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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Cyclopentadienyl coordination induces unexpected ionic Am-N bonding in an americium bipyridyl complex

Variations in bonding between trivalent lanthanides and actinides is critical for reprocessing spent nuclear fuel. The ability to tune bonding and the coordination environment in these trivalent systems is a key factor in identifying a solution for separating lanthanides and actinides. Coordination of 4,4'-bipyridine (4,4'-bpy) and trimethylsilylcyclopentadienide (Cp') to americium introduces unexpectedly ionic Am-N bonding character and unique spectroscopic properties. Here we report the structural characterization of (Cp' 3 Am) 2 (μ -4,4'-bpy) and its lanthanide analogue, (Cp' 3 Nd) 2 (μ - 4,4'-bpy), by single-crystal X-ray diffraction. Spectroscopic techniques in both solid and solution phase are performed in conjunction with theoretical calculations to probe the effects the unique coordination environment has on the electronic structure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Subaru Hyper Suprime-Cam Survey of Cygnus OB2 Complex – I. Introduction, photometry, and source catalogue

ABSTRACT Low-mass star formation inside massive clusters is crucial to understand the effect of cluster environment on processes like circumstellar disc evolution, planet, and brown dwarf formation. The young massive association of Cygnus OB2, with a strong feedback from massive stars, is an ideal target to study the effect of extreme environmental conditions on its extensive low-mass population. We aim to perform deep multiwavelength studies to understand the role of stellar feedback on the IMF, brown dwarf fraction and circumstellar disc properties in the region. We introduce here, the deepest and widest optical photometry of 1.5○ diameter region centred at Cygnus OB2 in r2, i2, z, and Y-filters, using Subaru Hyper Suprime-Cam (HSC). This work presents the data reduction, source catalogue generation, data quality checks, and preliminary results about the pre-main sequence sources. We obtain 713 529 sources in total, with detection down to ∼28, 27, 25.5, and 24.5 mag in r2, i2, z, and Y-band, respectively, which is ∼3 – 5 mag deeper than the existing Pan-STARRS and GTC/OSIRIS photometry. We confirm the presence of a distinct pre-main sequence branch by statistical field subtraction of the central 18 arcmin region. We find the median age of the region as ∼5 ± 2 Myr with an average disc fraction of ∼9 per cent. At this age, combined with A $_V\, \sim$ 6 – 8 mag, we detect sources down to a mass range of ∼0.01–0.17 M⊙. The deep HSC catalogue will serve as the groundwork for further studies on this prominent active young cluster.

Gupta, Saumya (ORCID:0000000161843958)↗
DOE OSTI2022

Changes in supramolecular organization of cyanobacterial thylakoid membrane complexes in response to far-red light photoacclimation

Cyanobacteria are ubiquitous in nature and have developed numerous strategies that allow them to live in a diverse range of environments. Certain cyanobacteria synthesize chlorophylls d and f to acclimate to niches enriched in far-red light (FRL) and incorporate paralogous photosynthetic proteins into their photosynthetic apparatus in a process called FRL-induced photoacclimation (FaRLiP). We characterized the macromolecular changes involved in FRL-driven photosynthesis and used atomic force microscopy to examine the supramolecular organization of photosystem I associated with FaRLiP in three cyanobacterial species. Mass spectrometry showed the changes in the proteome of Chroococcidiopsis thermalis PCC 7203 that accompany FaRLiP. Fluorescence lifetime imaging microscopy and electron microscopy reveal an altered cellular distribution of photosystem complexes and illustrate the cell-to-cell variability of the FaRLiP response.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract Background Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. Results Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. Conclusions This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Investigating and Optimizing the Lysate-Based Expression of Nonribosomal Peptide Synthetases Using a Reporter System

