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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

HumoNet: A Framework for Realistic Modeling and Simulation of Human Mobility Network

Understanding, analyzing, and predicting human mobility and dynamics are valuable to solving pressing problems, developing effective plans, and prescribing timely remedies. As a computational approach, realistic human mobility simulations allow us to understand, analyze, and predict complex systems, including human societies. Accurate simulations rely on (1) the model that captures interactions and behaviors of myriad entities in our society and (2) the mapping of model instances to real-world entities. Taking this into account, this paper introduces the Human Mobility Network simulation framework (HumoNet), an integrated patterns of life (POL) simulation framework that leverages real-world data layers including transportation networks, points of interest, populations, popularity, and human trajectories. HumoNet is a data informed model in which agents are equipped with activities, locomotion, and planning capabilities. To simulate realistic kinematic maneuvers of individuals in transportation networks, HumoNet harnesses a microscopic traffic simulator that provides interaction among vehicles and traffic objects. In this paper, we describe the framework, outline our methodologies, and discuss the data processing and challenges of each data layer. Through experiments, we demonstrate that our simulations capture key features of human mobility by comparing them to the literature and real data using standard measures of human mobility (i.e., the radius of gyration, number of locations visited, level of exploration) and metrics scoring (i.e., Jensen-Shannon divergence). We envision that the synthetic data produced by HumoNet will serve as a benchmark for analyzing epidemics, deploying EV charging networks, and validating AI/ML tasks such as location prediction.

Kim, Joon-Seok↗
DOE OSTI2026

MCP-eGridGPT (MCP-Enabled Chatbot with Electrical Power System Analysis and Interactive Visualization Tool) [SWR-25-126]

This software is an advanced chatbot system that integrates the Model Context Protocol (MCP) to provide intelligent electrical power system analysis and automated visualization generation. The system enables users to interact with complex electrical engineering tools through natural language, automatically analyzes power system data for voltage violations and grid health assessment, and generates professional interactive HTML dashboards and reports. Key features include dynamic tool discovery from MCP servers, multi-LLM provider support, intelligent data interpretation using large language models, automated chart generation, and a web-based interface for real-time analysis. The software bridges sophisticated electrical engineering analysis with user-friendly interfaces, making power system diagnostics accessible through conversational AI.

Choi, Seong [National Laboratory of the Rockies (N↗
DOE OSTI2024

Scaling the polymerization of polyaldehydes through continuous flow synthesis

Abstract A plug flow reactor was constructed to scale the synthesis of metastable, phthalaldehyde-based polymers to achieve production rates of 1–2 kg per day. The flow-induced mixing and in-line polymerization quench and precipitation sequences resulted in improved polymer purity and long-term stability compared to the same materials made from a conventional batch process. Cryogenic rheology was used to probe the complex fluid dynamics encountered during the polymerization of PPA homopolymers. It is envisioned that this continuous flow manufacturing approach could be extended to other low ceiling temperature or aldehyde monomer systems to help implement and support a plastic circular economy. Graphical abstract

Schwartz, Jared M.↗
DOE OSTI2025

Computational methods based on density functional theory for reactions and processes involving electronic spin (Final Technical Report)

This award supports one post-doctoral researcher for 1.5 years. Publications that acknowledge this grant: Refs. 1–14. Refs. 3,10,12 assess current methodology for the evaluation of magnetic exchange couplings in transition metal complexes. In particular, Ref. 10 validates the use of an approximate (non-iterative) Green’s function approach for the calculation of magnetic exchange couplings and will be the foundation for Thrust 2 in this proposal. Refs. 3 and 12 focus on widely used density functional approaches based on the standard energy differences methodology for the particular case of oxo-bridged Fe(III) complexes. Refs. 2,4–7,11 apply current methodologies to problems of practical interest in molecular magnetism. Ref. 13 presents a methodology to explicitly simulate the dynamics of open quantum systems within density functional theory (DFT) calculations based on the Liouville-von Neumann equation of motion for quantum systems driven out-of-equilibrium. Ref. 8 uses non-collinear spin DFT to explain the mechanical behavior of magnetic mono-atomic Pt wires produced in break-junction experiments in the presence of a magnetic field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multiscale Dynamics of Reactive Fronts in the Subsurface

Understanding and predicting flow and reactive transport in rocks (i.e. geologic porous media) is critical to many technologies at the heart of the energy transition, including CO 2 sequestration and H2 storage. However, accurate modeling and prediction of these systems is very complex because physico-chemical processes that occur at very small spatial scales, i.e. in the pores of the rocks, can dramatically control the system performance at the field scale (km). For example, precipitation reactions at the pore-scale can lead to large permeability changes at the field scale and dramatically alter the migration of stored gases. Properly accounting for multi-scale coupling effects is critical to achieve predictivity and confidence in model outputs, which then can guide design and optimization at the system-scale. This can be achieved through the development of rigorous mathematical models that can appropriately account for fine-scale effects at the large scale. The final report of the Early Career award DE-SC0019075 “Multiscale dynamics of reactive fronts in the subsurface” summarizes the mathematical, numerical and experimental advancements to study and predict reactive transport in geologic porous media across scales.

