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DOE OSTI2022

Observation of a Flat and Extended Surface State in a Topological Semimetal

A flat band structure in momentum space is considered key for the realization of novel phenomena. A topological flat band, also known as a drumhead state, is an ideal platform to drive new exotic topological quantum phases. Using angle-resolved photoemission spectroscopy experiments, we reveal the emergence of a highly localized surface state in a topological semimetal BaAl4 and provide its full energy and momentum space topology. We find that the observed surface state is localized in momentum, inside a square-shaped bulk Dirac nodal loop, and in energy, leading to a flat band and a peak in the density of state. These results imply this class of materials as an experimental realization of drumhead surface states and provide an important reference for future studies of the fundamental physics of correlated quantum effects in topological materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Beyond Mass and Multiscale Environments: What Shapes Low Surface Brightness Galaxies? Evidence from MaNGA

The origin of low surface brightness (LSB) galaxies remains a key open question in galaxy formation, reflecting the balance between internal mechanisms and environmental influence. Using MaNGA integral-field spectroscopy, we investigate whether LSB and high surface brightness (HSB) galaxies of comparable stellar mass (9 < logM * < 10) occupy distinct environments or differ primarily through internal evolution. Our late-type sample comprises 113 central and 29 satellite LSB galaxies, and 374 central and 142 satellite HSB galaxies. We characterize environments on scales from ∼100 kpc to 10 Mpc, analyzing radial profiles of stellar mass surface density (Σ * ), star formation activity, and gas-phase metallicity. Central LSB and HSB galaxies inhabit similarly low-density large-scale (>200 kpc) environments, but LSB galaxies are more isolated on small scales (∼100 kpc). Even after matching in stellar mass and environment, LSB galaxies show systematically lower Σ * , Σ SFR , and metallicities, often hosting diffuse, weakly star-forming bulges embedded in extended disks. These results indicate that LSB structure and star formation are not primarily governed by a large-scale environment or halo mass. While secondary halo properties such as spin, concentration, or gas accretion history are often invoked, their environmental dependence appears weak. Instead, LSB–HSB differences for centrals likely reflect divergent assembly or interaction histories and internal processes—such as angular momentum-driven disk evolution or inefficient gas conversion—largely decoupled from a large-scale environment. Nonetheless, the environment still influences the observed star formation and chemical differences between central and satellite LSB galaxies.

Shen, Mengting [Xiamen University (China); SDSS Co↗

DOE OSTI2021

Adjustable clamp systems and methods

In an example, an adjustable clamp system includes a base, a clamp assembly, and a first eccentric bushing. The base includes an anchor portion configured to couple the base to a support structure, a first clamp-support portion extending from the anchor portion, and a second clamp-support portion extending from the anchor portion. The clamp assembly includes a clamp defining a bore, a first flange extending from a first side of the clamp and coupled to the first clamp-support portion, and a second flange extending from a second side of the clamp and coupled to the second clamp-support portion. The first eccentric bushing couples the first flange to the first clamp-support portion. The first eccentric bushing is rotatable relative to the first flange to translate the clamp assembly in a first direction relative to the base and adjust a distance between the clamp and the anchor portion of the base.

Bailey, Michael Wallace↗

DOE OSTI2023

Multi-axis oscillating flight simulator

An apparatus for simulating an oscillating flight path is provided. The apparatus comprises a slide extending along a first axis; a support structure slidably coupled to the slide; and a table connected to the support structure. The support structure is operable to move along the slide. The table is coupled to the support structure and operable to rotate about a second axis orthogonal to the first axis. The table comprises a surface that is parallel to the second axis and that is operable to rotate about a third axis orthogonal to the second axis.

