Many-body Green’s functions theory within the GW approximation and the Bethe-Salpeter Equation (BSE) is implemented in the open-source VOTCA-XTP software, aiming at the calculation of electronically excited states in complex molecular environments. Based on Gaussian-type atomic orbitals and making use of resolution of identity techniques, the code is designed specifically for nonperiodic systems. Application to a small molecule reference set successfully validates the methodology and its implementation for a variety of excitation types covering an energy range from 2 to 8 eV in single molecules. Further, embedding each GW-BSE calculation into an atomistically resolved surrounding, typically obtained from Molecular Dynamics, accounts for effects originating from local fields and polarization. Using aqueous DNA as a prototypical system, different levels of electrostatic coupling between the regions in this GW-BSE/MM setup are demonstrated. Particular attention is paid to charge-transfer (CT) excitations in adenine base pairs. It is found that their energy is extremely sensitive to the specific environment and to polarization effects. The calculated redshift of the CT excitation energy compared to a nucelobase dimer treated in vacuum is of the order of 1 eV, which matches expectations from experimental data. Predicted lowest CT energies are below that of a single nucleobase excitation, indicating the possibility of an initial (fast) decay of such an UV excited state into a binucleobase CT exciton. The results show that VOTCA-XTP’s GW-BSE/MM is a powerful tool to study a wide range of types of electronic excitations in complex molecular environments.

We present the open-source VOTCA-XTP software for the calculation of the excited-state electronic structure of molecules using many-body Green's functions theory in the GW approximation with the Bethe-Salpeter Equation (BSE). This work provides a summary of the underlying theory and discusses details of its implementation based on Gaussian orbitals, including, i.a., resolution-of-identity techniques, different approaches to the frequency integration of the self-energy or acceleration by offloading compute-intensive matrix operations using GPUs in a hybrid OpenMP/Cuda scheme. A distinctive feature of VOTCA-XTP is the capability to couple the calculation of electronic excitations to a classical polarizable environment on atomistic level in a coupled quantum-and molecular-mechanics (QM/MM) scheme, where a complex morphology can be imported from Molecular Dynamics simulations. The capabilities and limitations of the GW -BSE implementation are illustrated with two examples. First, we study the dependence of optically active electron-hole excitations in a series of diketopyrrolopyrrole-based oligomers on molecular-architecture modifications and the number of repeat units. Second, we use the GW -BSE/MM setup to investigate the effect of polarization on localized and intermolecular charge-transfer excited states in morphologies of low-donor content rubrenefullerene mixtures. These showcases demonstrate that our implementation currently allows to treat systems with up to 2500 basis functions on regular shared-memory workstations, providing accurate descriptions of quasiparticle and coupled electron-hole excited states of various character on an equal footing.

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A detailed study of agglomeration in composite materials containing carbon nanotubes (CNT) is presented. Three dimensional samples with different degrees of agglomeration were created in three different ways, leading to a wider range of geometries available to study. Virtual charges are injected into the computer-generated samples and move through these samples according to a Monte Carlo hopping algorithm. Results show that there is an optimal level of agglomeration that is actually beneficial for charge transport at low volume concentrations, lowering the percolation threshold. It is found that near percolation, a more uniform CNT distribution (less agglomeration) leads to more conductive paths, but with a lower mobility. The optimum level of agglomeration comes from a trade off between these two properties. Beyond this optimum agglomeration state, it is observed that conductivity tends to decrease as dispersion increases at all concentrations studied here. At high concentration (percolated samples), where CNT clumps merge, conductivity seems to be less sensitive to agglomeration.

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Thermal energy transfer at the interconnects in carbon based nanoelectronic devices plays a crucial role towards their performance as well as their reliability. In this study, we investigate such thermal energy transfer across physically interacting multi-wall carbon nanotubes (MWCNTs) as a function of their diameter, length, number of walls, inter-layer chirality differences, and different angular orientation of the cross-contact. Using non-equilibrium molecular dynamics simulations for phonon energy transfer, we predict that MWCNTs' curvature and their number of walls emerge as two critical factors, with each of them determining the limiting value of the thermal conductance across MWCNT contacts in different diameter regimes. For thinner MWCNTs, the curvature determines the limiting value of the conductance and leads to an interesting nonmonotonic character, while the number of walls dominates the contact conductance for large diameter MWCNTs. We discuss their respective origins and distinguish their governing regimes using several arguments -focusing of phonons, and confinement of the phonon focusing cone, large mean free path of graphite-and how they modulate radial thermal transport, leading to observed trends of thermal conductance across MWCNT contacts.

On the path to exascale the landscape of computer device architectures and corresponding programming models has become much more diverse. While various low-level performance portable programming models are available, support at the application level lacks behind. To address this issue, we present the performance portable block-structured adaptive mesh refinement (AMR) framework Parthenon, derived from the well-tested and widely used Athena++ astrophysical magnetohydrodynamics code, but generalized to serve as the foundation for a variety of downstream multi-physics codes. Parthenon adopts the Kokkos programming model, and provides various levels of abstractions from multidimensional variables, to packages defining and separating components, to launching of parallel compute kernels. Parthenon allocates all data in device memory to reduce data movement, supports the logical packing of variables and mesh blocks to reduce kernel launch overhead, and employs one-sided, asynchronous MPI calls to reduce communication overhead in multi-node simulations. Using a hydrodynamics miniapp, we demonstrate weak and strong scaling on various architectures including AMD and NVIDIA GPUs, Intel and AMD x86 CPUs, IBM Power9 CPUs, as well as Fujitsu A64FX CPUs. At the largest scale on Frontier (the first TOP500 exascale machine), the miniapp reaches a total of 1.7 × 1013 zone-cycles/s on 9216 nodes (73,728 logical GPUs) at [Formula: see text] weak scaling parallel efficiency (starting from a single node). In combination with being an open, collaborative project, this makes Parthenon an ideal framework to target exascale simulations in which the downstream developers can focus on their specific application rather than on the complexity of handling massively-parallel, device-accelerated AMR.