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At least 73 records · Page 4

Dissipation Pathways in a Photosynthetic Complex

Determining how energy flows within and between molecules is crucial for understanding chemical reactions, material properties, and even vital processes such as photosynthesis. While the general principles of energy transfer are well established, elucidating the specific molecular pathways by which energy is funneled remains challenging, as it requires tracking energy flow in complex molecular environments. Here, we demonstrate how photon excitation energy is partially dissipated in the light-harvesting Fenna–Matthews–Olson (FMO) complex, mediating the excitation energy transfer from light-harvesting chlorosomes to the photosynthetic reaction center in green sulfur bacteria. Specifically, we isolate the contribution of the protein and specific vibrational modes of the pigment molecules to the energy dynamics. For this, we introduce an efficient computational implementation of a recently proposed theory of dissipation pathways for open quantum systems, based on second-order perturbation theory in the electronic couplings. Using it and a state-of-the-art FMO model with highly structured and chromophore-specific spectral densities, we demonstrate that energy dissipation is dominated by low-frequency modes (<800 cm –1 ) as their energy range is near-resonance with the energy gaps between electronic states of the pigments. We identify the most important modes for dissipation to be in-plane breathing modes (∼200 cm –1 ) of the bacteriochlorophylls in the complex. Conversely, far-detuned intramolecular vibrations with higher frequencies (>800 cm –1 ) play no role in dissipation. Interestingly, the FMO complex first needs to borrow energy from the environment to release excess photonic energy, indicating that the energy exchange between the system and thermal environment is not strictly unidirectional in time but involves a transient thermally activated step. Beyond their fundamental value, these insights can guide the development of artificial light-harvesting devices and, more broadly, engineer environments for chemical and quantum control tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Exciton-Defect Interaction and Optical Properties from a First-Principles T-Matrix Approach

Understanding exciton-defect interactions is critical for optimizing optoelectronic and quantum information applications in many materials. However, ab initio simulations of material properties with defects are often limited to high defect density. Here, we study effects of exciton-defect interactions on optical absorption and photoluminescence spectra in monolayer MoS 2 using a first-principles T-matrix approach. We demonstrate that exciton-defect bound states can be captured by the disorderaveraged Green’s function with the T-matrix approximation and further analyze their optical properties. Our approach yields photoluminescence spectra in good agreement with experiments and provides a new, computationally efficient framework for simulating optical properties of disordered 2D materials from firstprinciples.

T-matrix

Moduli axions, stabilizing moduli, and the large field swampland conjecture in heterotic M-theory

We compute the F- and D-term potential energy for the dilaton, complex structure, and Kähler moduli of realistic vacua of heterotic M-theory compactified on Calabi-Yau threefolds where, for simplicity, we choose ℎ 1,1 = ℎ 2,1 = 1. However, the formalism is immediately applicable to the “universal” moduli of Calabi-Yau threefolds with ℎ 1,1 = ℎ 1,2 > 1 as well. The F-term potential is computed using the nonperturbative complex structure, gaugino condensate and “world sheet instanton” superpotentials in theories in which the hidden sector contains an anomalous U⁡(1) structure group. The Green-Schwarz anomaly cancellation induces inhomogeneous “axion” transformations for the imaginary components of the dilaton and Kähler modulus—which then produce a D-term potential. V D is a function of the real components of the dilaton and Kähler modulus (s and t) that is minimized and precisely vanishes along a unique line in the s–t plane. Excitations transverse to this line have a mass m anom which is an explicit function of t. The F-term potential energy is then evaluated along the V D = 0 line. For values of t small enough that m anom ≳ M U —where M U is the compactification scale—we plot V F for a realistic choice of coefficients as a function of the Pfaffian parameter p. We find values of p for which V F has a global minimum at negative or zero vacuum density or a metastable minimum with positive vacuum density. In all three cases, the s, t, and associated “axion” moduli are completely stabilized. Finally, we show that, for any of these vacua, the large t behavior of the potential energy satisfies the “large scalar field” Swampland conjecture.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Final Technical Report: In-Silico Heterogeneous Catalyst Design for GHG Reduction via Bulk Chemicals

This project has advanced the understanding of ammonia synthesis by developing novel thermochemical catalysts, setting a new benchmark for energy and carbon efficiency in large-scale bulk chemicals production. This research leverages a proprietary computational discovery platform and high-throughput experimental validation, significantly accelerating catalyst optimization and enabling ammonia synthesis at lower temperature and pressure conditions than conventional processes. As a result, green ammonia can be produced at a cost that meets or exceeds established targets, supporting a viable pathway toward decarbonized ammonia for fuel, fertilizers, and hydrogen supply applications.

