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DOE OSTI2025

Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) of zwitterionic organic HCl salts

In this work, we benchmark quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) for determining the crystal structures of two zwitterionic organic HCl salts, L-ornithine HCl ( Orn ) and L-histidine HCl·H 2 O ( Hist ). These salts present an interesting challenge for QNMRX-CSP, as gas-phase geometry optimizations used to generate starting structures for the organic zwitterionic fragments fail to capture their correct solid-state geometries. To overcome this limitation, geometry optimizations using the COSMO water-solvation model are employed to generate initial structural models. Using this approach, QNMRX-CSP yields structural models of the two zwitterionic organic HCl salts that closely match experimentally determined crystal structures. In addition, the application of QNMRX-CSP to Hist represents a further step toward the de novo structural determination of solvated organic HCl salts, as Hist is the first benchmark system of this type to include a water molecule as a component of its crystal structure. This work is significant for its potential application to the structural determination of active pharmaceutical ingredients, which often feature complex organic components and solvated solid forms.

Fleischer, Carl H. [Florida State Univ., Tallahass↗

DOE OSTI2025

Growth and structure of alpha-Ta films for quantum circuit integration

Tantalum films incorporated into superconducting circuits have exhibited low surface losses, resulting in long-lived qubit states. The remaining loss pathways originate in microscopic defects that manifest as two level systems (TLSs) at low temperatures. These defects limit performance, so careful attention to tantalum film structures is critical for optimal use in quantum devices. In this work, we investigate the growth of tantalum using magnetron sputtering on sapphire, Si, and photoresist substrates. In the case of sapphire, we present procedures for the growth of fully-oriented films with α-Ta [1 1 1]//Al2O3 [0 0 0 1] and α-Ta [1 −1 0]//Al2O3 [1 0 −1 0] orientational relationships and having residual resistivity ratio (RRR) ∼ 60 for 220 nm thick films. On Si, we find a complex grain texturing with Ta [1 1 0] normal to the substrate and RRR ∼ 30. We further demonstrate airbridge fabrication using Nb to nucleate α-Ta on photoresist surfaces. For the films on sapphire, resonators show TLS-limited quality factors of 1.3 ± 0.3 × 106 at 10 mK (for a waveguide gap and conductor width of 3 and 6 μm, respectively). Structural characterization using scanning electron microscopy, x-ray diffraction, low temperature transport, secondary ion mass spectrometry, and transmission electron microscopy reveal the dependence of residual impurities and screw dislocation density on processing conditions. The results provide practical insights into the fabrication of advanced superconducting devices including qubit arrays and guide future works on crystallographically deterministic qubit fabrication.

42 ENGINEERING↗

DOE OSTI2025

Symmetry is the Key to the Design of Reticular Frameworks

De novo prediction of reticular framework structures is a challenging task for chemists and materials scientists. Herein, a computational workflow that predicts a list of possible reticular frameworks based on only the connectivity and symmetry of node and linker building blocks is presented. This list is ranked based on the occurrence of topologies in known structures, thus providing a manageable number of structures that can be optimized using density functional theory, and inform future experiments. This workflow is broadly applicable, correctly predicts known reticular materials, and furthermore identifies novel unknown phases for some systems.

COF↗

DOE OSTI2024

Variation of the Passive Film on Compositionally Concentrated Dual-Phase Al 0.3 Cr 0.5 Fe 2 Mn 0.25 Mo 0.15 Ni 1.5 Ti 0.3 and Implications for Corrosion

