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DOE OSTI2021

Fabrication, Measurement, and Modeling of GaInP/GaAs Three-Terminal Cells and Strings

Three-terminal (3T) GaInP/GaAs solar cells are fabricated from inverted-grown monolithic tandems and processed with external metal contacts suitable for easy interconnection. Prototype 3T tandems both with and without tunnel junctions are demonstrated. They are characterized as a function of two independent variables in a variety of configurations, with each configuration holding one of the contacts common to two source-meter units (SMUs). Each of these different measurement configurations completely characterizes the device by transforming the results into 6 unique device parameters and plotting the total power parametrically in two dimensions. The performance is fit using a 3T optoelectronic model that includes luminescent coupling as well as important resistances. Eight of these devices are interconnected in various voltage-constrained configurations to form voltage-matched (VM) strings. Measurement and analysis of these III-V devices and strings are generally applicable to all 3T photovoltaics.

photovoltaics↗

DOE OSTI2025

QuadTune version 1: a regional tuner for global atmospheric models

When a new, better-formulated physical parameterization is introduced into a global atmospheric model, aspects of the global model solutions are sometimes degraded. Then, in order to use the new global model to address science questions, there is an incentive to restore its accuracy. Oftentimes this restoration is achieved by tuning of model parameter values. Unfortunately, the retuning process is expensive because characterizing the parameter dependence requires numerous time-consuming global simulations. To reduce the cost of tuning, this manuscript introduces a “poor man's” model tuner, “QuadTune”. QuadTune carves the globe into regions and approximates the model parameter dependence through the use of an uncorrelated quadratic emulator (i.e., response surface). The simplicity of the emulator reduces the required number of global model simulations and aids explainability of tuner behavior. Tuning removes parametric error but leaves behind model structural error. Structural error manifests itself as regional residual biases, such as stubborn biases and tuning trade-offs. To visualize these residual biases, QuadTune's software includes a set of diagnostic plots. This paper illustrates the use of the plots for characterizing residual biases with an example tuning problem.

Environmental sciences↗

NASA NTRS1987

Quantitative analysis of the reconstruction performance of interpolants

The analysis presented provides a quantitative measure of the reconstruction or interpolation performance of linear, shift-invariant interpolants. The performance criterion is the mean square error of the difference between the sampled and reconstructed functions. The analysis is applicable to reconstruction algorithms used in image processing and to many types of splines used in numerical analysis and computer graphics. When formulated in the frequency domain, the mean square error clearly separates the contribution of the interpolation method from the contribution of the sampled data. The equations provide a rational basis for selecting an optimal interpolant; that is, one which minimizes the mean square error. The analysis has been applied to a selection of frequently used data splines and reconstruction algorithms: parametric cubic and quintic Hermite splines, exponential and nu splines (including the special case of the cubic spline), parametric cubic convolution, Keys' fourth-order cubic, and a cubic with a discontinuous first derivative. The emphasis in this paper is on the image-dependent case in which no a priori knowledge of the frequency spectrum of the sampled function is assumed.

Lansing, Donald L.↗

NASA NTRS1998

User Manual for Beta Version of TURBO-GRD: A Software System for Interactive Two-Dimensional Boundary/ Field Grid Generation, Modification, and Refinement

TURBO-GRD is a software system for interactive two-dimensional boundary/field grid generation. modification, and refinement. Its features allow users to explicitly control grid quality locally and globally. The grid control can be achieved interactively by using control points that the user picks and moves on the workstation monitor or by direct stretching and refining. The techniques used in the code are the control point form of algebraic grid generation, a damped cubic spline for edge meshing and parametric mapping between physical and computational domains. It also performs elliptic grid smoothing and free-form boundary control for boundary geometry manipulation. Internal block boundaries are constructed and shaped by using Bezier curve. Because TURBO-GRD is a highly interactive code, users can read in an initial solution, display its solution contour in the background of the grid and control net, and exercise grid modification using the solution contour as a guide. This process can be called an interactive solution-adaptive grid generation.