Lysate-based cell-free expression (CFE) systems are accessible platforms for expressing proteins that are difficult to synthesize in vivo, such as nonribosomal peptide synthetases (NRPSs). NRPSs are large (>100 kDa), modular enzyme complexes that synthesize bioactive peptide natural products. This synthetic process is analogous to transcription/translation (TX/TL) in lysates, resulting in potential resource competition between NRPS expression and NRPS activity in cell-free environments. Moreover, CFE conditions depend on the size and structure of the protein. Here, a reporter system for rapidly investigating and optimizing reaction environments for NRPS CFE is described. This strategy is demonstrated in E. coli lysate reactions using blue pigment synthetase A (BpsA), a model NRPS, carrying a C-terminal tetracysteine (TC) tag which forms a fluorescent complex with the biarsenical dye, FlAsH. A colorimetric assay was adapted for lysate reactions to detect the blue pigment product, indigoidine, of cell-free expressed BpsA-TC, confirming that the tagged enzyme is catalytically active. An optimized protocol for end point TC/FlAsH complex measurements in reactions enables quick comparisons of full-length BpsA-TC expressed under different reaction conditions, defining unique requirements for NRPS expression that are related to the protein’s catalytic activity and size. Importantly, these protein-dependent CFE conditions enable higher indigoidine titer and improve the expression of other monomodular NRPSs. Notably, these conditions differ from those used for the expression of superfolder GFP (sfGFP), a common reporter for optimizing lysate-based CFE systems, indicating the necessity for tailored reporters to optimize expression for specific enzyme classes. In conclusion, the reporter system is anticipated to advance lysate-based CFE systems for complex enzyme synthesis, enabling natural product discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fiberboard Properties and Degradation Rates for Storage of 9975 Shipping Package in KAC (2022 Status Report)

Thermal, mechanical, and physical properties have been measured on fiberboard samples following accelerated aging for up to 17 years. The aging environments include elevated temperature up to 250 °F (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions. KAC completed calculations that supported extending the service life of 9975 packages with 3013 containers in storage from 20 years to 40 years. These calculations addressed the potential for degraded fiberboard properties following 40 years in storage using degradation models developed previously. Due to differences in containers, 9975 packages with non-3013 containers are only approved for 20 years of storage. The updated degradation models developed in this report have been compared to the assumptions in those calculations, and the current results for fiberboard dimensions, density, radial thermal conductivity, and energy absorption remain consistent with those calculations. The axial thermal conductivity degradation rate slightly exceeds calculations estimate of 0.5% per year between 130 and 160 °F. Additional data will continue to be collected to permit future refinements to the models and assumptions. Some of the predicted degradation rates presented in this report are extreme. However, these relate to environments that do not exist within KAC or would be postulated only as upset conditions that would not likely persist for an extended period. For a typical package stored in KAC with approximately 10-12 watts internal heat load or less, and ambient temperatures below 90 °F, the fiberboard assemblies experience storage conditions less severe than any of the aging environments. Fiberboard in conforming packages with lower internal heat loads should experience little or no degradation and is expected to provide a service life beyond the currently approved 40 year storage period. Packages with higher internal heat loads may not continue to perform their required safety functions beyond 40 years. Ultimately, service life will be determined by the cumulative effect of degradation from all the conditions these packages might encounter. The results and model predictions presented in this report are applicable to 9975 packages with cane or softwood fiberboard overpack assemblies. These degradation models do not address the effects of non-conforming conditions such as the presence of excess moisture and mold or beetle infestations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Magnetotactic Bacteria Accumulate a Large Pool of Iron Distinct from Their Magnetite Crystals