Grose, Jacob E [Copernic Catalysts, Inc.]

Identifying Green Solvent Mixtures for Bioproduct Separation Using Bayesian Experimental Design

Liquid–liquid extraction (LLE) is a widely used technique for the separation and purification of liquid-phase products with applications in various industries, including pharmaceuticals, petrochemicals, and renewable chemistry. A critical step in the design of an LLE process is the selection of appropriate solvents. This study presents a new methodology for identifying solvent mixtures for bioproduct separation using Bayesian experimental design (BED). Motivated by the need for environmentally friendly and effective separation methods, we address the challenge of selecting solvent systems that balance separation efficiency, selectivity, and environmental impact while also tackling the difficulty of separating multiple bioproducts using complex solvent systems. Our approach specifically seeks to predict product partition coefficients (log10 Kp values) as thermodynamic parameters underlying solvent selection. The iterative approach integrates Bayesian optimization with experimental measurements to guide solvent selection and leverages COSMO-RS simulations to enhance high-throughput experimentation. Using the design of solvent systems for the separation of lignin-derived aromatic products via centrifugal partition chromatography (CPC) as a case study, we show that within seven iterations/cycles of the methodology, we can identify new mixtures of green solvents that align with CPC design principles. Furthermore, these results demonstrate the efficacy of the BED framework in optimizing green solvent systems for complex separations, highlighting the potential of this method to advance the field of green chemistry and contribute to the development of sustainable industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Review of recent activities with MOOSE, an open-source finite element & finite volume multi-fidelity simulation framework

Modeling and simulation are an increasing part of engineering. This is undoubtedly driven by the high costs of constructing experimental facilities, but also enabled by the exponential increase in computing powers over the last decades, which allows computational models to be closer than ever to reality. One of the main drivers for the development of MOOSE is supporting advanced nuclear reactor simulations. A challenging aspect of modeling advanced nuclear reactors is the plurality of physics involved, including neutronics, thermal hydraulics and fuel performance. These physics are all coupled to some extent and are generally solved in a sequential but iterative fashion. The United States (U.S.) national laboratories have been developing MOOSE, an open source multiphysics framework since its inception at the Idaho National Laboratory (INL) in 2008. This framework enables seamless coupling of multiphysics simulations and facilitates the implementation of new physics and material governing laws. It is continuously expanded with novel numerical methods and new pre-implemented physics module. Numerous applications, developed within the Department of Energy (DOE) laboratories, academia, and industry, including outside of nuclear engineering, have been developed to study specialized physics problems. International collaborations are welcome on this open-source modeling and simulation project.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Plasma assisted NH 3 /H 2 /air ignition in nanosecond discharges with non-equilibrium energy transfer

Ammonia (NH 3 ), with its high energy density and easiness to store and transport as a hydrogen carrier, has become a promising alternative green fuel. However, its adoption in power generation is hindered by challenges such as low burning velocity, slow low-temperature oxidation, high NO x emissions, and ignition difficulty. Here, this work computationally investigates the effects of non-equilibrium energy transfer by nanosecond discharges on NH 3 ignition and flame propagation in an NH 3 /H 2 /air flow at 700 K and 1 atm. The simulation results demonstrate that NH 3 /air mixtures require a large ignition energy due to their large critical ignition radius. It is shown that adding 30 % hydrogen significantly reduces the critical ignition radius and minimum ignition energy. Two-dimensional modeling further shows a non-monotonic dependence of ignition kernel volume on the applied voltage and reduced electric field. The optimum ignition enhancement occurs at 200 Td where the generation of electronically excited species and radicals including N 2 (B), O( 1 D) and OH becomes most efficient. Higher voltages divert electron energy toward ionization, which makes it less effective for NH 3 ignition. The study also identifies an optimal electrode gap size for a given pulse energy. Smaller gap sizes increase deposited energy density, raising temperature and radical concentrations. However, excessive reduction of the gap distance reduces flame propagation speed due to the flame stretch effect in rich mixtures with the effective Lewis number greater than unity. A nonlinear relationship between pulse repetition frequency and ignition kernel volume is observed in a nanosecond pulsed high frequency discharge (NPHFD). An optimal frequency range of 200 kHz to 2 MHz is found when two pulses are used. In addition, an optimal number of pulses exists for each pulse repetition frequency, with higher frequencies requiring more pulses to maximize the overlap region. These findings provide critical insights on developing controlled plasma discharge techniques for efficient NH 3 ignition in reactive flows within internal combustion engines and gas turbines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