Choo, Yung K.↗

DOE OSTI2026

Biopolymer-Templated Titania Film Formation for Nanostructured Coatings Revealed by Machine Learning-Supported Time-Resolved Analysis

This study presents a machine learning approach to derive the film formation of biopolymer-templated titania nanostructures during spray deposition, in combination with in situ grazing-incidence small-angle X-ray scattering (GISAXS). A neural network trained on synthetic GISAXS data directly predicts domain-size distributions from experimental two-dimensional scattering patterns, capturing the full kinetics of nanostructure evolution with high temporal resolution. The predictions reveal hierarchical size distributions and periodic growth features, consistent with layer-by-layer spray deposition and validated by complementary scanning electron microscopy (SEM) imaging. Quantitative comparison with conventional parametric GISAXS fits shows good qualitative agreement, with systematic differences explained by domain-shape assumptions and resolved by applying a geometric scaling factor. Simulated SEM-like surfaces derived from neural network outputs reproduce the porous, foam-like nanoscale morphology observed experimentally, reinforcing the method’s credibility. This integrated approach enables real-time, nondestructive, statistically averaged monitoring of bulk nanostructure development in functional coatings, offering a scalable methodology to accelerate the characterization and process control of sustainably manufactured nanostructured titania films for energy-related applications such as photocatalysis and photovoltaics.

Heger, JulianEliah↗

DOE OSTI2022

Latent Space Dynamics Identification

LaSDI is a data-driven physical simulation software that forms a latent space for a given high-fidelity model and discovers a set of ordinary differential equations for the latent space dynamics. It allows a fast and accurate solution process, which is useful for multi-query decision making applications, such as design optimization and uncertainty quantification. The performance of the LaSDI framework is demonstrated on four different problems, i.e., 1D and 2D Burgers equations, nonlinear heat conduction, and radial advection problems. Both linear and nonlinear compression techniques, such as neural network and proper orthogonal decomposition, are used to form a latent space. A concept of local dynamics identification procedure is introduced to enable a parametric model, which enhances the accuracy level over a given parameter space.

Fries, William↗

NASA NTRS2002

Radiation Effects in a Semitransparent Gray Coating Heated by Convection and Cooled by Radiation

A parametric study using a one dimensional model of a semitransparent gray thermal barrier coating was performed to gain an understanding of the role thermal radiation can play in the heat transferred. Some ceramic materials are semitransparent in the wavelength ranges were thermal radiation is important. Therefore, absorption, emission, and scattering of thermal radiation can affect the he at transfer through the coating. In this paper, a one dimensional layer was used to model the heat transfer process occurring, in a burner test rig. The semitransparent layer is heated by a hot gas flowing over its surface. The layer and substrate at a cooled by radiation to the surroundings. The back side of the substrate is insulated. The coating is assumed to be gray (absorption and scattering coefficients are not function of wavelength). An absorption coefficient of 0.3/cm and scatter a rig coefficients of 0 (no scattering) and 100/cm (isotropic scattering) were used. The thickness and thermal conductivity of the layer are varied. The results show that the temperatures are affected by the properties of the semitransparent .ever and the emissivity of the substrate. The substrate and surface temperatures are presented. The apparent temperature an optical pyrometer would read for the emitted energy is also given. An apparent thermal conductivity was calculated for the layer.

Spuckler, Charles M.↗

NASA NTRS2022

Are Soybean Models Ready for Climate Change Food Impact Assessments?

An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO 2 concentration [CO 2 ] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO 2 ]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO 2 ] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble, ensemble mean yield responses to temperature and [CO 2 ] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO 2 ] and temperature is needed to reduce the uncertainty from the individual models.

