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DOE OSTI2025

Strong anharmonicity dictates ultralow thermal conductivities of type-I clathrates

Type-I clathrate solids have attracted significant interest due to their ultralow thermal conductivities and sub- sequent promise for thermoelectric applications, yet the mechanisms underlying these properties are not well understood. Here, we extend the framework of vibrational dynamical mean-field theory (VDMFT) to calculate temperature-dependent thermal transport properties of solids using a many-body Green’s function approach. When applied to a coarse-grained description of 𝑋 8 Ga 16 Ge 30 , where 𝑋= Ba, Sr, we find that nonresonant scattering between cage acoustic modes and rattling modes leads to a reduction of acoustic phonon lifetimes and thus thermal conductivities. Moreover, we find that the moderate temperature dependence of conductivities above 300 K, which is consistent with experimental measurements, cannot be reproduced by textbook perturbation theory calculations, which predict a 𝑇 −1 dependence. Therefore, we suggest that nonperturbative anharmonic effects, including four- and higher-phonon scattering processes, are responsible for the ultralow thermal conductivities of type-I clathrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Transition from Vehicular to Structural Ionic Transport in Electrified Alkali Aqueous Solutions

A molecular understanding of the solvation and dynamics of ions under static electric fields is crucial for modelling a wide range of natural and technological processes. Yet, traditional simulation methods suffer from a trade-off that has to be made between accuracy and statistical convergence. To bridge this gap, herein we extend our recently introduced Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) approach to investigate the solvation structures and ionic transport mechanisms of electrified alkali cationic solutions. We obtain ionic conductivities for Li+, Na+ and Cs+ from the field dependence of the ionic current density in good agreement with experiment. Surprisingly, the migration mechanism is found to be strikingly different for the three ions despite their similar ionic conductivities. While Li+ conducts predominantly through vehicular migration of a stable 4-fold coordinated ion at all field strengths, Cs+ conducts strictly through a structural diffusion mechanism, where 9-12 transient first shell water coordination bonds are broken and renewed. Notably, aqueous Na+ emerges as a “Goldilocks” ion: its ion-water interactions are strong enough to maintain distinct 5-6 fold coordination shells at zero field (unlike Cs+) yet labile enough to be strongly perturbed by electric fields (unlike Li+). As a consequence, we observe an electric field-induced transition from vehicular to structural ionic transport for Na+ that is accompanied by a marked increase in the ionic current density. Our results imply that the conductance mechanism of ions with moderate ion-solvent interactions can be effectively tuned by external electric fields.

Joll, Kit↗

DOE OSTI2026

Insights into elevated temperature tensile deformation mechanisms and kink banding in additively manufactured tungsten

Additive manufacturing (AM) potentially enables fabrication and repair of plasma facing components (PFCs) of tungsten. However, deformation mechanisms in AM-fabricated tungsten under service-relevant thermomechanical conditions remain unknown majorly due to challenges in achieving crack-free W. This study reveals the deformation mechanisms operative under tension at 800 °C and 1200 °C in the electron beam melting powder bed fusion (EBM-PBF) fabricated W. Textured columnar grains with mixed <001 >/<111 >|| build-direction were observed. Strong anisotropy in tensile properties persisted across test temperatures, and all specimens exhibited extensive deformation-induced banding phenomena. Grain boundary character analysis of the deformed specimens indicated that these deformation bands were kink bands with tilt grain boundaries prominently present at the band-matrix interface. Interestingly, the material within the kink bands rotated toward higher resolved shear stress, providing insights into the origins of kink band formation in body-centered cubic refractory metals. Intragranular misorientation axis analysis revealed that plasticity was dominated by {110} <111 > slip at 800 °C, whereas additional (213)[11⁢̄1] and (112)[11⁢̄1] slip systems activated at 1200 °C. A dense low-angle boundary networks observed near fractured surface indicated the onset of dynamic recrystallization. Results reveal plasticity governing mechanisms in AM-fabricated W under power plant-relevant conditions, and provide insights into kink band attributes in refractory metals.