The passive film on a dual-phase Al 0.3 Cr 0.5 Fe 2 Mn 0.25 Mo 0.15 Ni 1.5 Ti 0.3 FCC + Heusler (L2 1 ) compositionally concentrated alloy formed during extended exposure to an applied potential in the passive range in dilute chloride solution was characterized. Each phase, with its own distinct composition of passivating elements, formed unique passive films separated by a heterophase interface. High-resolution, surface sensitive characterization enabled chemical analysis of the passive film formed over individual phases. The film formed over the L2 1 phase had a higher concentration of Al, Ni, and Ti, while the film formed over FCC phase was of similar thickness but contained comparatively higher Cr, Fe, and Mo concentrations, consistent with the differences in bulk microstructure composition. The passive film was continuous across phase boundaries and the distribution of passivating elements (Al, Cr, and Ti) indicated both phases were independently passivated. Spatially resolved analysis of the surface chemistry of the dual-phase CCA revealed that the cation with the highest composition in passive film formed on the FCC phase was Cr (52.4 at. pct) and for the L2 1 phase was Ti (53.1 at. pct) despite the bulk concentration of each element being below 20 at. pct in their respective phases. Al, Cr, and Ti were enriched in both phases within the passive film relative to their respective bulk compositions. In parallel studies, single-phase alloys with compositions representative of the FCC and L2 1 phases were synthesized to evaluate the corrosion behavior of each phase in isolation. The corrosion behavior of the dual-phase alloy showed passivity evidenced by a pitting potential of 0.615 V SCE in 0.01 M NaCl. The pitting potential and other electrochemical parameters suggested a combination of behaviors of both single-phase samples, suggesting that the global corrosion behavior may be represented by a composite theory applied to phases, their area fractions, and interphase length. However, the interphase in the dual-phase CCA was a local corrosion initiation site and may limit localized corrosion protectiveness. The alloy design implications for optimization of second phase structure and morphology are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Physicochemical properties of digital light processing 3D-Printed alumina and mullite ceramics

Alumina ceramics fabricated using conventional techniques such as uniaxial pressing or injection molding are popular due to their low density, excellent insulation, and mechanical properties. However, these methods often limit the fabrication of complex geometries with high dimensional accuracy due to tooling constraints and limited design freedom. To overcome these limitations, this study employed Digital Light Processing (DLP) additive manufacturing (AM), which enables the production of precise structures. In addition, the optimization of sintering parameters to enhance the densification and performance of alumina and mullite ceramics was investigated, with a specific focus on how varying sintering temperatures and hold times affect part shrinkage, geometric accuracy, and material integrity. Flexural strength of both alumina and mullite specimens was clearly influenced by the way the layers was stacked. When layers were arranged across the direction of the applied load (Z = 4; XZ), the strength was higher than when they were stacked along the same direction as the load (Z = 3; XY). Weibull analysis based on these results showed high modulus values across all samples, indicating good reliability in the flexural strength measurements. This reliability, combined with the clear influence of sintering parameters, highlights how processing conditions effect the material properties and mechanical performance of parts produced through DLP additive manufacturing. In conclusion, these findings open new avenues for ceramic AM across various applications, enhancing the potential for innovation in fields such as aerospace, biomedical engineering, and energy.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Machine learning-guided design, synthesis, and characterization of atomically dispersed electrocatalysts

The recent integration of machine learning into materials design has revolutionized the understanding of structure–property relationships and optimization of material properties beyond the trial-and-error paradigm. On one hand, machine learning has significantly accelerated the development of atomically dispersed metal-nitrogen-carbon (M-N-C) electrocatalysts, which traditionally heavily relied on heuristic approaches. On the other hand, the primary challenge of leveraging machine learning to expedite M-N-C materials discovery lies in the cost associated with data collection. Here, we review recent machine learning integration strategies for M-N-C catalyst development, including discussions on the typical algorithms such as symbolic regression and convolutional neural networks employed for the theoretical design, synthesis optimization via active learning, and advanced microscopy characterization. Subsequently, we provide our perspective on potential near-future directions for furthering machine learning-assisted development of new M-N-C catalysts and elucidating the complex physicochemical mechanisms governing the selectivity, activity, and durability in this class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Corrosion resistant hot melt adhesive to bind metals