Agricultural Model Inter-comparison and Improvemen↗

DOE OSTI2023

Ultra‐Low‐Loss Silicon Nitride Photonics Based on Deposited Films Compatible with Foundries

Abstract The fabrication processes of silicon nitride (Si 3 N 4 ) photonic devices used in foundries require low temperature deposition, which typically leads to high propagation losses. Here, it is shown that propagation loss as low as 0.42 dB cm −1 can be achieved using foundry compatible processes by solely reducing waveguide surface roughness. By postprocessing the fabricated devices using rapid thermal anneal (RTA) and furnace anneal, propagation losses down to 0.28 dB cm −1 and 0.06 dB cm −1 , respectively, are achieved. These low losses are comparable to the conventional devices using high temperature, high‐stress LPCVD films. The dispersion of the devices is also tuned, and it is proved that these devices can be used for linear and nonlinear applications. Low threshold parametric oscillation, broadband frequency combs, and narrow‐linewidth laser are demonstrated. This work demonstrates the feasibility of scalable photonic systems based on foundries.

Ji, Xingchen↗

DOE OSTI2025

Sensitivity to longitudinal vector boson scattering and doubly charged Higgs boson production in $W^± W^± jj$ at future hadron colliders

We study the sensitivity to longitudinal vector boson scattering at a 27-, 50-, and 100-TeV pp collider using events containing two leptonically decaying same-electric-charge 𝑊 bosons produced in association with two jets. The baseline FCC-hh detector parametrization within the D ELPHES framework is used under the assumption of fully efficient pileup mitigation. A tightly constrained phase space with a dijet mass greater than 2 TeV is considered in order to suppress the impact of potential instrumental backgrounds. Based on this setup, the expected sensitivity to the production of longitudinally polarized same-sign 𝑊 boson pairs is evaluated. Additionally, expected limits are set on doubly charged Higgs bosons produced via vector boson fusion processes and decaying to same-sign 𝑊 boson pairs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been well studied as DAC sorbent materials due to their tunable structural and compositional properties. Thermodynamic simulations using force fields are often used to provide predictions of a material’s performance in many separations. However, these force fields often make assumptions about bonds and the physics of the adsorption process. A new class of force fields called machine-learned force fields (MLFFs) use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). In this work, models were developed to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using MLFFs. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John↗

NASA NTRS2004

Turbulent Jet Flames Into a Vitiated Coflow

Examined is the vitiated coflow flame, an experimental condition that decouples the combustion processes of flows found in practical combustors from the associated recirculating fluid mechanics. The configuration consists of a 4.57 mm diameter fuel jet into a coaxial flow of hot combustion products from a lean premixed flame. The 210 mm diameter coflow isolates the jet flame from the cool ambient, providing a hot environment similar to the operating conditions of advanced combustors; this important high temperature element is lacking in the traditional laboratory experiments of jet flames into cool (room) air. A family of flows of increasing complexity is presented: 1) nonreacting flow, 2) all hydrogen flame (fuel jet and premixed coflow), and 3) set of methane flames. This sequence of experiments provides a convenient ordering of validation data for combustion models. Laser Raman-Rayleigh-LIF diagnostics at the Turbulent Diffusion Flame laboratory of Sandia National Laboratories produced instantaneous multiscalar point measurements. These results attest to the attractive features of the vitiated coflow burner and the well-defined boundary conditions provided by the coflow. The coflow is uniform and steady, isolating the jet flame from the laboratory air for a downstream distance ranging from z/d = 50-70. The statistical results show that differential diffusion effects in this highly turbulent flow are negligible. Complementing the comprehensive set of multiscalar measurements is a parametric study of lifted methane flames that was conducted to analyze flame sensitivity to jet and coflow velocity, as well as coflow temperature. The linear relationship found between the lift-off height and the jet velocity is consistent with previous experiments. New linear sensitivities were found correlating the lift-off height to coflow velocity and temperature. A blow-off study revealed that the methane flame blows off at a common coflow temperature (1260 K), regardless of coflow or jet velocity. An explanation for this phenomenon is that entrainment of ambient air at the high lift-off heights prevents autoignition. Analysis of the results suggests that flame stabilization occurs through a combination of flame propagation, autoignition, and localized extinction processes. Proposed is an expanded view of distributed reaction combustion based on analysis of the distributions of probe volume conditions at the stabilization region of the lifted hydrogen and methane flames. Turbulent eddies the size of the flame thickness mix fuel and hot coflow across the flame front, thereby enhancing the reaction zone with autoignition of reactants at elevated temperatures; this is the reverse effect of turbulent flames in ambient air, where intense turbulence in cool mixtures result in localized extinction. Each of the three processes (i.e., flame propagation, autoignition and localized extinction) contributes to flame stabilization in varying degrees, depending on flow conditions.