Dark, Philip Ryan↗

DOE OSTI2023

Adjustable clamp systems

Bailey, Michael Wallace↗

DOE OSTI2021

Structural organization of space polymers

Extraterrestrial polymers of glycine with iron have been characterized by mass spectrometry to have a core mass of 1494 Da with dominant rod-like variants at mass to charge ratios of 1567 and 1639 [McGeoch et al., “Meteoritic proteins with glycine, iron and lithium,” arXiv:2102.10700 (2021)]. Several principal macro-structural morphologies are observed in solvent extracts from a chondritic Vigarano class alteration type 3 meteoritic material. The first is an extended sheet of linked (three-legged) triskelia containing the 1494 Da core entity that encloses gas bubbles in the solvent. A second is of fiber-like crystals found here, via x-ray diffraction, to be multiple-walled nanotubes made from a square lattice of the 1494 Da polymer. A third is a dispersion of floating phantom-like short tubes of up to 100 μm length with characteristic angled bends that suggest the influence of a specific underlying protein structure. Here, it is proposed that the angled tubes are the observable result of a space-filling superpolymerization of 1638 Da polymer subunits guided by the tetragonal symmetry of linking silicon bonds. Distorted hexagonal sheets are linked by perpendicular subunits in a three-dimensional hexagonal diamond structure to fill the largest possible volume. This extended very low-density structure is conjectured to have dominated in a process of chemical selection because it captured a maximum amount of molecular raw material in the ultra-low density of molecular clouds or of the proto-solar nebula. This could have led ultimately to the accretion of the earliest planetary bodies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Surface structure of mass-selected niobium oxide nanoclusters on Au(111)

The structures formed by the deposition of mass-selected niobium oxide clusters, Nb 3 O y ( y = 5, 6, 7), onto Au(111) were studied by scanning tunneling microscopy. The as-deposited Nb 3 O 7 clusters assemble into large dendritic structures that grow on the terraces as well as extend from the top and bottom of step edges. The Nb 3 O 6 cluster also forms dendritic assemblies but they are generally much smaller in size. The assemblies are composed of smaller discrete structures (<1 nm) which are likely to be single clusters. Furthermore, the dendritic assemblies for both the Nb 3 O 7 and Nb 3 O 6 clusters have fractal dimensions of about 1.7 which is very close to that expected for simple diffusion limited aggregation. Annealing the Nb 3 O 7,6 /Au(111) surfaces up to 550 K results in changes in assembly sizes and increases in heights, while heating to 700 results in the disruption of the assemblies into smaller structures. By contrast, the as-deposited Nb 3 O 5 /Au(111) surface at RT exhibits compact cluster structures which become 3D nanoparticles when annealed above 550 K. Differences in the observed surface structures and thermal stability are attributed to differences in metal-oxygen stoichiometry which can influence cluster binding energies, mobility and inter-cluster interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Insights into cosmological structure formation with machine learning.

Our modern understanding of cosmological structure formation posits that small matter density fluctuations present in the early Universe, as traced by the cosmic microwave background, grow via gravitational instability to form extended haloes of dark matter. A theoretical understanding of the structure, evolution and formation of dark matter haloes is an essential step towards unravelling the intricate connection between halo and galaxy formation, needed to test our cosmological model against data from upcoming galaxy surveys. Physical understanding of the process of dark matter halo formation is made difficult by the highly non-linear nature of the haloes' evolution. I describe a new approach to gain physical insight into cosmological structure formation based on machine learning. This approach combines the ability of machine learning algorithms to learn non-linear relationships, with techniques that enable us to physically interpret the learnt mapping. I describe applicatio ns of th e method, with the aim of investigating which aspects of the early universe density field impact the later formation of dark matter haloes. First I present a case where the process of halo formation is turned into a binary classification problem; the algorithm predicts whether or not dark matter `particles' in the initial conditions of a simulation will collapse into haloes of a given mass range. Second, I present its generalization to regression, where the algorithm infers the final mass of the halo to which each particle will later belong. I show that the initial tidal shear does not play a significant role compared to the initial density field in establishing final halo masses. Finally, I demonstrate that extending the framework to deep learning algorithms such as convolutional neural networks allows us to explore connections between the early universe and late time haloes beyond those studied by existing analytic approximations of halo collapse.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Dynamic Copper Site Redispersion through Atom Trapping in Zeolite Defects

