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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Automated tuning for HMC mass ratios

We extended previous work on tuning HMC parameters using gradient information to include Hasenbusch mass ratios. The inclusion of mass ratios adds many more parameters that need to be tuned, and also allows for lots of variations in the choice of integrator pattern. We investigate the effectiveness of automatically tuning a large number of HMC parameters and compare the optimally tuned versions over a range of integrator variants.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Sub‐5 Ångstrom Porosity Tuning in Calixarene‐Derived Porous Liquids via Supramolecular Complexation Construction

Abstract Sub‐Ångstrom‐level porosity engineering, which is appealing in gas separations, has been demonstrated in solid carbon, polymer, and framework materials but rarely achieved in the liquid phase. In this work, a gas molecular sieving effect in the liquid phase at sub‐5 Ångstrom scale is created via sophisticated porosity tuning in calixarene‐derived porous liquids (PLs). Type II PLs are constructed via supramolecular complexation between the sodium salts of calixarene derivatives and crown ether solvents. The chemical structure variation and assembly behavior of the porous host upon PL construction are monitored by spectroscopy‐, X‐ray‐, and neutron‐scattering techniques. The presence of permanent porosity in calixarene‐derived PLs is verified by pressure swing gas uptake, altered CO 2 physisorption behavior, and molecular simulations. Sub‐5 Ångstrom porosity tuning within the PL phase is achieved by introducing bulky substituted groups on the benzene ring of the calixarene host, which then greatly affects the dynamic motion and transport behavior of CO 2 molecules and the Xe uptake performance. The approach being demonstrated in this work represents a promising pathway to tune and leverage the porosity effect for enhanced gas uptake capacity and selectivity in liquid sorbents.

Li, Errui [Department of Chemistry University of T↗
DOE OSTI2025

Sub-5 Ångstrom Porosity Tuning in Calixarene-Derived Porous Liquids via Supramolecular Complexation Construction

Sub-Ångstrom-level porosity engineering, which is appealing in gas separations, has been demonstrated in solid carbon, polymer, and framework materials but rarely achieved in the liquid phase. In this work, a gas molecular sieving effect in the liquid phase at sub-5 Ångstrom scale is created via sophisticated porosity tuning in calixarene-derived porous liquids (PLs). Type II PLs are constructed via supramolecular complexation between the sodium salts of calixarene derivatives and crown ether solvents. The chemical structure variation and assembly behavior of the porous host upon PL construction are monitored by spectroscopy-, X-ray-, and neutron-scattering techniques. The presence of permanent porosity in calixarene-derived PLs is verified by pressure swing gas uptake, altered CO 2 physisorption behavior, and molecular simulations. Sub-5 Ångstrom porosity tuning within the PL phase is achieved by introducing bulky substituted groups on the benzene ring of the calixarene host, which then greatly affects the dynamic motion and transport behavior of CO 2 molecules and the Xe uptake performance. Further, the approach being demonstrated in this work represents a promising pathway to tune and leverage the porosity effect for enhanced gas uptake capacity and selectivity in liquid sorbents.

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

Tuning 3-D Nanomaterial Architectures Using Atomic Layer Deposition to Direct Solution Synthesis