Holdeman, James D.↗

DOE OSTI2024

Sol-gel derived silicate-phosphate glass SiO 2 –P 2 O 5 –CaO–TiO 2 : The effect of titanium isopropoxide on porosity and thermomechanical stability

Despite of several decades lasting extensive research of bioactive and bioresorbable glasses the systematic parametrization and determination of the key factors affecting porosity and thermomechanical characteristics still remains challenging. Here, we present silica-phosphate glasses, with the composition 70SiO 2 - 20P 2 O 5 - (10-x)CaO-xTiO 2 (mol%; x = 0, 2.5, 5, and 7.5), prepared by sol -gel method and reinforced by titanium dioxide via titanium isopropoxide (TTIP) incorporation which demonstrated tunable variation of porosity from micro-to macro -region and superb mechanical integrity during the calcination process. The presence of 7.5 mol% TiO 2 promotes dimensional stability up to 1000°C as investigated by thermomechanical analysis. The XRD showed the dominant presence of silicon phosphate [Si(P 2 O 7 )], titanium phosphate [Ti(P 2 O 7 )] and calcium phosphates [β-Ca(P 2 O 6 ) and γ- Ca 2 (P 2 O 7 )]. The effect of TiO 2 doping on the multiscale morphology and porosity was investigated by means of SEM, MIP, μCT, N 2 adsorption and USAXS/SAXS. Increasing TiO 2 content leads to the formation of open porosity up to 70vol% and drives the formation of a refined interconnected macroporosity of 2-30 μm. In contrast, mesoporosity with a dominance of 3-6nm pores decreases in all samples with increasing TiO 2 content. USAXS/SAXS revealed an increase in primary particle size with increasing TiO 2 content which is in good agreement with the nitrogen physisorption analysis showing that microporosity decreases with increasing TiO2 content.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Air separation and N 2 purification with Ba 0.15 Sr 0.85 FeO 3-$δ$ via a two-step thermochemical process

Thermochemical air separation to produce high-purity N 2 was demonstrated in a vertical tube reactor via a two-step reduction–oxidation cycle with an A-site substituted perovskite Ba 0.15 Sr 0.85 FeO 3–δ (BSF1585). BSF1585 particles were synthesized and characterized in terms of their chemical, morphological, and thermophysical properties. A thermodynamic cycle model and sensitivity analysis using computational heat and mass transfer models of the reactor were used to select the system operating parameters for a concentrating solar thermal-driven process. Thermal reduction up to 800 °C in air and temperature-swing air separation from 800 °C to minimum temperatures between 400 and 600 °C were performed in the reactor containing a 35 g packed bed of BSF1585. The reactor was characterized for dispersion, and air separation was characterized via mass spectrometry. Gas measurements indicated that the reactor produced N 2 with O 2 impurity concentrations as low as 0.02 % for > 30 min of operation. Additionally, a parametric study of air flow rates suggested that differences in observed and thermodynamically predicted O 2 impurities were due to imperfect gas transport in the bed. Temperature swing reduction/oxidation cycling experiments between 800 and 400 °C in air were conducted with no statistically significant degradation in N 2 purity over 50 cycles.