Single-site copper-based catalysts have shown remarkable activity and selectivity for a variety of reactions. However, deactivation by sintering in high-temperature reducing environments remains a challenge and often limits their use due to irreversible structural changes to the catalyst. Here, we report zeolite-based copper catalysts in which copper oxide agglomerates formed after reaction can be repeatedly redispersed back to single sites using an oxidative treatment in air at 550 °C. Under different environments, single-site copper in Cu–Zn–Y/deAlBeta undergoes dynamic changes in structure and oxidation state that can be tuned to promote the formation of key active sites while minimizing deactivation through Cu sintering. For example, single-site Cu 2+ reduces to Cu 1+ after catalyst pretreatment (270 °C, 101 kPa H 2 ) and further to Cu0 nanoparticles under reaction conditions (270–350 °C, 7 kPa EtOH, 94 kPa H 2 ) or accelerated aging (400–450 °C, 101 kPa H 2 ). After regeneration at 550 °C in air, agglomerated CuO was dispersed back to single sites in the presence and absence of Zn and Y, which was verified by imaging, in situ spectroscopy, and catalytic rate measurements. Ab initio molecular dynamics simulations show that solvation of CuO monomers by water facilitates their transport through the zeolite pore, and condensation of the CuO monomer with a fully protonated silanol nest entraps copper and reforms the single-site structure. Importantly, the capability of silanol nests to trap and stabilize copper single sites under oxidizing conditions could extend the use of single-site copper catalysts to a wider variety of reactions and allows for a simple regeneration strategy for copper single-site catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

FAIR Data Meets FAIR Software

Modern scientific research is increasingly defined by the interplay between data, software, and the workflows that connect them. Yet while the FAIR (Findable, Accessible, Interoperable, Reusable) principles have become foundational for scientific data stewardship, the same level of structure and expectation has only recently begun to extend to research software. This talk covers why and how FAIR principles are being applied to data and software to support data reuse. It outlines the gaps in current sharing norms, the growing federal emphasis on persistent identifiers and public access, and the opportunities created when datasets, computational workflows, code, and models are linked through rich, standardized metadata. Practical implementation pathways for the EIC and JLab communities are described, including datacards for structured dataset documentation and provenance-aware workflows. By aligning data lifecycle management with FAIR-aligned software practices, the scientific community can advance toward autonomous knowledge graphs, generative workflows, and high-quality, AI-ready scientific datasets.

McSpadden, Diana [Thomas Jefferson National Accele↗

DOE OSTI2024

Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)

This work is devoted to the investigation of dielectric permittivity which is influenced by electronic, ionic, and dipolar polarization mechanisms, contributing to the material’s capacity to store electrical energy. In this study, an extended dataset of 86 polymers was analyzed, and two quantitative structure–property relationship (QSPR) models were developed to predict dielectric permittivity. From an initial set of 1273 descriptors, the most relevant ones were selected using a genetic algorithm, and machine learning models were built using the Gradient Boosting Regressor (GBR). In contrast to Multiple Linear Regression (MLR)- and Partial Least Squares (PLS)-based models, the gradient boosting models excel in handling nonlinear relationships and multicollinearity, iteratively optimizing decision trees to improve accuracy without overfitting. The developed GBR models showed high R2 coefficients of 0.938 and 0.822, for the training and test sets, respectively. An Accumulated Local Effect (ALE) technique was applied to assess the relationship between the selected descriptors—eight for the GB_A model and six for the GB_B model, and their impact on target property. ALE analysis revealed that descriptors such as TDB09m had a strong positive effect on permittivity, while MLOGP2 showed a negative effect. These results highlight the effectiveness of the GBR approach in predicting the dielectric properties of polymers, offering improved accuracy and interpretability.

Ascencio-Medina, Estefania↗

DOE OSTI2021

Simulation of enhanced light extraction from periodic, disordered, and quasi-periodic OLED structures

Here we have developed a rigorous scattering matrix theory of light emission from periodically structured media using a Green’s function approach. We computationally simulate the spectral power inside the structure, incorporating Purcell factor enhancements, and find internal waveguiding modes and plasmonic losses. We simulate the light-outcoupling factor η out and describe how corrugations and structured media can enhance η out . We have extended our framework to describe non-periodic disordered arrays as well as aperiodic quasi-crystalline arrays. Flat organic light-emitting diodes (OLEDs) have low outcoupling with η out ~20% since most of the light is trapped in waveguided modes in higher index layers or lost to plasmonic excitations at the metal cathode. Periodically corrugated OLEDs can achieve highly enhanced η out ~65%-70% for pitch values between 1000 and 2000 nm, representing an enhancement factor >3 over planar structures. Periodic corrugations strongly diffract trapped waveguided and plasmonic modes to the emissive air cone. Disordered templates also can cause significant enhanced outcoupling with η out ~50%-55% for smaller nearest-neighbor separations of 300–400 nm. Quasi-crystalline tilings can also lead to enhancements of η out ~50%-55%. This framework can be utilized to design novel structured media that can generate high light extraction.