The ability to synthesize nanoarchitected materials with tunable geometries provides a means to control their functional properties, with applications in biological, environmental, and energy fields. To this end, various bottom-up and top-down synthesis processes have been developed. However, many of these processes require prepatterning or etching steps, making them challenging to scale-up to complex, nonplanar substrates. Furthermore, the ability to integrate nanomaterials into hierarchical arrays with precise control of feature spacing and orientation remains a challenge. One approach to overcome these patterning challenges is the use of surface modification layers to guide the resulting geometry of nanomaterial architectures grown from the substrate. A powerful strategy to accomplish this is what we will refer to as “surface-directed assembly,” where the resulting geometric parameters (feature size, shape, orientation) are predetermined by the initial surface layer. In particular, the use of Atomic Layer Deposition (ALD) to form a surface layer, followed by solution-based growth processes, has the ability to synthesize architected structures with tunable geometries on complex, nonplanar surfaces. Over the past decade, we have reported a series of studies where surface-directed assembly is used to synthesize ZnO nanowires (NWs) on top of a variety of substrates. In this case, a thin film of ZnO is deposited onto the substrate using ALD, which can guide the NW diameter, spacing, and angular orientation with respect to the substrate by controlling epitaxial relationships. Furthermore, we have shown that by depositing a submonolayer overcoat of a secondary material (e.g., amorphous TiO 2 ), nucleation sites are partially blocked, which can further tune the spacing between nanowires while minimizing changes to their other geometric properties. This approach can be used to generate multilevel hierarchical structures, such as hyperbranched NW arrays with tunable control of each level of hierarchy using ALD. Finally, we have demonstrated that the tunable control of geometric parameters can be scaled-up to curved, nonplanar substrates. This highlights the power of ALD to conformally and uniformly deposit the seed layers on complex substrates with subnanometer precision. To complement these seeded hydrothermal approaches, we expanded this strategy to include conversion chemistry of the initial ALD seed layers. For example, by replacing ZnO with Al 2 O 3 as the seed layer without changing the hydrothermal growth conditions, Al–Zn layered-double hydroxide nanosheets can be formed instead of nanowires. In another example of conversion chemistry, a solution anion-exchange process was used to incorporate sulfur into ALD metal oxide films. In both of these conversion processes, the properties of the initial ALD film enabled tuning of the resulting nanostructure geometry. In this Account, we describe the use of ALD to guide the growth of diverse nanomaterial systems, with tunable control over their geometry and composition. We further show how these approaches can be used to tune functional properties for a range of applications, including superomniphobic surfaces, antibiofouling coatings, and photocatalysis. In conclusion, we conclude with an outlook on how the combination of ALD and solution synthesis can enable future directions in scalable nanomanufacturing to overcome the limitations of traditional top-down and bottom-up approaches.

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

Pressure tuning of competing interactions on a honeycomb lattice

Exchange interactions are mediated via orbital overlaps across chemical bonds. Thus, modifying the bond angles by physical pressure or strain can tune the relative strength of competing interactions. Here we present a remarkable case of such tuning between the Heisenberg (J) and Kitaev (K) exchange, which respectively establish magnetically ordered and spin liquid phases on a honeycomb lattice. We observe a rapid suppression of the Néel temperature (T N ) with pressure in Ag 3 LiRh 2 O 6 , a spin-1/2 honeycomb lattice with both J and K couplings. Using a combined analysis of x-ray data and first-principles calculations, we find that pressure modifies the bond angles in a way that increases the ∣K/J∣ ratio and thereby suppresses T N . Consistent with this picture, we observe a spontaneous onset of muon spin relaxation (μSR) oscillations below T N at low pressure, whereas in the high pressure phase, oscillations appear only when T < T N /2. Unlike other candidate Kitaev materials, Ag 3 LiRh 2 O 6 is tuned toward a quantum critical point by pressure while avoiding a structural dimerization in the relevant pressure range.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Advanced thermal/environmental barrier coatings of high-entropy rare earth disilicates tuned by strong anharmonicity of Eu 2 Si 2 O 7