Mayes, Riley [ORNL] (ORCID:000900089307010X)↗

DOE OSTI2026

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗

DOE OSTI2026

Phase Stability and Electrochemical Performance of La-Site-Doped Li6La3Zr0.5Nb0.5Ta0.5Hf0.5O12 High-Entropy Garnets

We investigate La-site substitution in the high-entropy garnet Li6La3Zr0.5Nb0.5Ta0.5Hf0.5O12 (LLZNTH) using Ba2+, Sr2+, and Sm3+ to elucidate how dopant governs phase stability, Li-site distribution, and electrochemical behavior. X-ray diffraction shows that Sr2+ is incorporated homogeneously into the garnet lattice, whereas the larger Ba2+ and smaller Sm3+ ions partially exceed the structural tolerance, generating secondary phases. Nevertheless, the Sm-doped composition (x = 0.05) exhibits the highest room-temperature ionic conductivity (2.7 × 10–4 S cm–1). Neutron powder diffraction reveals that Sm substitution drives a redistribution of Li+ from the tetrahedral 24 d sites into the higher-mobility 96 h positions, enhancing the connectivity of the three-dimensional Li-ion migration network. A Sm-doping series (x = 0.01–0.05) further shows that only sufficiently high Sm levels induce this redistribution, whereas lower concentrations retain Li arrangements similar to the undoped garnet. Critical current density measurements demonstrate that La-site dopants also influence interfacial stability against Li metal, underscoring a trade-off between bulk transport enhancement and mechanical robustness. Collectively, these findings reveal that in high-entropy garnets improved ionic conductivity can originate not only from phase-pure structures but also from targeted modification of the Li sublattice, even when accompanied by secondary phases, offering a compositional design principle for garnet electrolytes.

Li, Chang [Mechanical Engineering, School of Scien↗

DOE OSTI2024

Laser-induced graphene gas sensors for environmental monitoring

Artemesia tridentatais a foundational plant taxon in western North America and an important medicinal plant threatened by climate change. Low-cost fabrication of sensors is critical for developing large-area sensor networks for understanding and monitoring a range of environmental conditions. However, the availability of materials and manufacturing processes is still in the early stages, limiting the capacity to develop cost-effective sensors at a large scale. In this study, we demonstrate the fabrication of low-cost flexible sensors using laser-induced graphene (LIG); a graphitic material synthesized using a 450-nm wavelength bench top laser patterned onto polyimide substrates. We demonstrate the effect of the intensity and focus of the incident beam on the morphology and electrical properties of the synthesized material. Raman analyses of the synthesized LIG show a defect-rich graphene with a crystallite size in the tens of nanometers. This shows that the high level of disorder within the LIG structure, along with the porous nature of the material provide a good surface for gas adsorption. The initial characterization of the material has shown an analyte response represented by a change in resistance of up to 5% in the presence of volatile organic compounds (VOCs) that are emitted and detected byArtemisiaspecies. Bend testing up to 100 cycles provides evidence that these sensors will remain resilient when deployed across the landscapes to assess VOC signaling in plant communities. The versatile low-cost laser writing technique highlights the promise of low-cost and scalable fabrication of LIG sensors for gas sensor monitoring.

Chemistry↗

DOE OSTI2026

Quality and Loss Factor Characterization of YBCO Superconducting Transmission Lines for Axion Dark Matter Detection

Axion haloscope experiments aim to detect the conversion of axions into microwave photons under a strong magnetic field through resonant cavity techniques. The conversion produces an extremely small signal, requiring a cryogenic environment to reduce thermal noise, and low-loss superconducting transmission lines for minimal attenuation in the readout chain. Yttrium barium copper oxide (YBCO) cables are a promising candidate. Unlike commonly used low-loss cryogenic cables such as niobium (Nb) and niobium titanium (NbTi), which have low critical fields, YBCO is a high-temperature superconductor that can remain stable in strong magnetic fields. We characterized the quality and loss of five stripline resonators from the Brookhaven Technology Group: three YBCO, a copper reference, and a silver reference. Experimental methodology included collecting scattering parameter data on a vector network analyzer for the samples at 77 K along with room temperature baseline measurements, and employing both Lorentzian-fit and circle-fitting techniques to confirm the coupling regime and corroborate results. We achieved quality factors on the order of $10^3$ with corresponding loss factors on the order of $10^{-1}$ dB/m. Trends were comparable with literature data on Nb and NbTi at 4 K, which did have lower loss under these conditions, but suggested similar or perhaps better loss for YBCO when accounting for the temperature difference. We also developed a cryogenic probe for future measurements in a 14 T applied field at 30 mK. This will serve to directly evaluate YBCO's durability in magnetic fields, and we expect significantly improved performance at millikelvin temperatures.