58 GEOSCIENCES↗
DOE OSTI2024

Tidal Love numbers and Green’s functions in black hole spacetimes

Tidal interactions play a crucial role in deciphering gravitational wave signals emitted by the coalescence of binary systems. They are usually quantified by a set of complex coefficients which include tidal Love numbers, describing the conservative response to an external perturbation. In the static case, these are found to vanish exactly for asymptotically flat black holes in general relativity in four space-time dimensions, and recently they have been generalized to dynamical interactions. In the context of response theory, the retarded Green’s function provides the complete description of the behavior of dynamical systems. Here, in this work we investigate the relation between Love numbers and Green’s functions, and highlight the relevance of radiation reaction effects to their connection. As a special case, we discuss Banados-Teitelboim-Zanelli black holes, where the absence of radiative modes allows us to make a direct link between them.

classical black holes↗
DOE OSTI2025

Energy migration and scintillation kinetics in compositionally complex (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce single crystal scintillator

It is well-established that compositional tuning through binary admixture can improve scintillation performance in several materials systems, including Ce-activated garnets. Although recent work on ternary or quaternary cation admixture shows promise, the impact of this increased compositional complexity on thermal stability and carrier-defect dynamics has not been addressed. Here, we investigate a compositionally complex garnet, (Gd 1/4 Y 1/4 Tb 1/4 Lu 1/4 ) 3 Al 5 O 12 :Ce (GYTLAG), grown by the Czochralski method using temperature-dependent photoluminescence (PL), PL decay, and thermoluminescence (TL). PL and PL decay measurements support a thermally activated Tb 3+ -Ce 3+ energy transfer, where Tb 3+ emission dominates below 60 K, but Ce 3+ emission increases from 20-300 K. Thermal quenching of Ce 3+ emission occurs around T 50 = 508 K, with an activation energy of 0.6 eV. TL and wavelength-resolved TL spectra from 20–500 K show that GYTLAG contains similar trap groups to LuAG but with a broader distribution of glow peaks below room temperature, possibly caused by quaternary cation mixing. A combination of dose dependence, partial cleaning and initial rise, and glow curve fitting to a first order continuous Gaussian distribution model are used to understand the contribution of electronic point defects to scintillation decay and afterglow at room temperature. Furthermore, these results inform how increased compositional complexity influences recombination dynamics in garnet scintillators.

Compositionally complex↗
DOE OSTI2025

Light induced ion migration studies in perovskite solar cell using nonlinear impedance spectroscopy

Complex interactions between mobile ions and charge carriers in perovskite solar cells (PSCs) make it challenging to fully understand their dynamic interplay. Exposure to light further complicates these interactions, altering the system’s dynamics and inducing nonlinear effects that lead to changes in the J−V curve. Understanding these effects is crucial for improving the operational stability of PSCs. Impedance spectroscopy (IS) is a powerful technique for evaluating relaxation processes in the frequency domain; however, it is limited in capturing nonlinear contributions. Here, in this work, nonlinear impedance spectroscopy (NLIS) is employed to analyze the higher harmonic response to AC perturbation, both in the dark and after short-term light exposure. A shift in the low-frequency (LF) higher harmonic peak is observed after open-circuit light exposure, attributed to an altered electric field suggesting ion re-distribution, whereas closed-circuit exposure shows no LF shift, indicating minimal ion movement. Additionally, light exposure reduces higher-order admittance, more notably in open-circuit conditions, suggesting decreased recombination. Temperature-dependent analysis was conducted to characterize the activation energy of migrating species, identifying iodide as the dominant migrating ion.

14 SOLAR ENERGY↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗
DOE OSTI2026

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗
DOE OSTI2025

Strategic Lifetime Tuning of Visible-Light Absorbing Two-Coordinate Metal Complexes

This paper highlights how the singlet and triplet amide ligand centered ( 1,3 LC) and interligand charge transfer ( 1,3 ICT) states in (carbene)M(amide), M = Cu, Au (cMa) complexes influence the excited state properties when the triplet states are close in energy. To that end we prepared a set of five cMa complexes, in which the amide (i.e., 5H-benzo[b]carbazole, H-BnCz) was kept constant giving a 3 LC energy of ca. 2.15 eV. Four different carbene ligands were selected to develop M BnCz Carbene complexes which have energies for the ICT state that vary from being either markedly higher, lower, or close to the energy of the 3 LC state on the amide ligand. Steady-state and time-resolved spectroscopic studies show that the emission spectrum of the cMa complex mirrors the phosphorescence of the parent H-BnCz amide and has a luminescence decay lifetime in the millisecond regime when the lowest energy excited state is 3 LC. When the lowest energy states are 1,3 ICT in nature, the emission band is broad and featureless, giving a lifetime in the nanosecond regime. As the 3 LC and 1,3 ICT states have comparable energies, dynamic equilibrium between the states is observed with the luminescence consisting of a mixture of 3 LC and 1,3 ICT transitions. The measured lifetime of this equilibrating system is between 45 and 350 μs depending on the solvent, for both copper- and gold-based cMa complexes. Furthermore, these complexes demonstrate the ability to “park” the excited state population in the 3 LC state, allowing it to act as a reservoir for thermally activated emission, while still maintaining a very rapid equilibrium between LC and ICT states.

