Search NASA⌕ Search

SEARCH · Search NASA

Results for “Complex systems theory”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Accelerating lattice gauge theory studies with Agentic AI

Lattice gauge theory research, with its computationally intensive simulations and complex multi‑stage workflows, is well positioned to benefit from agentic AI systems. We demonstrate how such tools can support key components of lattice gauge theory research, including novel simulation code development using standard LQCD frameworks, HPC job orchestration, simulation data analysis, and expert‑guided tuning of algorithmic parameters such as Hasenbusch mass preconditioning and multigrid solvers. Our results show that agentic AI can reduce manual effort, improve productivity, and accelerate the research cycle while maintaining essential human oversight.

Ayyar, Venkitesh [Fermilab]↗
DOE OSTI2025

Accelerating Instanton Theory with the Line Integral Nudged Elastic Band Method and Gaussian Process Regression

Quantum tunneling plays a fundamental role in many chemical reactions, particularly proton transfer processes. Ring polymer instanton theory offers a practical framework for computing tunneling rates in complex molecular systems. However, applying the ring polymer instanton method with a potential energy surface generated on-the-fly using electronic structure calculations can be computationally demanding. Here, in this work, we present a new efficient implementation of the ring polymer instanton method by combining the Line Integral Nudged Elastic Band (LI-NEB) approach with Gaussian Process Regression (GPR). We benchmarked this method on prototypical ground-state proton transfer systems, including the benchmark gas-phase hydrogen abstraction reaction H + CH 4 → H 2 + CH 3 , malonaldehyde, and Z-3-amino-propenal (aminopropenal). Our results show that this approach is an order of magnitude faster than traditional instanton algorithms while maintaining excellent agreement with their tunneling rates. This development opens the door to studying proton transfer in larger systems with improved efficiency.

chemical physics↗
DOE OSTI2025

Connecting relativistic density functional theory to microscopic calculations

The development of systematic effective field theories (EFTs) for nuclear forces and advances in solving the nuclear many-body problem have greatly improved our understanding of dense nuclear matter and the structure of finite nuclei. For global nuclear calculations, density functional theories (DFTs) have been developed to reduce the complexity and computational cost required in describing nuclear systems. However, DFT often makes approximations and assumptions about terms included in the functional, which may introduce systematic uncertainties compared to microscopic calculations using EFTs. In this work, we investigate possible avenues of improving nuclear DFT using nonlinear relativistic mean-field (RMF) theory. We explore the impact of RMF model extensions by fitting the nonlinear RMF model to predictions of nuclear matter and selected closed-shell nuclei using four successful chiral EFT Hamiltonians. We find that these model extensions are impactful and important in capturing the physics present within chiral Hamiltonians, particularly for charge radii and neutron skins of closed-shell nuclei. However, there are additional effects that are not captured within the RMF model, particularly within the isoscalar sector of RMF theory. Additional model extensions and the reliability of the nonlinear RMF model are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Ligand‐Mediated Quantum Yield Enhancement in 1‐D Silver Organothiolate Metal–Organic Chalcogenolates

X-ray free electron laser (XFEL) microcrystallography and synchrotron single-crystal crystallography are used to evaluate the role of organic substituent position on the optoelectronic properties of metal–organic chalcogenolates (MOChas). MOChas are crystalline 1D and 2D semiconducting hybrid materials that have varying optoelectronic properties depending on composition, topology, and structure. While MOChas have attracted much interest, small crystal sizes impede routine crystal structure determination. A series of constitutional isomers where the aryl thiol is functionalized by either methoxy or methyl ester are solved by small molecule serial femtosecond X-ray crystallography (smSFX) and single crystal rotational crystallography. While all the methoxy examples have a low quantum yield (0-1%), the methyl ester in the ortho position yields a high quantum yield of 22%. Here, the proximity of the oxygen atoms to the silver inorganic core correlates to a considerable enhancement of quantum yield. Four crystal structures are solved at a resolution range of 0.8–1.0 Å revealing a collapse of the 2D topology for functional groups in the 2- and 3- positions, resulting in needle-like crystals. Further analysis using density functional theory (DFT) and many-body perturbation theory (MBPT) enables the exploration of complex excitonic phenomena within easily prepared material systems.