Hot melt adhesives (HMAs) play an important role in many industries, and their demand is expected to grow. HMAs don't require any solvents, and their application results in the formation of strong bonds with the substrate upon cooling within seconds. These properties differentiate them from liquid glues and make them preferable for practical application. Currently, commercial HMAs are used in bonding lightweight materials such as paper, polymers, and cartons, and have limited usage in areas necessitating the bonding of heavier objects like metals. Here, in this study, we report a design and testing of versatile platform comprising an ion-coordinating polymer and ionic fillers for performance optimization and understanding of structure–property relationships, enabling the rational design of HMAs with improved adhesion to metal surfaces. All-atom Molecular dynamics (MD) simulations and various characterization methods are used to elucidate the adhesion mechanism in model composite system containing polyethylene oxide mixed with chemically diverse salt particles. The maximum adhesion strength is found in composites with Al(OH) 3 and FeCl 3 fillers. Interestingly, the presence of Al(OH) 3 also provides a multifunctional anticorrosion property as measured electrochemically using the Tafel method. The discovered path to formulations with improved adhesion to metal surfaces constitutes an important step toward advancing HMAs for use in the structural and semi-structural metal work domain.

Adhesive and cohesive forces↗

DOE OSTI2025

Photon counting with intensified charge coupled device (ICCD) – I. In-depth detector characterization

While the adsorption properties of transition metal catalysts have been widely studied, leading to the discovery of various scaling relations, descriptors of catalytic activity, and well-established computational models, a similar understanding of semiconductor catalysts has not yet been achieved. In this work, we present a high-throughput density functional theory investigation into the adsorption properties of 5 oxides of interest to the photocatalytic CO 2 reduction reaction: TiO 2 (rutile and anatase), SrTiO 3 , NaTaO 3 , and CeO 2 . Using a systematic approach, we exhaustively identify unique surfaces and construct adsorption structures to undergo geometry optimizations. We then perform a data-driven analysis, which reveals the presence of weak adsorption energy scaling relations, the propensity of adsorbates of interest to interact with oxygen surface sites, and the importance of slab deformation upon adsorption. Our findings are presented in the context of experimental observations and in comparison to previously studied classes of catalysts, such as pure metals and tellurium-containing semiconductors, and reinforce the need for a comprehensive approach to the study of site-specific surface phenomena on semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Systematic computational study of oxide adsorption properties for applications in photocatalytic CO 2 reduction

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Ambient Synthesis for Fe(II) Polypyridyl Complexes with an Order of Magnitude Increase in Charge-Transfer Excited-State Lifetimes over [Fe(bpy) 3 ] 2+

Replacing precious metals with abundant metals is an important research focus in photochemical energy conversion and storage to meet global energy demands. However, transition metal complexes (TMCs) based on abundant 3d metals typically possess photochemical disadvantages─such as short charge-transfer excited-state lifetimes─and molecular modifications have focused on optimizing the interplay of structure, dynamics, and energetics to overcome their limitations. One strategy to do so is the use of bespoke ligands that can extend the lifetimes of chemically useful excited states. Here, in this study, we report the synthesis and characterization of novel Fe(II) complexes featuring lengthy polypyridyl ligands that can be readily synthesized. Steady-state and transient absorption spectroscopies indicate that these complexes have desirable properties and their excited metal-to-ligand charge-transfer states live an order of magnitude longer than in the benchmark [Fe(bpy) 3 ] 2+ . This lifetime is largely preserved in the heteroleptic complexes, thereby enabling the preparation of asymmetric complexes. Additionally, we apply nonradiative transition theory to explain the long-time decay kinetics. In light of their ease of preparation and reasonable excited-state lifetimes, we suggest the use of these complexes in Fe(II) dye-sensitized solar cells, where the rate of charge injection would be competitive with increased lifetime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Zeolitic Imidazole Framework Decorated Substrates for Lead Removal From Water