A Linear-Complexity Tensor Butterfly Algorithm for Compressing High-Dimensional Oscillatory Integral Operators

This paper presents a multilevel tensor compression algorithm called tensor butterfly algorithm for efficiently representing large-scale and high-dimensional oscillatory integral operators, including Green's functions for wave equations and integral transforms such as Radon transforms and Fourier transforms. The proposed algorithm leverages a tensor extension of the so-called complementary low-rank property of existing matrix butterfly algorithms. The algorithm partitions the discretized integral operator tensor into subtensors of multiple levels and factorizes each subtensor at the middle level as a Tucker-type interpolative decomposition, whose factor matrices are formed in a multilevel fashion. For a d-dimensional (d > 1) integral operator discretized into a 2d-mode tensor with n2d entries, the overall CPU time and memory requirement scale as O(nd), in stark contrast to the O(nd log n) complexity of existing matrix algorithms such as matrix butterfly algorithms and fast Fourier transforms (FFTs), where n is the number of points per direction. When comparing with other tensor algorithms such as quantized tensor train (QTT), the proposed algorithm also shows superior CPU and memory performance for tensor contraction. Remarkably, the tensor butterfly algorithm can efficiently model high-frequency Green's function interactions between two unit cubes, each spanning 512 wavelengths per direction, which represents problems of scale over 512× larger than that existing butterfly algorithms can handle, with the same amount of computation resources. On the other hand, for a problem representing 64 wavelengths per direction, which is the largest size existing algebraic matrix algorithms can handle, our tensor butterfly algorithm exhibits 200x speedups and 30× memory reduction compared with existing ones. Moreover, the tensor butterfly algorithm also permits O(nd)-complexity FFTs and Radon transforms up to d = 6 dimensions.

Kielstra, P Michael

A meshless stochastic method for Poisson–Nernst–Planck equations

A plethora of biological, physical, and chemical phenomena involve transport of charged particles (ions). Its continuum-scale description relies on the Poisson–Nernst–Planck (PNP) system, which encapsulates the conservation of mass and charge. The numerical solution of these coupled partial differential equations is challenging and suffers from both the curse of dimensionality and difficulty in efficiently parallelizing. We present a novel particle-based framework to solve the full PNP system by simulating a drift–diffusion process with time- and space-varying drift. We leverage Green’s functions, kernel-independent fast multipole methods, and kernel density estimation to solve the PNP system in a meshless manner, capable of handling discontinuous initial states. The method is embarrassingly parallel, and the computational cost scales linearly with the number of particles and dimension. We use a series of numerical experiments to demonstrate both the method’s convergence with respect to the number of particles and computational cost vis-à-vis a traditional partial differential equation solver.

Chemistry

Insight into pseudo-film-boiling in supercritical water under simplified interfacial conditions

The focus of this paper is the physics of supercritical water film boiling through the simulation of natural convection of supercritical water in a rectangular cavity. It has been widely believed that above a fluid's critical point, only one phase exists. However, recent research has indicated the existence of distinct gas-like and liquid-like regions separated by the Widom line, which is the locus of the maxima of the specific heat. Along the Widom line, density decreases sixfold, viscosity drops by a factor of two, while specific heat spikes by an order of magnitude. These variations, specifically in density and viscosity, produce a thick pseudo-interface and flow dynamics behavior akin to film-boiling, denoted here as pseudo-two-phase flow dynamics. When the cavity is heated from the bottom, a pseudo-film of gas-like fluid is formed at the heated wall, and the flow complexity evolves, characterized by the formation of multiple vortices. Results demonstrate the ability of modern conjugate heat transfer computational fluid dynamics to capture the pseudo two-phase regime, with the formation of a pseudo-film at the heated wall. Further, the boiling curve is studied, showing an increase in heat flux with an increase in the temperature differential between the wall and the pseudo-critical temperature. Furthermore, results also show a previously uncharacterized instability, where the convection cells in the cavity oscillate and can flip directions under certain conditions.