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

Binding of Sulfates and Water to Monovalent Cations

The binding of the sulfate ligand group to monovalent cations in the presence of water is important for many systems. To understand the structure and energetics of sulfate complexes, we use density functional theory to study ethyl sulfate binding to the monovalent cations Li + , Na + , and K + , and to water. The free energies of binding and optimal structures are calculated for a range of the number of ethyl sulfates and waters. Without water, the most optimal structure for all the cations is bidentate binding by two ethyl sulfates, yielding a 4-fold coordination. With water, the lowest free energy structures also have two ethyl sulfates, but the coordination varies with cations. For complexes with water, the four oxygen atoms in the sulfate group enable multiple binding geometries for the cations and for hydrogen bonding with water. Many of these geometries differ in free energy by only a small amount (1–2 kcal/mol), meaning there will be multiple binding configurations in bulk solution. In comparison to the optimal structures for binding to the carboxylate group, there is more variation for binding to the sulfate group as a function of cation type and the number of waters. Further, the polarization of the atoms is significant and varies among the sulfate oxygen atoms. The water oxygen charge is often larger than that of sulfate oxygen, which plays a role in the preference for monodentate ligand binding to cations in the presence of water.

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

Out of time order correlation of the Hubbard model with random local disorder

The out-of-time-order correlator (OTOC) serves as a powerful tool for investigating quantum information spreading and chaos in complex systems. We present a method employing non-equilibrium dynamical mean-field theory and coherent potential approximation combined with diagrammatic perturbation on the Schwinger–Keldysh contour to calculate the OTOC for correlated fermionic systems subjected to both random disorder and electron interaction. Furthermore, our key finding is that random disorder enhances the OTOC decay in the Hubbard model for the metallic phase in the weakly interacting limit. However, the current limitation of our perturbative solver restricts the applicability to weak interaction regimes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Fundamental Path Optimization Strategies for Extrusion-based Additive Manufacturing

Extrusion-based additive manufacturing processes begin with a software program, called a slicer, that generates layer geometry and fits toolpaths to each layer to define where material is to be extruded or deposited. Before the toolpaths are output as g-code for the additive manufacturing system to execute, the toolpaths should be optimized. Many complex optimization approaches using graph theory, Chinese postman problem, and other complex mathematical models exist, but these approaches are rarely used in daily printing operations and are not available through common slicing programs such as Cura and PrusaSlicer. Instead, path planning and optimization typically revolves around simpler, fully automated approaches such as inside out and next closest. This paper will explore the fundamental optimization strategies for toolpath planning and document a new implementation, available via open-source slicing software, that allows for greater control of the path planning process.

Roschli, Alex [ORNL] (ORCID:0000000213084632)↗
DOE OSTI2026

Long-Range Fit: A Software Package for the Representation and Study of Long-Range Molecular Interactions

Describing intermolecular forces is fundamental to modeling and predicting the behavior of molecular systems. In particular, long-range molecular interactions─with electrostatic, induction, and dispersion as the main components─play a critical role, especially for low-temperature and low-density regimes. Long-range interactions are often described through perturbation theory, representing the electronic charge distribution via a multipolar series of the moments and polarizability tensors corresponding to each molecule. However, while the theory is well established, obtaining the resulting analytical expressions (and their practical implementation) constitutes a highly complex and system-dependent task. To address this challenge, we developed long-range-fit (LRF), an interactive and user-friendly software package designed to automate the generation and fitting of long-range interaction terms for arbitrary molecules in nondegenerate (ground or excited) electronic states. We have derived and implemented all terms up to 15th order, without approximations, via a spherical tensor representation, with symmetry adaptation to all molecular point-group symmetries. The resulting potential energy surface is compatible with most representations of the close interaction region.

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

Shell Thickness and Heterogeneity Dependence of Triplet Energy Transfer between Core–Shell Quantum Dots and Adsorbed Molecules

Quantum dot (QD)-sensitized triplet energy transfer (TET) has found promising applications in photon upconversion and photocatalysis. However, the underlying mechanism of TET in the QD-acceptor complex remains unclear despite the well-developed TET theory for the molecular donor–acceptor systems. Herein, the coupling strength of TET from CdSe/CdS core–shell QDs to 9-anthracene carboxylic acid (ACA) was studied by measuring the TET rate as a function of shell thickness with time-resolved photoluminescence. The change of TET-coupling strength with increasing shell thickness was further compared to those of electron and hole transfers from QDs so that we could test whether QD-sensitized TET is mediated by the charge transfer virtual state and can be considered as simultaneous electron and hole transfers as in molecular donor–acceptor systems. The measured coupling strength of TET from the CdSe/CdS QD decreases exponentially with the CdS shell thickness r: |V|(r) = |V|(0)e –βr , with an exponential decay factor β of 0.19 Å –1 , which is smaller than the sum of the measured decay factors for electron transfer to methyl viologen (0.18 Å –1 ) and hole transfer to phenothiazine (0.29 Å –1 ) from the same QD. This inconsistency is explained by the broadening of QD shell thicknesses in the distance dependence study, which significantly modifies the TET-coupling strength and driving force, resulting in a shallower distance dependence of the TET rate constants. This study sheds light on the fundamental mechanisms of QD-sensitized TET reactions.