Advancing thermal/environmental barrier coating (TEBC) materials with integrated thermal-mechanical functions is paramount for safeguarding SiC-based ceramic matrix composites (CMCs) in high-efficiency gas turbines. Herein, we employ a synergistic approach, combining density functional theory (DFT) methods and combinatorial chemistry techniques, to design high-performance and low-cost RE 2 Si 2 O 7 (RE = rare earth elements) TEBC materials tailored for enhanced compatibility with SiC-based CMCs. Expanding on phase stability of alloying pure RE 2 Si 2 O 7 , the investigation extends to the mechanical and thermal properties of solid solution systems, including Er 1/2 Y 3/4 Yb 3/4 Si 2 O 7 , Gd 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 , and Eu 1/4 Er 1/4 Y 3/4 Yb 3/4 Si 2 O 7 . The solid solution systems exhibit a major reduction in lattice thermal conductivity relative to their pure counterparts, achieving ultralow values of 0.25 to 0.39 W m −1 K −1 at 1500 K. Furthermore, the coefficients of thermal expansion (CTE) of these solid solutions are precisely tuned within the desired range for SiC (4.4 to 5.5 × 10 −6 K −1 ), while maintaining good mechanical properties. Here, in particular, the addition of Eu 2 Si 2 O 7 demonstrates to be an important variable to the tuning of CTE and lattice thermal conductivity by leveraging its strong anharmonicity, presenting a pioneering avenue for fine-tuning material properties. In summary, this research not only identifies promising TEBC materials with superior thermal properties, but also introduces a valuable computational material design methodology for the rapid discovery of complex materials for harsh environments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhancing generative molecular design via uncertainty-guided fine-tuning of variational autoencoders

In recent years, deep generative models have been successfully applied to various molecular design tasks, particularly in the life and materials sciences. One critical challenge for pre-trained generative molecular design (GMD) models is to fine-tune them to be better suited for downstream design tasks that aim at optimizing specific molecular properties. However, redesigning and training an existing effective generative model from scratch for each new design task are impractical. Furthermore, the black-box nature of typical downstream tasks that involve property prediction makes it nontrivial to optimize the generative model in a task-specific manner. In this work, we propose an uncertainty-guided fine-tuning strategy that can effectively enhance a pre-trained variational autoencoder (VAE) for GMD through performance feedback in an active learning setting. The strategy begins by quantifying the model uncertainty of the generative model using an efficient active subspace-based UQ (uncertainty quantification) scheme. Next, the decoder diversity within the characterized model uncertainty class is explored to expand the viable space of molecular generation. The low-dimensionality of the active subspace makes this exploration tractable using a black-box optimization scheme, which in turn enables us to identify and leverage a diverse set of high-performing models to generate enhanced molecules. Empirical results across six target molecular properties using multiple VAE-based generative models demonstrate that our uncertainty-guided fine-tuning strategy consistently leads to improved models that outperform the original pre-trained models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Morphology and property tuning in ZnO–Ni hybrid metamaterials in vertically aligned nanocomposite (VAN) form

ZnO thin films have attracted significant interest in the past decades owing to their unique wide band gap properties, piezoelectric properties, non-linearity and plasmonic properties. Recent efforts have been made in coupling ZnO with secondary phases to enhance its functionalities, such as Au–ZnO nanocomposite thin films with tunable optical and plasmonic properties. In this work, magnetic nanostructures of Ni are incorporated in ZnO thin films in a vertically aligned nanocomposite (VAN) form to couple magnetic and plasmonic response in a complex hybrid metamaterial system. Nickel (Ni) is of interest due to its ferromagnetic and plasmonic properties along with gold (Au) which is also plasmonic. Therefore, two approaches, namely, tuning of the deposition pressure and use of a ZnO–Au seeding layer have been attempted to achieve unique Ni nanostructures in addition to tuning of the microstructure. Together, both approaches demonstrate a range of microstructures such as core–shell, nanodisk, nanocup, and nanocube-like morphologies not previously attempted. Additionally, there is effective tuning of properties. Specifically, the seeding layer thickness causes hyperbolic behavior as well as redshift in the surface plasmon resonance (SPR) wavelength. The addition of the ZnO–Au seeding layer directly influences the optical properties. Plus, regardless of the different approaches, the films demonstrate magnetic anisotropy based on the composition and microstructure of the film which impacted the saturation magnetization and coercivity. This study demonstrates the potential of ZnO-based complex hybrid metamaterials with coupled electro-magneto-optical properties for integrated photonic devices.