Lead contamination in water supplies necessitates efficient and mechanistically understood removal strategies. Zeolitic imidazole frameworks (ZIFs) are promising adsorbents; however, ZIF-67 (Co-based) is more susceptible to hydrolysis than its zinc analogue ZIF-8, raising questions about stability during metal uptake. In this study, we systematically compare ZIF-8 and ZIF-67 under controlled pH conditions and evaluate how substrate anchoring influences hydrolytic stability and Pb 2+ adsorption behavior. By integrating adsorption capacity measurements, kinetic analysis, metal-node leaching data, and structural characterization, we distinguish ion exchange from framework degradation and clarify the temporal interplay between adsorption and hydrolysis. Although ZIF-67 exhibits greater hydrolytic sensitivity, coordination with phosphoryl-bearing Mucor hiemalis membranes significantly reduces Co 2+ leaching and enhances structural retention. Under the optimized conditions (pH 5), ZIF-67@Mucor achieves a maximum Pb 2+ adsorption capacity of 867 mg g −1 . These findings demonstrate that substrate-dependent stabilization enables controlled exploitation of ZIF reactivity for aqueous metal remediation.

Adsorption↗

DOE OSTI2025

High-resolution high-throughput spatiotemporal strain imaging reveals loss mechanisms in a surface acoustic wave device

Surface acoustic wave devices are key components for processing radio frequency signals in wireless communication because these devices offer simultaneously high performance, compact size and low cost. The optimization of the device structure requires a quantitative understanding of energy conversion and loss mechanisms. Here we use stroboscopic full-field diffraction x-ray microscopy to reveal an unanticipated acoustic loss in a prototypical one-port resonator device. A non-uniform acoustic excitation in the active area was responsible for the substantial end and side leakages observed at the design frequency. Quantitative analysis of the strain amplitude using a wave decomposition method allowed the determination of several key device parameters. This high-resolution high-throughput spatiotemporal strain imaging technique is more generally applicable to the study of dynamic strain modulation in nanoscale acoustic, electronic, optical and quantum devices. The high sensitivity allows precise measurement of the strain modulation with picometer-scale amplitude.

Zhou, Tao [ESRF - The European Synchrotron, Grenob↗

DOE OSTI2024

Accelerating the design of lattice structures using machine learning

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R 2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Probing electronic and dielectric properties of ultrathin Ga 2 O 3 /Al 2 O 3 atomic layer stacks made with in vacuo atomic layer deposition

Ultrathin (1–4 nm) films of wide-bandgap semiconductors are important to many applications in microelectronics, and the film properties can be sensitively affected by defects especially at the substrate/film interface. Motivated by this, an in vacuo atomic layer deposition (ALD) was developed for the synthesis of ultrathin films of Ga 2 O 3 /Al 2 O 3 atomic layer stacks (ALSs) on Al electrodes. It is found that the Ga 2 O 3 /Al 2 O 3 ALS can form an interface with the Al electrode with negligible interfacial defects under the optimal ALD condition whether the starting atomic layer is Ga 2 O 3 or Al 2 O 3 . Such an interface is the key to achieving an optimal and tunable electronic structure and dielectric properties in Ga 2 O 3 /Al 2 O 3 ALS ultrathin films. In situ scanning tunneling spectroscopy confirms that the electronic structure of Ga 2 O 3 /Al 2 O 3 ALS can have tunable bandgaps (E g ) between ~2.0 eV for 100% Ga 2 O 3 and ~3.4 eV for 100% Al 2 O 3 . With variable ratios of Ga:Al, the measured E g exhibits significant non-linearity, agreeing with the density functional theory simulation, and tunable carrier concentration. Furthermore, the dielectric constant of ultrathin Ga 2 O 3 /Al 2 O 3 ALS capacitors is tunable through the variation in the ratio of the constituent Ga 2 O 3 and Al 2 O 3 atomic layer numbers from 9.83 for 100% Ga 2 O 3 to 8.28 for 100% Al 2 O 3 . The high ε leads to excellent effective oxide thickness ~1.7–2.1 nm for the ultrathin Ga 2 O 3 /Al 2 O 3 ALS, which is comparable to that of high-K dielectric materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Pure edge-dislocation half-loops in low-temperature Ga⁢N for V-defect formation