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

Projector‐Based Quantum Embedding Study of Iron Complexes

Projection‐based embedding theory (PBET) is used to calculate and assess the challenging spin‐crossover energies for a selection of small Fe‐containing systems by embedding the metal center into the frozen potential of the ligands. MP2, CCSD, and CCSD(T) are embedded in potentials from the SCAN and r 2 SCAN functionals and compared with the canonical values for the constituent methods and previously reported reference values. Considering the PBET calculations as a correction for the underlying DFT, the embedding calculations are able to provided improvement for most cases. In some cases, the PBET methods are able to compensate for limitations in the wave function methods and produce results similar to more rigorous calculations from the literature. For the systems with spin‐crossover energies near zero, the current methodology fails to provide consistent improvement. In conclusion, the isolated recalculation of the electronic structure around the metal center when embedded into a DFT treatment of the ligand field shows promise as a pragmatic and lower cost treatment compared to the canonical treatment of the whole system of the difficult class of spin‐crossover complexes.

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

Modeling Strong Light-Matter Coupling in Correlated Systems: State-Averaged Cavity Quantum Electrodynamics Complete Active Space Self-Consistent Field Theory

The description of strongly correlated systems interacting with quantized cavity modes poses significant theoretical challenges due to the combinatorial scaling of electronic and photonic degrees of freedom. Recent advances addressing this complexity include cavity quantum electrodynamics (QED) generalizations of complete active space configuration interaction and density matrix renormalization group methods. In this work, we introduce a QED extension of state-averaged complete active space self-consistent field theory, which incorporates cavity-induced correlations through a second-order orbital optimization framework with robust convergence properties. The method is implemented using both photon number state and coherent state representations, with the latter showing robust origin invariance in the energies regardless of the completeness of the photonic Fock space. The implementation enables symmetry-free orbital relaxations to account for photon-mediated symmetry breaking in polaritonic systems. Numerical validation on lithium hydride, hydroxide anion, and magnesium hydride cation demonstrates that this method achieves significantly improved accuracy in modeling ground-state and polariton potential energy surfaces compared to QED-CASCI in a fixed orbital basis. In these studies, we reach sub-kcal/mol accuracy in potential energy surface in much smaller active spaces than are required for QED-CASCI. This advancement provides a more robust approach for studying cavity-altered chemical landscapes for ground and exited strongly coupled systems.

CASSCF↗
DOE OSTI2025

Advances and Challenges of SCAN and r 2 SCAN Density Functionals in Transition‐Metal Compounds

ABSTRACT Transition‐metal compounds (TMCs) with open‐shell d ‐electrons are characterized by a complex interplay of lattice, charge, orbital, and spin degrees of freedom, giving rise to various fascinating applications. Often exhibiting exotic properties, these compounds are commonly classified as correlated systems due to strong inter‐electronic interactions called Hubbard U . This inherent complexity presents significant challenges to Kohn‐Sham density functional theory (KS‐DFT), the most widely used electronic structure method in condensed matter physics and materials science. While KS‐DFT is, in principle, exact for the ground‐state total energy, its exchange‐correlation energy must be approximated in practice. The mean‐field nature of KS implementations, combined with the limitations of current exchange‐correlation density functional approximations, has led to the perception that DFT is inadequate for correlated systems, particularly TMCs. Consequently, a common workaround involves augmenting DFT with an on‐site Hubbard‐like U correction. In recent years, the strongly constrained and appropriately normed (SCAN) density functional, along with its refined variant r 2 SCAN, has achieved remarkable progress in accurately describing the structural, energetic, electronic, magnetic, and vibrational properties of TMCs, challenging the traditional perception of DFT's limitations. This review explores the design principles of SCAN and r 2 SCAN, highlights their key advancements in studying TMCs, explains the mechanisms driving these improvements, and addresses the remaining challenges in this evolving field.