ABSTRACT Magnetotactic bacteria (MTB) are ubiquitous aquatic microorganisms that form intracellular nanoparticles of magnetite (Fe 3 O 4 ) or greigite (Fe 3 S 4 ) in a genetically controlled manner. Magnetite and greigite synthesis requires MTB to transport a large amount of iron from the environment. Most intracellular iron was proposed to be contained within the crystals. However, recent mass spectrometry studies suggest that MTB may contain a large amount of iron that is not precipitated in crystals. Here, we attempted to resolve these discrepancies by performing chemical and magnetic assays to quantify the different iron pools in the magnetite-forming strain Magnetospirillum magneticum AMB-1, as well as in mutant strains showing defects in crystal precipitation, cultivated at various iron concentrations. All results show that magnetite represents at most 30% of the total intracellular iron under our experimental conditions and even less in the mutant strains. We further examined the iron speciation and subcellular localization in AMB-1 using the fluorescent indicator FIP-1, which was designed for the detection of labile Fe(II). Staining with this probe suggests that unmineralized reduced iron is found in the cytoplasm and associated with magnetosomes. Our results demonstrate that, under our experimental conditions, AMB-1 is able to accumulate a large pool of iron distinct from magnetite. Finally, we discuss the biochemical and geochemical implications of these results. IMPORTANCE Magnetotactic bacteria (MTB) produce iron-based intracellular magnetic crystals. They represent a model system for studying iron homeostasis and biomineralization in microorganisms. MTB sequester a large amount of iron in their crystals and have thus been proposed to significantly impact the iron biogeochemical cycle. Several studies proposed that MTB could also accumulate iron in a reservoir distinct from their crystals. Here, we present a chemical and magnetic methodology for quantifying the iron pools in the magnetotactic strain AMB-1. Results showed that most iron is not contained in crystals. We then adapted protocols for the fluorescent Fe(II) detection in bacteria and showed that iron could be detected outside crystals using fluorescence assays. This work suggests a more complex picture for iron homeostasis in MTB than previously thought. Because iron speciation controls its fate in the environment, our results also provide important insights into the geochemical impact of MTB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Immersive Analytics in Critical Spatial Domains: From Materials to Energy Systems

Immersive analytics (IA) leverages virtual reality, augmented reality, and mixed reality to transform how users interact with complex datasets across domains such as science, industry, and education. These immersive technologies offer spatial and multimodal environments that foster intuitive exploration, but they also introduce challenges related to cognitive load, interface design, and system performance. Here, this article presents a comprehensive review of visualization techniques, interaction models, and multimodal inputs utilized in IA. Drawing on case studies in scientific visualization, industrial training, and educational communication, we examine both the potential and limitations of current systems. Finally, we propose future research directions, focusing on real‐time collaboration, adaptive user interfaces, and scalable data exploration strategies to advance the field.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗
DOE OSTI2022

Many-Body Collective Neutrino Oscillations: Recent Developments

Neutrino flavor transformations in core-collapse supernovae and binary neutron star mergers represent a complex and unsolved problem that is integral to our understanding of the dynamics and nucleosynthesis in these environments. The high number densities of neutrinos present in these environments can engender various collective effects in neutrino flavor transformations, driven either by neutrino-neutrino coherent scattering, or in some cases, through collisional (incoherent) interactions. An ensemble of neutrinos undergoing coherent scattering among themselves is an interacting quantum many-body system -- as such, there is a tantalising prospect of quantum entanglement developing between the neutrinos, which can leave imprints on their flavor evolution histories. Here, in this study, we seek to summarize recent progress that has been made towards understanding this phenomenon.

Hypernuclei↗
DOE OSTI2024

Autonomous anomaly detection of proliferation in the AGN-201 nuclear reactor digital twin

The expansion of global nuclear power necessitates advanced methods for analyzing proliferation indicators. This study introduces a novel application of the Isolation Forest Machine Learning (IFML) algorithm within a digital twin (DT) of the AGN-201 nuclear reactor to autonomously detect anomalies. Leveraging real-time operational data from the AGN-201 DT, the IFML algorithm identifies outliers without prior data labeling and operates as a lightweight, complementary approach to traditional physics-based anomaly detection methods for nuclear safeguards. In a simulated Red vs. Blue team exercise, the IFML algorithm successfully detected six significant unseen anomalies related to reactivity changes, achieving an accuracy of 99% for identifying operational deviationxs. These anomalies, caused by deliberate perturbations, were detected alongside known physics-based models, underscoring the potential of IFML to enhance real-time monitoring without displacing traditional methods. Further, this study highlights the applicability of IFML in nuclear environments by providing an additional, redundant layer of anomaly detection to improve safeguards and operational safety in complex systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Computational modeling of microalgal biofilm growth in heterogeneous rotating algal biofilm reactors (RABRs) for wastewater treatment