Lateral injection of carriers through semipolar crystallographic planes into c-plane QWs is one of the new frontiers in III-N light-emitting diodes (LEDs), especially for long wavelengths. Strategic use of V-defects has proven to be the most promising method for lateral injection, and creating optimal V-defect structure and density is an important research area for reducing forward voltage and increasing wall plug efficiency. Here, in this article, we present a novel method for forming V-defects in nominally unstressed low-temperature Ga⁢N through the generation of pure edge-dislocation half-loops. We present a detailed material science analysis of the loops via scattering-contrast electron microscopy. The loops have pure-edge character with Burgers vector 1/3 ⁢⟨$11\bar{2}0$⟩, and form in a sessile orientation on {$11\bar{2}0$} a-planes. The two arms of the loops are inclined such that the extra half-planes face down toward the growth substrate. The dislocation loops can be used to intentionally form V-defects through conditions of kinetically limited growth: these conditions also favor nucleation of V-defects at ∼100% of other threading dislocations in the Ga⁢N templates. Patterned sapphire substrates (PSS) are one of the most important substrates for III-N LED growth because of their superior light extraction. However, due to its low threading dislocation density, PSS have not been used extensively for V-defect LEDs. This work provides a pathway for improved control of V-defect formation and density on LEDs grown on sapphire with the goal of enabling uniform lateral injection in these V-defect engineered LEDs with low forward voltage, including PSS for high light extraction.

LEDs↗

DOE OSTI2024

An Experimental Setup for Mechanical Vibration Analysis Using VLC

This study explores the potential applications across various domains, including earthquake detection and warning systems, where the system’s sensitivity to ground vibrations can contribute to early seismic event detection. Additionally, the study paves the way of developing applications of VLC/T in mechanical vibration and stability analysis of engines and platforms, offering insights into structural integrity and performance optimization. These multifaceted applications underscore the adaptability and potential of VLC/T systems in diverse fields, heralding advancements in sensing, communication, and security technologies. To achieve this, in this study, Peak to Average Power Ratio (PAPR) is proposed to represent the impact of mechanical shocks and vibrations generated by several weights dropped onto the platform with which the receiver is fixed. Even though non-contact measurement methodology is preferred for various reasons, the proposed measurement campaign obtains the data in contact form; however, the system and signal model proposed in this study could easily be extended into non-contact form. Considering the fact that the proposed measurement campaign employs off-the-shelf products, it is cost-effective and very scalable.

Yilmaz, Ahmet Mucahit↗

DOE OSTI2026

A User-Friendly GUI Tool for Automated Microstructural Analysis of Fiber-Reinforced Composites and Porous Structures

Understanding and quantifying microstructural features such as fiber orientation and porosity is critical for predicting the mechanical behavior and performance of fiber-reinforced polymer composites. Traditional manual analysis is time-consuming, subjective, and unsuitable for high-throughput datasets. We present a graphical user interface (GUI) application that automates the analysis of microscopy images to extract key microstructural metrics, including fiber orientation tensors, fiber orientation distribution, porosity and pore size distribution. The app integrates multiple image segmentation techniques including global and local thresholding, clustering, and region-based approaches, offering flexibility for different types of image qualities and features. Users can load microstructural images, select regions of interest and segmentation techniques tailored to their image dataset. It also addresses a critical challenge in fiber orientation analysis: the ambiguities caused by touching, overlapping, or partially cut fibers. It supports autorun examples for standardized workflows, enabling reproducible analysis and facilitating training and benchmarking. This tool significantly reduces manual intervention, enhances consistency, and accelerates data generation for structure–property modeling, process optimization, and digital materials research. The tool is intended for use by materials scientists, engineers, and researchers engaged in composite characterization, quality control, and machine learning-based microstructural studies.

Chawla, Komal [ORNL] (ORCID:0000000190327565)↗