Zhang, Yubo [Minjiang Collaborative Center for The↗
DOE OSTI2024

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗
DOE OSTI2026

Electron–electrophile coupled dinitrogen reduction in a cerium– meta -tetraphenolate system: a computational study

The use of lanthanide complexes for catalytic dinitrogen reduction is a new development in homogeneous catalysis. Density functional theory calculations on our recently reported cerium phenolate catalyst [K 2 Ce 2 (sol) 4 (mTP) 2 ] (mTP = {(OC 6 H 2 - 2- t Bu-4-Me) 2 CH} 2 - 1,3-C 6 H 4 ; sol = OMe 2 here; THF in the experiment) have been undertaken to elucidate the reduction, activation and silylation steps at the bound dinitrogen molecule, in the presence of the reductant, potassium metal (K 0 ) and the electrophile Me 3 SiCl (TMSCl). Out of the total of six electron reductions required to cleave the N 2 , the first two-electron reduction step was found to be highly disfavoured unless potassium cations (K + ) are included, upon which the step is rendered strongly exergonic; N–Si bond formation at the two-electron stage is predicted to be unfavourable. The three-electron-reduced N 2 -adduct is found to be at the reductive activation limit in the absence of added electrophiles, which can form N-element bonds and lower the overall charge. Added electron density beyond three-electron reduction no longer localises on N 2 , preventing formal N 2 4− formation. A pathway in which both K 0 and Me 3 SiCl work in concert was modelled, and six sequential reduction–silylation steps were calculated, showing how the N–N bond is cleaved after the third reduction, eventually releasing two equivalents of N(SiMe 3 ) 3 , and regenerating the starting complex with the highest barrier of any step being 22 kcal mol −1 . We establish alkali metal coordination and coupled electron–electrophile transfer as key factors in the design of rare-earth-mediated dinitrogen functionalisation.

Ahmad, Shahbaz [Univ. of Manchester (United Kingdo↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2026

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Generalized Quasi-Static Mooring System Modeling with Analytic Jacobians

This paper presents a generalized and efficient method for quasi-static analysis of mooring systems, including complex scenarios such as when shared mooring lines interconnect multiple floating wind or wave energy devices. While quasi-static mooring models are well established, most published formulations are focused on specific applications, and no publicly available implementations provide efficient handling of large mooring system networks. The present formulation addresses these gaps by: (1) formulating solutions for edge cases not typically supported by quasi-static models; (2) creating a fully generalized model structure such that any combination of mooring lines, point masses, and floating bodies can be assembled; and (3) deriving analytic expressions for the system Jacobians (stiffness matrices) so that systems with many degrees of freedom can be solved efficiently. These techniques form the theory basis of MoorPy, an open-source mooring analysis library. The model is demonstrated on nine scenarios of increasing complexity with features of interest for offshore renewable energy applications. When compared with steady-state results from a lumped-mass dynamic model, the results show that the quasi-static formulation accurately calculates profiles and tensions and that its analytic approach provides more efficient and reliable computation of system stiffness matrices than finite-differencing methods. These results verify the accuracy of the MoorPy model.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

17 O NMR Spectroscopy Reveals CO 2 Speciation and Dynamics in Hydroxide-Based Carbon Capture Materials

Carbon dioxide capture technologies are set to play a vital role in mitigating the current climate crisis. Solid-state 17 O NMR spectroscopy can provide key mechanistic insights that are crucial to effective sorbent development. In this work, we present the fundamental aspects and complexities for the study of hydroxide-based CO 2 capture systems by 17 O NMR. We perform static density functional theory (DFT) NMR calculations to assign peaks for general hydroxide CO 2 capture products, finding that 17 O NMR can readily distinguish bicarbonate, carbonate and water species. However, in application to CO 2 binding in two test case hydroxide-functionalised metal-organic frameworks (MOFs) – MFU-4l and KHCO 3 -cyclodextrin-MOF, we find that a dynamic treatment is necessary to obtain agreement between computational and experimental spectra. We therefore introduce a workflow that leverages machine-learning force fields to capture dynamics across multiple chemical exchange regimes, providing a significant improvement on static DFT predictions. In MFU-4l, we parameterise a two-component dynamic motion of the bicarbonate motif involving a rapid carbonyl seesaw motion and intermediate hydroxyl proton hopping. For KHCO 3 -CD-MOF, we combined experimental and modelling approaches to propose a new mixed carbonate-bicarbonate binding mechanism and thus, we open new avenues for the study and modelling of hydroxide-based CO 2 capture materials by 17 O NMR.

NMR spectroscopy↗