Rotating algal biofilm reactors (RABRs) are innovative systems designed to cultivate microalgae biofilms efficiently. In this paper, we have developed a novel mathematical model to accurately capture the growth dynamics of algae biofilms within RABR. By considering the spatial heterogeneity of the RABR, we introduce a PDE-based model that addresses the spatial variations across the substratum, enabling a more accurate simulation of biofilm growth in RABRs. The photosynthesis process is modeled through reactive kinetics, driving the growth of the algae biofilm. To analyze the system's behavior, we employ finite difference numerical methods to solve the complex PDE model. We then conduct extensive numerical simulations to understand algae biofilm growth in the RABR environment under various operational factors and environmental conditions. One primary focus in these simulations is to investigate the impact of various harvesting strategies, harvesting frequencies, light intensity, and light exposure on the overall biomass productivity of the algae biofilm. The numerical results provide valuable insights into optimizing algae biofilm growth and designing harvesting techniques in RABR systems. Our proposed novel mathematical model provides an effective platform for the theoretical investigation and design of RABRs for wastewater treatment.

09 BIOMASS FUELS↗
DOE OSTI2025

Optimizing on-ramp merging for connected and automated vehicles: A hierarchical approach using deep reinforcement learning and optimal control

On-ramp merging for Connected and Automated Vehicles (CAVs) presents significant challenges in dynamic traffic environments. Traditional methods and recent learning-based approaches often fail to simultaneously address decision-making complexity and execution precision under fluctuating conditions. This study introduces a novel hierarchical framework that combines: (1) a high-level Deep Reinforcement Learning (DRL) module that coordinates merging sequences through Virtual Traffic Signals (VTS) with Yield/Green phases and (2) a low-level optimal controller generating collision-free speed trajectories via pseudospectral convex optimization. A convolutional autoencoder compresses high-dimensional traffic states to enhance responsiveness. Extensive simulations demonstrate a 12.5% improvement in mainline throughput a 28% reduction in emergency braking events, and 31.66% lower fuel consumption compared to baseline methods. Furthermore, the framework’s effectiveness in coordinating CAV merges highlights its potential for real-world deployment. Future work will extend validation to multi-lane scenarios with mixed traffic and large-scale multiple merging points.

Connected and automated vehicles↗
DOE OSTI2026

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗
DOE OSTI2024

Direct Mapping of Polyclonal Epitopes in Serum by HDX-MS

Elucidating the interactions that drive antigen recognition is central to understanding antibody-mediated protection and is vital for the rational design of immunogens. Often, structural knowledge of epitopes targeted by antibodies is derived from isolated studies of monoclonal antibodies, for which numerous structural techniques exist. In contrast, there are very few approaches capable of mapping the full scope of antigen surfaces targeted by polyclonal sera through the course of a natural antibody response. Here, in this study, we develop an approach using immobilized antigen coupled to hydrogen/deuterium exchange with mass spectrometry (HDX-MS) to probe epitope targeting in the context of the fully native serum environment. Using the well-characterized Staphylococcal enterotoxin B (SEB) as a model system, we show that complex combinations of epitopes can be detected and subtle differences across different anti-sera can be discerned. This work reveals new insight into how neutralizing antibodies and antisera target SEB, and more importantly, establishes a novel method for directly mapping the epitope landscape of polyclonal sera.

antigens↗
DOE OSTI2021

Magnetism in Mixed Valence, Defect, Cubic Perovskites: BaIn 1– x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75. Local and Average Structures

