrophobicity. We have derived a universal chart (MacMullin number as function of wet proofing and porosity) that can be used to characterize various GDM. The abovementioned GDMs have been evaluated in operating fuel cells; their performance is correlated to various pore structure, tortuosity and hydrophobicity of the GDM. Unfortunately, determining a universal relationship between the MacMullin number and these properties was not achieved. We have simulated fuel cell performance, current distribution and water distribution at various values of the water uptake, membrane diffusivity, and electro-osmotic drag coefficient (EODC) and compared modeling results with segmented-cell data for both serpentine and parallel flow-fields. We have developed iterations of fuel cell flow fields to achieve specific water transport and thermal management targets. This work demonstrated the importance of membrane diffusivity on fuel cell performance, the necessity of a high membrane diffusion coefficient, and the desirability of a low EODC at low levels of relative humidity.

08 HYDROGEN↗

A divide-conquer-recombine algorithmic paradigm for large spatiotemporal quantum molecular dynamics simulations

We introduce an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large quantum molecular dynamics (QMD) simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). In DCR, the DC phase constructs globally informed, overlapping local-domain solutions, which in the recombine phase are synthesized into a global solution encompassing large spatiotemporal scales. For the DC phase, we design a lean divide-and-conquer (LDC) DFT algorithm, which significantly reduces the prefactor of the O(N) computational cost for N electrons by applying a density-adaptive boundary condition at the peripheries of the DC domains. Our globally scalable and locally efficient solver is based on a hybrid real-reciprocal space approach that combines: (1) a highly scalable real-space multigrid to represent the global charge density; and (2) a numerically efficient plane-wave basis for local electronic wave functions and charge density within each domain. Hybrid space-band decomposition is used to implement the LDC-DFT algorithm on parallel computers. A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786 432 cores for a 50.3 × 10{sup 6}-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16 661 atoms is performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles. As an example of the recombine phase, LDC-DFT electronic structures are used as a basis set to describe global photoexcitation dynamics with nonadiabatic QMD (NAQMD) and kinetic Monte Carlo (KMC) methods. The NAQMD simulations are based on the linear response time-dependent density functional theory to describe electronic excited states and a surface-hopping approach to describe transitions between the excited states. A series of techniques are employed for efficiently calculating the long-range exact exchange correction and excited-state forces. The NAQMD trajectories are analyzed to extract the rates of various excitonic processes, which are then used in KMC simulation to study the dynamics of the global exciton flow network. This has allowed the study of large-scale photoexcitation dynamics in 6400-atom amorphous molecular solid, reaching the experimental time scales.

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Making many-body interactions nearly pairwise additive: The polarized many-body expansion approach

The Many-Body Expansion (MBE) is a useful tool to simulate condensed phase chemical systems, often avoiding the steep computational cost of usual electronic structure methods. However, it often requires higher than 2-body terms to achieve quantitative accuracy. In this work, we propose the Polarized MBE (PolBE) method where each MBE energy contribution is treated as an embedding problem. In each energy term, a smaller fragment is embedded into a larger, polarized environment and only a small region is treated at the high-level of theory using embedded mean-field theory. The role of polarized environment was found to be crucial in providing quantitative accuracy at the 2-body level. PolBE accurately predicts noncovalent interaction energies for a number of systems, including CO 2 , water, and hydrated ion clusters, with a variety of interaction mechanisms, from weak dispersion to strong electrostatics considered in this work. We further demonstrate that the PolBE interaction energy is predominantly pairwise unlike the usual vacuum MBE that requires higher-order terms to achieve similar accuracy. We numerically show that PolBE often performs better than other widely used embedded MBE methods such as the electrostatically embedded MBE. Finally,owing to the lack of expensive diagonalization of Fock matrices and its embarrassingly parallel nature, PolBE is a promising way to access condensed phase systems with hybrid density functionals that are difficult to treat with currently available methods.

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