Marinos, Z. [UCLA]↗

DOE OSTI2025

A General Solution Route to Nanoporous Metal Oxide Films

Metal oxide semiconductors are of interest as efficient, stable, and low-cost photoanode materials for photoelectrochemical water splitting, but their characteristically poor charge transport properties remain a fundamental challenge to practical use. Nanoporous metal oxide films that feature open bicontinuous networks of nanocrystals and nanopores can overcome such inefficient charge transport to enable high-performance photoanodes. Here, this paper describes a general method to make high-quality nanoporous films of metal oxides by spin coating and calcining molecular inks that contain a porosity-generating block copolymer. Phase-pure nanoporous films of BiFeO 3 , FeWO 4 , WO 3 , Fe 2 O 3 , and TiO 2 serve to demonstrate the versatility of the approach. It is demonstrated that the crystallite size, film porosity, and film thickness can be independently tuned by adjusting the ink composition and film processing conditions. The method is extended to fabricate core–shell nanoporous films consisting of a nanoporous film coated in a thin shell of a second metal oxide, using WO 3 –BiVO 4 and BiFeO 3 –BiVO 4 as examples. Given its simplicity and flexibility, this solution-phase route should prove useful for making nanoporous films of many different materials for a variety of applications, including energy conversion and storage, catalysis, and chemical sensing.

coating materials↗

DOE OSTI2026

Mechanistic origin of solvent-dependent thermal stability in sodiated Sn anodes for sodium-ion batteries

Understanding the thermal stability of high-energy density alloy anodes is critical for the safe deployment of sodium-ion batteries (SIBs). Here, accelerating rate calorimetry (ARC), post-mortem characterizations, and density functional theory (DFT) calculations are combined to understand the thermal reactivity of fully sodiated Sn, Sn-hard carbon (HC) blends, and HC anodes in carbonate- and ether-based electrolytes. ARC measurements show that propylene carbonate (PC) causes earlier self-heating rate (SHR) onset and higher reactivity than tetraethylene glycol dimethyl ether (TEGDME), indicating inferior thermal stability. Sodiated Sn exhibits better thermal stability than sodiated HC, while Sn-HC blends show intermediate behavior that improves with increasing Sn content. Post-ARC analyses reveal desodiation of Na15Sn4 to metallic Sn with particle coalescence, whereas Sn-HC blends and HC retain finer morphologies. PC promotes Sn oxidation to SnO, while TEGDME suppresses oxide formation; NaPF6-containing electrolytes additionally form NaF. DFT calculations show that PC adsorption lowers Na extraction energy and enhances interfacial electronic interactions, facilitating Na release and reductive decomposition. These results establish a direct correlation between solvent-dependent reaction pathways and thermal stability in SIB alloy anodes.

Accelerating rate calorimetry↗

DOE OSTI2026

Treatment of Lagoon Dairy Manure Wastewater via Iron Electrocoagulation, Microfiltration, and Adsorption

Dairy manure wastewater generated by flushing barn cow waste contains nutrients, pathogens, and organic and inorganic contaminants. This study utilized a process consisting of iron electrocoagulation (Fe-EC), microfiltration (MF), and activated carbon (AC) adsorption to treat farm wastewater and explore the reclamation of clean water for irrigation and livestock consumption. Significant removal (>99.9%) of chemical oxygen demand (COD), total organic carbon (TOC), phosphorus (P), turbidity, and microorganisms, as well as ions including magnesium, calcium, sulfur, and silica was achieved by the combined EC-MF-AC process. Specifically, a charge loading of ∼37,500 C/L in a continuous-flow EC configuration, followed by MF, achieved more than 95% removal of TOC and COD. Characterization of produced flocs and foam via scanning-electron microscopy with energy-dispersal spectroscopy and Fourier transform infrared spectroscopy confirmed the removal of ions, including calcium, sulfur, and silica. A key finding was the electrocatalytic conversion of nitrogen species to ammonia gas through the intermediate reduction of nitrate/nitrite, which led to ∼60% total nitrogen (TN) removal. AC treatment further improved TN removal to ∼70%. The Fe-EC process also eradicated >99.9% of bacteria. Preliminary process cost assessment, based on recycled materials for EC electrodes, showed significant cost savings (∼2 times) compared to commercial electrodes.

Dutta, Swapnamoy [ORNL]↗

DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗

DOE OSTI2026

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗

DOE OSTI2023

Overcoming the Entropy Penalty of Direct Air Capture for Efficient Gigatonne Removal of Carbon Dioxide