Computational fluid dynamics

Site-Projected Thermal Conductivity: Application to Defects, Interfaces, and Homogeneously Disordered Materials

With the rapid advance of high-performance computing and electronic technologies, understanding thermal conductivity in materials has become increasingly important. This study presents a novel method: the site-projected thermal conductivity that quantitatively estimates the local (atomic) contribution to heat transport, leveraging the Green–Kubo thermal transport equations. The effectiveness of this approach on disordered and amorphous graphene, amorphous silicon, and grain boundaries in silicon–germanium alloys is demonstrated. Amorphous graphene reveals a percolation behavior for thermal transport. The results highlight the potential of the method to provide new insights into the thermal behavior of materials, offering a promising avenue for materials design and performance optimization.

36 MATERIALS SCIENCE

Uniting Theory and Experiment to Deliver Flexible MOFS for Superior Methane (NG) Storage

The objective of the project was to use previous insights developed through synthesis and quantitative modeling of rigid metal–organic frameworks (MOFs) in an established synergistic theoretical/experimental team to create, modify, and evaluate flexible MOFs (FlexMOFs) for natural gas (NG) storage and release at practically useful pressures and transform the NG storage economy. The goal was reduced pressure absorbed natural gas (ANG) FlexMOF storage at operating pressures less than 100 bar with physisorption exploiting the favorable thermodynamics and kinetics of flexible porous material opening in response to adsorption. Hydrogen behavior in this context was also considered. The specific aim of the project was to design and develop a standard computational modeling methodology for, first, detailed atomistic retrodiction of FlexMOF gating behavior and ultimately prediction of the effects of functionalization and/or substitution on structural transitioning. The project was also geared towards the establishment of the interaction of methane with the framework and binding sites using modeling and the FlexMOF will be both internally and external validated as a SMART metric. This has value to the scientific community both from the obvious standpoint of providing a better understanding of the promising test case systems (CdIF-13 and the MIL-53(Al) series of MOFs), but also in providing an avenue of obtaining insight into these FlexMOF systems in general, which is of particular interest given the tendency of structure-function correlation to lag behind synthesis methodology (making the latter a hit or miss proposition for applications). This gap remains significant for FlexMOF systems whose gate opening behaviors complicate computational examination. The computational methodologies are relatively inexpensive in terms of both money and computational resources enhancing the general viability of these methodologies. The ultimate gain to the public will be in the application of these techniques to design systems for natural gas storage and use to cut down on green-house emissions.

03 NATURAL GAS

HFIR Activity Workbook Generator (HAWK) User Guide

The HFIR Activity WorkbooK generator (HAWK) is a Python code that automates and streamlines the activity calculation of samples after irradiation in the High Flux Isotope Reactor (HFIR). HAWK’s results provide estimates of the activity and nuclide inventory of irradiated specimens before they are moved to hot cell facilities, where they undergo post-irradiation examination. The samples’ activity results guide the packing of shipping containers and inform the accountable inventories for the hot cell facilities. The toolkit was originally developed by Charles Daily, a former R&D staff member at Oak Ridge National Laboratory (ORNL). As of May 2025, HAWK is developed by the Radiation Transport & HPC Methods Group (Nuclear Energy and Fuel Cycle Division) at ORNL. Figure 1 presents HAWK’s workflow. To use HAWK, users need to: 1. Develop an Excel input workbook (i.e., XLSX extension) containing data from the experiment’s materials, irradiation history (cycles), and irradiation positions. 2. Make minor edits to an existing template JSON file (i.e., auxiliary_data.JSON) and to the Python driver. The driver sets the necessary environment variables, defines the material compositions, and ultimately calls HAWK. Once configured, HAWK runs the Oak Ridge Isotope Generation code (ORIGEN) to calculate the masses, activities, and heat load at the end of irradiation for each isotope in the specimen. ORIGEN is part of SCALE, ORNL’s in-house computational tool for performing nuclear safety and design calculations. Following this step, HAWK postprocesses the results and generates three output workbooks summarizing the activity calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS

Denoising of imaginary time response functions with Hankel projections

Imaginary-time response functions of finite-temperature quantum systems are often obtained with methods that exhibit stochastic or systematic errors. Reducing these errors comes at a large computational cost—in quantum Monte Carlo simulations, the reduction of noise by a factor of two incurs a simulation cost of a factor of four. In this paper, we relate certain imaginary-time response functions to an inner product on the space of linear operators on Fock space. We then show that data with noise typically does not respect the positive definiteness of its associated Gramian. The Gramian has the structure of a Hankel matrix. As a method for denoising noisy data, we introduce an alternating projection algorithm that finds the closest positive definite Hankel matrix consistent with noisy data. We test our methodology at the example of fermion Green's functions for continuous-time quantum Monte Carlo data and show remarkable improvements of the error, reducing noise by a factor of up to 20 in practical examples. We argue that Hankel projections should be used whenever finite-temperature imaginary-time data of response functions with errors is analyzed, be it in the context of quantum Monte Carlo, quantum computing, or in approximate semianalytic methodologies. Published by the American Physical Society 2024

Yu, Yang (ORCID:0000000186178878)

SCALE 6.3 Validation: Nuclear Criticality Safety

The KENO codes have been used extensively around the world since their initial development in the 1960s. Therefore, a large number and wide range of validation reports have been generated for KENO by a variety of organizations. This section provides a synopsis of recent validation reports generated at ORNL, along with a brief list of some older validation reports generated in Oak Ridge, Tennessee. Some of the oldest reports are not attributed directly to ORNL, as the Y-12 Plant (currently the Y-12 National Security Complex), the K-25 Gaseous Diffusion Plant (now the East Tennessee Technology Park), and the X-10 Site (ORNL) were operated as a single entity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Sum-of-Fractions Method

Sum-of-fractions is a method intended to make sure a subcritical margin for aqueous solutions and slurries of fissionable isotopes exists. The method indicates that a system is subcritical if the sum of the ratios of the mass of each isotope (in a mixture) to its individual minimum subcritical mass limit is less than or equal to one. Historically, the basis of the sum-of-fractions has been derived from allowances given in the American National Standards Institute (ANSI)/ American Nuclear Society (ANS)-8.15-1981. However, the allowance was removed in ANSI/ANS-8.15-2014 due to a lack of technical basis. A methodology was developed to assess the validity of using the sum-of-fractions for water- or polyethylene-moderated systems for the following nuclides: 232U, 233U, 234U, 235U, 237Np, 236Pu, 238Pu, 239Pu, 240Pu, 241Pu, 242Pu, 241Am, 242mAm, 243Am, 242Cm, 243Cm, 244Cm, 245Cm, 246Cm, 247Cm, 249Cf, and 251Cf. The methodology uses available benchmark data for mixtures of 233U, 235U, and 239Pu to establish the calculational margin, and a mass limit reduction to establish the margin of subcriticality. Water- or polyethylene-moderated and -reflected mixtures containing the nuclides are evaluated with the code system, SCALE 6.2.4. Including the calculational margin, subcritical mass limits for each nuclide were computed for optimally water- or polyethylene-moderated and fully reflected systems. These masses were used to create nuclide mixtures in which the sum of the mass to subcritical mass limit ratios is one. The various nuclide mixtures were modeled over a range of moderation and demonstrate the keff does not exceed the calculational margin. For additional assurance of subcriticality, a significant mass reduction is applied to each computed minimum critical mass of the nuclides without adequate benchmark data consistent with the method in ANSI/ANS-8.15-2014.

criticality safety, Actinide

Relative sensitivity of plastic scintillator: A comparative analysis with 60 Co gamma rays, deuterium–deuterium, and deuterium–tritium neutrons

A plastic scintillator has found extensive application in the realm of high-energy physics and national security science. Many applications in those fields often involve the simultaneous production of photons, neutrons, and charged particles, which makes the relative sensitivity information for these different radiation types important. In this study, we have adopted a multi-head detector comprised of a plastic scintillator and high gain phototubes, which provides a large dynamic range and linearity. A comparative study on the relative sensitivities of plastic scintillators was facilitated by adopting three distinct radiation calibration sources (i.e., 60 Co γ rays, DD neutrons, and DT neutrons). Neutrons from a DD source generate a comparable level of scintillation to gamma rays emitted by 60 Co (i.e., 60 Co-γ/DD-n = 0.92 ± 16%). DT neutrons induce ~3.5 times the scintillation observed with DD neutrons (i.e., DT-n/DD-n = 3.5 ± 28%). In addition, the Geant4 simulation granted us valuable insights into the relative sensitivity of the scintillator. This comparative study will provide a useful database for users in diverse applications.

47 OTHER INSTRUMENTATION

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