14 SOLAR ENERGY↗

DOE OSTI2022

Coupled Cluster Downfolding Methods: the effect of double commutator terms on the accuracy of ground-state energies

Downfolding coupled cluster (CC) techniques have recently been introduced into quantum chemistry as a tool for the dimensionality reduction of the many-body quantum problem. As opposed to earlier formulations in physics and chemistry based on the concept of effective Hamiltonians, the appearance of the downfolded Hamiltonians is a natural consequence of the single-reference exponential parametrization of the wave function. In this paper, we discuss the impact of higher-order terms originating in double commutators. In analogy to previous studies, we consider the case when only one- and two-body interactions are included in the downfolded Hamiltonians. We demonstrate the efficiency of the many-body expansions involving single and double commutators for the unitary extension of the downfolded Hamiltonians on the example of the beryllium atom, and bond-breaking processes in the Li2 and H2O molecules. For the H2O system, we also analyze energies obtained with downfolding procedures as functions of the active space size.

quantum computing, quantum algorithms, electronic ↗

DOE OSTI2025

Lie-algebraic classical simulations for quantum computing

The classical simulation of quantum dynamics plays an important role in our understanding of quantum complexity and in the development of quantum technologies. Efficient techniques such as those based on the Gottesman-Knill theorem for Clifford circuits, tensor networks for low entanglement-generating circuits, or Wick's theorem for fermionic Gaussian states have become central tools in quantum computing. In this work, we contribute to this body of knowledge by presenting a framework for classical simulations, dubbed “𝔤-sim”, which is based on the underlying Lie algebraic structure of the dynamical process. When the dimension of the algebra grows at most polynomially in the system size, there exist observables for which the simulation is efficient. Indeed, we show that 𝔤-sim enables new regimes for classical simulations, is able to deal with certain forms of noise in the evolution, as well as can be used to tackle several paradigmatic variational and nonvariational quantum computing tasks. For the former, we perform Lie-algebraic simulations to train and optimize parametrized quantum circuits (thus effectively showing that some variational models can be dequantized), design enhanced parameter initialization strategies, solve tasks of quantum circuit synthesis, and train a quantum-phase classifier. For the latter, we report large-scale noiseless and noisy simulations on benchmark problems. By comparing the limitations of 𝔤-sim and certain Wick's theorem-based simulations, we find that the two methods become inefficient for different types of states or observables, hinting at the existence of distinct, nonequivalent resources for classical simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Study of the f 0 ( 980 ) and f 0 ( 500 ) Scalar Mesons through the Decay D s + → π + π − e + ν e

Using e + e − collision data corresponding to an integrated luminosity of 7.33 fb − 1 recorded by the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, we present an analysis of the decay D s + → π + π − e + ν e , where the D s + is produced via the process e + e − → D s * ± D s ∓ . We observe the f 0 ( 980 ) in the π + π − system and the branching fraction of the decay D s + → f 0 ( 980 ) e + ν e with f 0 ( 980 ) → π + π − measured to be ( 1.72 ± 0.1 3 stat ± 0.1 0 syst ) × 10 − 3 , where the uncertainties are statistical and systematic, respectively. The dynamics of the D s + → f 0 ( 980 ) e + ν e decay are studied with the simple pole parametrization of the hadronic form factor and the Flatté formula describing the f 0 ( 980 ) in the differential decay rate, and the product of the form factor f + f 0 ( 0 ) and the c → s Cabibbo-Kobayashi-Maskawa matrix element | V c s | is determined for the first time to be f + f 0 ( 0 ) | V c s | = 0.504 ± 0.01 7 stat ± 0.03 5 syst . Furthermore, the decay D s + → f 0 ( 500 ) e + ν e is searched for the first time but no signal is found. The upper limit on the branching fraction of D s + → f 0 ( 500 ) e + ν e , f 0 ( 500 ) → π + π − decay is set to be 3.3 × 10 − 4 at 90% confidence level. Published by the American Physical Society 2024

Ablikim, M.↗

DOE OSTI2022

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

59 BASIC BIOLOGICAL SCIENCES↗