Bhatt, Nirali A. [Purdue Univ., West Lafayette, IN↗
DOE OSTI2025

Tuning effect of vanadium substitution on the structural and electronic properties of potassium hollandite surfaces

Metal oxide surfaces possess unique properties that are crucial for a wide variety of applications. Herein, density functional theory calculations are performed to study surfaces of potassium hollandite, KMn 8 O 16 , a promising cathode material for electrochemical energy storage, and the vanadium-substituted analog KMn 7 VO 16 . The results show that there is a clear increase in the stability of KMn 8 O 16 with (001) < (110) < (100) or (010), apt to adopt an elongated rod-like morphology. The vanadium (V)-substitution lowers the crystal symmetry and prefers to occupy the surface sites, resulting in electron redistribution and selective tuning of surface energy depending on the surface structures. In particular, the higher stability of substituted V 4+ compared with Mn 4+ ions leads to stabilization of the (001) surface due to the direct interaction of reduced Mn δ+ ions on the surface, while such tuning effect decreases with the increase in surface stability, (110) > (100) and (010). As a result, the KMnO 16 rod is shortened upon V-substitution as observed experimentally, effectively facilitating the ion transport during discharge. The V substituents also introduce stabilization to the defect surfaces resulting from Mn 2+ dissolution during cycling, thereby hindering further structural decay. In conclusion, our study demonstrates the potential tuning effect of V-substitution to promote the ion transport and mitigate the capacity degradation of α-MnO 2 -based materials.

25 ENERGY STORAGE↗
DOE OSTI2026

Simulation of Channel Flow with Square Ribs for Blanket First-Wall Cooling: Geometry-Specific Tuning of k-ω Model Using Adjoint Method

Cooling of the plasma-facing first wall is challenging in the design of blanket components because of the high heat flux (on the order of 𝑀𝑊/𝑚2) from the plasma, especially when a low thermal mass medium like helium is chosen as the coolant. Therefore, heat transfer enhancement in which the convective heat transfer rate is augmented by the addition of turbulence-promoting structures becomes a key initiative for providing sufficient cooling capability with helium. Previously, computational fluid dynamics simulations had been performed on pipe flows with different transverse and longitudinal ribbed geometries at Oak Ridge National Laboratory to compare the enhancement performance among different ribbed geometries. Rib shape morphing had been conducted to obtain an optimized rib profile. In the work presented here, the adjoint method is adopted in the ANSYS Fluent solver for turbulence model augmentation, and the Generalized k-ω (GEKO) turbulence model is employed because of its ability of tuning the turbulence model. The Nusselt number and pressure drop obtained from the channel flow with bottom ribbed wall experiments are used as the targets. Sensitivity analysis provides information as guidance to improve the turbulence model accuracy. The augmented GEKO model is tuned for the studied ribbed channel geometry and flow conditions, providing improved predictive accuracy within this context. Extension to other configurations offers potential but may require additional tuning and validation.

Xu, Tracy [ORNL] (ORCID:0009000193700887)↗
DOE OSTI2026

Customized Bayesian optimization for efficient beam tuning at the facility for rare isotope beams

Bayesian optimization (BO) has recently emerged as a powerful approach for on-line beam tuning, and it is rapidly gaining adoption across accelerator facilities due to its flexibility and efficiency in handling complex optimization tasks. At the Facility for Rare Isotope Beams, rapid and reliable tuning is essential to support the delivery of diverse ion species. To improve the practicality of BO in this setting, we implemented several enhancements, including scalarized composite objective construction for multicriteria optimization, asynchronous evaluation for better resource utilization, prior-mean-assisted optimization to accelerate convergence, and a local search strategy for rapid completion of the task. We present the details of these methods, discuss challenges-encountered, and share our experience applying them to specific beam-tuning tasks.