The series BaIn 1–x Fe x O 2.5+δ , x = 0.25, 0.50, and 0.75, has been prepared under air-fired and argon-fired conditions and studied using X-ray diffraction, d.c. and a.c. susceptibility, Mössbauer spectroscopy, neutron diffraction, X-ray near edge absorption spectroscopy (XANES), and X-ray pair distribution (PDF) methods. While Ba 2 In 2 O 5 (BaInO 2.5 ) crystallizes in an ordered brownmillerite structure, Ibm2, and Ba 2 Fe 2 O 5 (BaFeO 2.5 ) crystallizes in a complex monoclinic structure, P2 1 /c, showing seven Fe 3+ sites with tetrahedral, square planar, and octahedral environments, all phases studied here crystallize in the cubic perovskite structure, Pm$\bar{}3}$m, with long-range disorder on the small cation and oxygen sites. 57 Fe Mössbauer studies indicate a mixed valency, Fe 4+ /Fe 3+ , for both the air-fired and argon-fired samples. The increased Fe 3+ content for the argon-fired samples is reflected in increased cubic cell constants and in the increased Mössbauer fraction. It appears that the Pm$\bar{}3}$m phases are only metastable when fired in argon. From a slightly modified percolation theory for a primitive cubic lattice (taking into account the presence of random O atom vacancies), long-range spin order is permitted for the x = 0.50 and 0.75 phases. Instead, the d.c. susceptibility shows only zero-field-cooled (ZFC) and field-cooled (FC) divergences at ~6 K [5 K] for x = 0.50 and at ~22 K [21 K] for x = 0.75, with values for the argon-fired samples in [ ]. Neutron diffraction data for the air-fired samples confirm the absence of long-range magnetic order at any studied temperature. For the air-fired x = 0.50, a.c. susceptibility data show a frequency-dependent χ'(max) and spin glass behavior, while for x = 0.75, χ'(max) is invariant with frequency, ruling out either a spin glass or a superparamagnetic ground state. These behaviors are discussed in terms of competing Fe 3+ –Fe 3+ antiferromagnetic exchange and ferromagnetic Fe 3+ –Fe 4+ exchange. The PDF and 57 Fe Mössbauer data indicate a local structure at short interatomic distances, which deviates strongly from the average Pm$\bar{}3}$m model. Fe Mössbauer, PDF, and XANES data show a systematic dependence on x and indicate that the Fe 3+ sites are largely fourfold-coordinated and Fe 4+ sites are fivefold- or sixfold-coordinated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Mapping in situ the assembly and dynamics in aqueous supramolecular polymers

Supramolecular polymers, bonded through directional non-covalent interactions, closely mimic dynamic behaviors of biological nanofibers. However, the complexity of assembly pathways makes it highly challenging to unravel the nature of supramolecular dynamics in aqueous environments. Here we introduce a precise combinatorial titration methodology to probe in situ the assembly of peptide amphiphiles (PAs). This approach reveals a binary assembly mechanism governed by equilibrium between spheroidal micelles and β-sheet polymers. Weakening hydrogen bonding shifts the equilibrium towards micelles and decreases the internal structural order of filamentous polymers, promoting supramolecular dynamics. Extending this methodology to two-component copolymerization systems, we find a surprising tendency to form blocky nanostructures with reduced internal phase separation as the mismatch in peptide sequence decreases. Interestingly, while well-mixed copolymers acquire different dynamics, mismatched ones retain the characteristic supramolecular motion of their homopolymer counterparts. These critical insights into supramolecular dynamics offer strategies to tailor the dynamic functions of supramolecular nanomaterials.

Molecular self-assembly↗
DOE OSTI2020

Excited-state electronic structure of molecules using many-body Green’s functions: Quasiparticles and electron–hole excitations with VOTCA-XTP

Here, we present the open-source VOTCA-XTP software for the calculation of the excited-state electronic structure of molecules using many-body Green’s function theory in the GW approximation with the Bethe–Salpeter equation (BSE). This work provides a summary of the underlying theory and discusses the details of its implementation based on Gaussian orbitals, including resolution-of-identity techniques and different approaches to the frequency integration of the self-energy or acceleration by offloading compute-intensive matrix operations using graphics processing units 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 an 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 rubrene–fullerene mixtures. These showcases demonstrate that our implementation currently allows us 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 characters on an equal footing.

74 ATOMIC AND MOLECULAR PHYSICS↗