Atmospheric carbon poses an existential threat to civilization via global climate change. Hundreds of gigatonnes of carbon dioxide must be removed from earth’s atmosphere in the next three decades, necessitating a low-cost, energy-efficient process to extract low concentrations of carbon dioxide for conversion to a stable material permanently stored for thousands of years. In this work, the challenge of removing gigatonnes of CO 2 is described via the scale of effort and the thermodynamics of collecting and reducing this diffuse chemical, the accumulation of which imparts a substantial entropy penalty on any atmospheric carbon capture process. The methods of CO 2 reduction combined with upstream direct air capture (DAC) including absorption, membrane separation, and adsorption are compared with biomass torrefaction and permanent burial (BTB). A Monte Carlo model assesses the mass, energy, and economics of the full process of biomass torrefaction from biomass collection and transport to stable carbon burial to determine that 95% of scenarios could remove carbon for less than $200 per CO 2 -tonne-equivalent. Torrefied carbon is further discussed for its long-term stability and availability at the scale required to substantially mitigate the threat of climate change.

biomass↗

DOE OSTI2024

Framework of compressive sensing and data compression for 4D-STEM

Four-dimensional Scanning Transmission Electron Microscopy (4D-STEM) is a powerful technique for high-resolution and high-precision materials characterization at multiple length scales, including the characterization of beam-sensitive materials. However, the field of view of 4D-STEM is relatively small, which in absence of live processing is limited by the data size required for storage. Furthermore, the rectilinear scan approach currently employed in 4D-STEM places a resolution- and signal-dependent dose limit for the study of beam sensitive materials. Improving 4D-STEM data and dose efficiency, by keeping the data size manageable while limiting the amount of electron dose, is thus critical for broader applications. Here we introduce a general method for reconstructing 4D-STEM data with subsampling in both real and reciprocal spaces at high fidelity. The approach is first tested on the subsampled datasets created from a full 4D-STEM dataset, and then demonstrated experimentally using random scan in real-space. The same reconstruction algorithm can also be used for compression of 4D-STEM datasets, leading to a large reduction (100 times or more) in data size, while retaining the fine features of 4D-STEM imaging, for crystalline samples.

4D-STEM↗

DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗

DOE OSTI2026

Methanol mixing−controlled compression ignition enabled via homogeneous charge compression ignition of dimethyl ether through catalytic decomposition of methanol

Methanol is a potentially attractive fuel for marine and off−road engines owing to its availability at bunkering and global distribution locations. Although methanol is well−distributed worldwide, its fuel chemistry and ignition properties make it poorly suited as a direct drop−in replacement for diesel fuel in compression−ignition engines. However, industrial processes are regularly used to convert methanol, via catalytic dehydration, to dimethyl ether (DME) over nonprecious metal catalysts. This chemical conversion can occur at relatively low pressures, temperatures, and catalyst space velocities, highlighting a potential opportunity to generate DME via onboard catalytic dehydration of methanol. DME’s fuel kinetic and ignition properties for compression ignition are much more favorable than those of methanol or even diesel fuel, but DME is more challenging than diesel fuel or methanol to pump, store, and deliver through conventional diesel fueling injection hardware. Thus, a potential opportunity exists to use the ignition and kinetic properties of DME, with the transportation and delivery advantages of methanol, in a methanol−fueled mixing−controlled compression−ignition engine. The present work explores performance, combustion behavior, and emissions reduction opportunities for methanol mixing−controlled combustion, enabled by a HCCI of DME that represents a small fraction of the total fuel energy that can be generated onboard via catalytic dehydration of methanol.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗

DOE OSTI2026

A review of United States energy-only generator interconnection service policy and considerations for reform

Grid interconnection has emerged as a significant obstacle to the development of new electricity resources. There is growing interest in energy-only interconnection, which is an interconnection service option meant to allow the interconnection of new generators without ensuring their energy deliverability during all hours through the transmission system to customers. This approach potentially avoids upfront congestion-related transmission upgrades but could increase curtailment risk. Interest in energy-only interconnection is shaped by incomplete understanding of how interconnection policy functions in different jurisdictions, a knowledge gap that makes it difficult to determine how energy-only interconnection might be better used or re-designed. In this paper, we provide a regulatory review of energy-only interconnection in U.S. interconnection policy and practice, identifying jurisdictions in which rules are close to -or farther from-the theoretical concept of energy-only interconnection service. We find substantial jurisdictional differences in how energy-only interconnection is implemented, driven by differences in resource adequacy frameworks, real-time transmission operations, and state-level procurement practices. U.S. regulators have preferred local jurisdictional flexibility over federal prescription of interconnection study methods and procedures, which also contributes to differences among regions. Such findings raise fundamental questions about whether competition policies in electricity markets should extend beyond spot energy markets and into more prescriptive guidelines around interconnection rules and market entry. This paper sheds light on tensions that energy-only interconnection raises in allowing generators to access the transmission system on an as available basis and discusses how controlling thresholds for congestion-related network upgrades may be a barrier to electricity market entry.

Gorman, Will↗