Accelerators & storage rings↗
DOE OSTI2025

Visual Instance-aware Prompt Tuning

Visual Prompt Tuning (VPT) has emerged as a parameter-efficient fine-tuning paradigm for vision transformers, with conventional approaches utilizing dataset-level prompts that remain the same across all input instances. We observe that this strategy results in sub-optimal performance due to high variance in downstream datasets. To address this challenge, we propose Visual Instance-aware Prompt Tuning (ViaPT), which generates instance-aware prompts based on each individual input and fuses them with dataset-level prompts, leveraging Principal Component Analysis (PCA) to retain important prompting information. Moreover, we reveal that VPT-Deep and VPT-Shallow represent two corner cases based on a conceptual understanding, in which they fail to effectively capture instance-specific information, while random dimension reduction on prompts only yields performance between the two extremes. Instead, ViaPT overcomes these limitations by balancing dataset-level and instance-level knowledge, while reducing the amount of learnable parameters compared to VPT-Deep. Extensive experiments across 34 diverse datasets demonstrate that our method consistently outperforms state-of-the-art baselines, establishing a new paradigm for analyzing and optimizing visual prompts for vision transformers.

Xiao, Xi [ORNL] (ORCID:0009000009316982)↗
DOE OSTI2025

Simulation-Based Inference for Neutrino Interaction Model Tuning

This project demonstrates, for the first time, the application of simulation-based inference (SBI) techniques to tune neutrino–nucleus interaction models. Using a mock dataset based on the MicroBooNE tuning of the GENIE event generator, our approach employs a Neural Posterior Estimator (NPE) with Masked Autoregressive Flows (MAF) to infer the posterior distributions of key GENIE parameters directly from simulated histograms. The workflow provides a scalable and amortized framework for performing likelihood-free inference in high-dimensional parameter spaces, offering a pathway to more efficient and uncertainty-aware model tuning for next-generation neutrino experiments such as DUNE and SBND.

Tame-Narvaez, KarlaMaria [Fermi National Accelerat↗
DOE OSTI2025

A Scientist-in-the-Loop Data Analytics Framework for Intelligent Simulation Model Tuning and Validation

This project developed a scientist-in-the-loop data analytics framework for intelligent simulation model tuning and validation, targeting the Weather Research and Forecasting (WRF) model and its solar energy variant, WRF-Solar-BNL. Domain experts, such as climate scientists, depend on large-scale numerical simulations for knowledge discovery and decision-making, yet the complexity of parameter tuning and the disconnect between automated optimization and domain expertise pose significant challenges. We extended an interactive visual analytics framework that enables domain experts to observe and intervene in the computational steering process by identifying disagreements between the simulation model, surrogate model, and the expert’s domain knowledge. Using Bayesian Optimization with Gaussian Process Regression as the surrogate model, our system allows users to probe parameter relationships, analyze correlation patterns, and adjust tuning parameters in real time. We developed use cases for solar irradiance forecasting through sustained collaboration with Brookhaven National Laboratory, resolving critical model configuration challenges and achieving meaningful reductions in prediction error. The project supported one PhD student, one MS student, and eight undergraduate students across three Data Science Capstone projects, resulting in one master’s thesis.

Dasgupta, Aritra [New Jersey Institute of Technolo↗
DOE OSTI2026

A Systematic Framework for Tuning Open-Source Multifunctional IBR Models To Emulate OEM Black-Box Fault Dynamics

This paper presents a systematic framework to tune a generic IBR EMT model to match with an OEM provided balckbox inverter model based on the fault current responses. The key learnings and findings are summarized as follows: The tunable key parameters include inner control loops and current limiters to align the fault current magnitude, sequence content, and phase trajectories with the OEM models across diverse fault type and locations. The tuned model's fidelity is validated through comparative analysis with an OEM blackbox model, assessing both the fault current response and the responses of multiple relay elements. The results demonstrate the tuned generic model can trigger relay decision logic that is identical or near identical to that of the OEM model, thus generating very good match model for fault studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Test cavity and Iris-to-Coax transition for tuning and high-power verification of SNS DTL iris couplers