14 SOLAR ENERGY↗
DOE OSTI2025

Polarization Switching on the Open Surfaces of the Wurtzite Ferroelectric Nitrides: Ferroelectric Subsystems and Electrochemical Reactivity

Binary ferroelectric nitrides are promising materials for information technologies and power electronics. However, polarization switching in these materials is highly unusual. From the structural perspective, polarization reversal is associated with the change of the effective polarity at the surfaces and interfaces from N‐to‐M terminated, suggesting strong coupling between ferroelectric and chemical phenomena. Phenomenologically, macroscopic studies demonstrate the presence of complex time dependent phenomena including wake‐up. Here, in this study, the polarization switching using the multidimensional high‐resolution piezoresponse force microscopy (PFM) and spectroscopy is explored, detecting both the evolution of induced ferroelectric domain, electromechanical response, and surface deformation during first‐order reversal curve measurements. The presence of two weakly coupled ferroelectric subsystems are demonstrated and the bias‐induced electrochemical reactivity. The observed behaviors are very similar to the recent studies of other wurtzite system but additionally include electrochemical reactivity, suggesting the universality of these behaviors for the wurtzite binary ferroelectrics. These studies suggest potential of high‐resolution multimodal PFM spectroscopies to resolve complex coupled polarization dynamics in materials. Furthermore, these PFM based studies are fully consistent with the recent electron microscopy observations of the shark‐teeth like ferroelectric domains in nitrides. Hence, it is believed that these studies establish the universal phenomenological picture of polarization switching in binary wurtzite.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Multimodal Instrument Concepts for Chemical Sciences at Second Target Station

The development of advanced chemical and energy systems is inherently complex, relying heavily on their unique pathways. Because no two catalysts or batteries follow exactly the same kinetic trajectories, conventional sequential measurements often obscure crucial relationships between structure and dynamics through statistical averaging. This report introduces two neutron scattering instrument concepts for the Second Target Station (STS) specifically designed to overcome this barrier: the Extended Q-range Diffractometer (EQD) and the Multimodal Chemical Spectrometer (MCS).

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

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
DOE OSTI2023

Dynamic Oscillation and Motion of Oil‐in‐Water Emulsion Droplets

The interplay of interfacial tensions on droplets results in a range of self‐powered motions that mimic those of living systems and serve as a tunable model to understand their complex non‐equilibrium behavior. Spontaneous shape deformations and oscillations are crucial features observed in nature but difficult to incorporate in synthetic artificial systems. Here, we report sessile oil‐in‐water emulsions that exhibit rapid oscillating behavior. The oscillations depend on the nature and concentration of the surfactant, the chemical composition of the oil, and the wettability of the solid substrate. The rapid changes in the contact angle per oscillation are observed using side‐view optical microscopy. We propose that the changes in the interfacial tension of the oil droplets is due to the partitioning of the surfactant into the oil phase and the movement of self‐emulsified oil out of the parent droplets giving rise to the rhythmic variation in droplet contact‐line. The ability to control and understand droplet oscillation can help model similar oscillations in out‐of‐equilibrium systems in nature and reproduce biomimetic behavior in artificial systems for various applications, such as microfluidic lab‐on‐a‐chip and adaptive materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A Gauss-Radau-Laguerre Discrete Variable Representation for Use in Continuum Electron Dynamics

In this work, we detail an implementation, suitable for calculations on highly correlated ionizing systems, of a modified finite element discrete variable representation (FE-DVR) appended with a Gauss-Radau-Laguerre element. The appended element includes exterior complex scaling (ECS) to impose outgoing wave boundary conditions on treatments of processes involving continuum electrons. In this “infinite range” ECS (irECS), the complications that introduce reflections from the end of the grid when the last ECS finite element has finite range are avoided by the use of the Laguerre-weighted exponentially decaying tails, while outgoing wave boundary conditions are still imposed via the ECS transformation. For highly correlated systems in the absence of strong external fields we find that accurate two-electron integrals are essential in this modified FE-DVR. To accurately compute the two-electron integrals over the entire ECS contour, we present a detailed examination of the implications from the boundary terms that arise in a solution of Poisson’s equation with the Radau-Laguerre basis. A boundary term correction is necessary, and when included, the Radau-Laguerre DVR can accurately describe highly correlated states such as the doubly excited states of helium over the entire ECS contour.

elements↗