The Spallation Neutron Source (SNS) Drift Tube Linac (DTL) employs iris couplers to efficiently deliver RF power into the accelerating structure. To support the development, tuning, and high‑power conditioning of these couplers prior to installation in the actual DTLs, a dedicated test cavity and an iris‑to‑coaxial transition structure have been designed. This work presents the electromagnetic design, simulation, and optimization of the test setup, enabling precise characterization of the iris coupler’s performance. The transition structure allows for tuning of the iris opening dimensions without requiring a waveguide taper or full‑size waveguide transitions, while maintaining impedance matching between the coaxial feed and the iris geometry to minimize reflection and power loss. During low‑power tests, the iris opening di-mensions can be evaluated using the iris‑to‑coax transi-tion attached to the test cavity. For high‑power condi-tioning, full‑size waveguides with ceramic vacuum win-dows are connected to the test cavity to replicate opera-tional conditions. Key design parameters were optimized using computer-aided simulation, and sensitivity studies were conducted to assess the impact of mechanical toler-ances on RF performance. The resulting test platform provides a reliable and efficient means for tuning and validating iris couplers, contributing to improved opera-tional stability in the SNS DTL.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗
DOE OSTI2026

Axion dark matter search with a photonic bandgap cavity haloscope and dielectric tuning rod over 10.25-10.45 GHz

We report the development of a new widely tunable cavity and demonstrate its use in a search for dark matter axions. We achieve unloaded quality factors above $10^{5}$, roughly $25\times$ larger than a bare copper cavity at the same frequency, using concentric sapphire shells to reduce Ohmic losses on the cavity barrel. A rotating sapphire rod tunes our cavity mode over the $10.1-11.7$ GHz range, approximately $16\%$ of its resonant frequency. Using an amplified receiver chain, we demonstrate sensitivity to new axion parameter space by tuning the cavity over the $200$ MHz range between $10.25-10.45$ GHz (42.4 - 43.2, $μ$eV) to constrain the axion-to-photon coupling to $|g_{aγγ}|$$\leq$ 1 $\times$$10^{-12}$${GeV}^{-1}$. This cavity can scan its tuning range about $9$ times faster compared to a bare copper cavity when paired with a photon counting device, laying the groundwork for a definitive search for the QCD axion over $10.1-11.7$ GHz.

Lynn, Morgan [Chicago U.]↗
DOE OSTI2024

Colossal Strain Tuning of Ferroelectric Transitions in KNbO 3 Thin Films

Strong coupling between polarization ( P ) and strain (ɛ) in ferroelectric complex oxides offers unique opportunities to dramatically tune their properties. Here colossal strain tuning of ferroelectricity in epitaxial KNbO 3 thin films grown by sub‐oxide molecular beam epitaxy is demonstrated. While bulk KNbO 3 exhibits three ferroelectric transitions and a Curie temperature ( T c ) of ≈676 K, phase‐field modeling predicts that a biaxial strain of as little as −0.6% pushes its T c > 975 K, its decomposition temperature in air, and for −1.4% strain, to T c > 1325 K, its melting point. Furthermore, a strain of −1.5% can stabilize a single phase throughout the entire temperature range of its stability. A combination of temperature‐dependent second harmonic generation measurements, synchrotron‐based X‐ray reciprocal space mapping, ferroelectric measurements, and transmission electron microscopy reveal a single tetragonal phase from 10 K to 975 K, an enhancement of ≈46% in the tetragonal phase remanent polarization ( P r ), and a ≈200% enhancement in its optical second harmonic generation coefficients over bulk values. These properties in a lead‐free system, but with properties comparable or superior to lead‐based systems, make it an attractive candidate for applications ranging from high‐temperature ferroelectric memory to cryogenic temperature quantum computing.

36 MATERIALS SCIENCE↗