42 ENGINEERING↗

DOE OSTI2025

An evolutionarily conserved tryptophan cage promotes folding of the extended RNA recognition motif in the hnRNPR ‐like protein family

Abstract The heterogeneous nuclear ribonucleoprotein (hnRNP) R‐like family is a class of RNA binding proteins in the hnRNP superfamily with diverse functions in RNA processing. Here, we present the 1.90 Å X‐ray crystal structure and solution NMR studies of the first RNA recognition motif (RRM) of human hnRNPR. We find that this domain adopts an extended RRM (eRRM1) featuring a canonical RRM with a structured N‐terminal extension (N ext ) motif that docks against the RRM and extends the β‐sheet surface. The adjoining loop is structured and forms a tryptophan cage motif to position the N ext motif for docking to the RRM. Combining mutagenesis, solution NMR spectroscopy, and thermal denaturation studies, we evaluate the importance of residues in the N ext –RRM interface and adjoining loop on eRRM folding and conformational dynamics. We find that these sites are essential for protein solubility, conformational ordering, and thermal stability. Consistent with their importance, mutations in the N ext –RRM interface and loop are associated with several cancers in a survey of somatic mutations in cancer studies. Sequence and structure comparison of the human hnRNPR eRRM1 to experimentally verified and predicted hnRNPR‐like proteins reveals conserved features in the eRRM.

Biochemistry & Molecular Biology↗

DOE OSTI2023

Monomeric crystal structure of the vaccine carrier protein CRM 197 and implications for vaccine development

CRM 197 is a genetically detoxified mutant of diphtheria toxin (DT) that is widely used as a carrier protein in conjugate vaccines. Protective immune responses to several bacterial diseases are obtained by coupling CRM 197 to glycans from these pathogens. Wild-type DT has been described in two oligomeric forms: a monomer and a domain-swapped dimer. Their proportions depend on the chemical conditions and especially the pH, with a large kinetic barrier to interconversion. A similar situation occurs in CRM 197 , where the monomer is preferred for vaccine synthesis. Despite 30 years of research and the increasing application of CRM 197 in conjugate vaccines, until now all of its available crystal structures have been dimeric. Here, CRM 197 was expressed as a soluble, intracellular protein in an Escherichia coli strain engineered to have an oxidative cytoplasm. The purified product, called EcoCRM, remained monomeric throughout crystallization. The structure of monomeric EcoCRM is reported at 2.0 Å resolution with the domain-swapping hinge loop (residues 379–387) in an extended, exposed conformation, similar to monomeric wild-type DT. The structure enables comparisons across expression systems and across oligomeric states, with implications for monomer–dimer interconversion and for the optimization of conjugation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Rapid and efficient ambient temperature X-ray crystal structure determination at Turkish Light Source

High-resolution biomacromolecular structure determination is essential to better understand protein function and dynamics. Serial crystallography is an emerging structural biology technique which has fundamental limitations due to either sample volume requirements or immediate access to the competitive X-ray beamtime. Obtaining a high volume of well-diffracting, sufficient-size crystals while mitigating radiation damage remains a critical bottleneck of serial crystallography. As an alternative, we introduce the plate-reader module adapted for using a 72-well Terasaki plate for biomacromolecule structure determination at a convenience of a home X-ray source. We also present the first ambient temperature lysozyme structure determined at the Turkish light source (Turkish DeLight). The complete dataset was collected in 18.5 min with resolution extending to 2.39 Å and 100% completeness. Combined with our previous cryogenic structure (PDB ID: 7Y6A), the ambient temperature structure provides invaluable information about the structural dynamics of the lysozyme. Turkish DeLight provides robust and rapid ambient temperature biomacromolecular structure determination with limited radiation damage.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Anisotropic Motions of Fibrils Dictated by Their Orientations in the Lamella: A Coarse-Grained Model of a Plant Cell Wall

Plant cell walls are complex systems that exhibit the characteristics of both rigid and soft material depending on their external perturbations. The three main polymeric components in a plant primary cell wall are cellulose fibrils, hemicellulose, and pectins. These components interact in a hierarchical fashion giving rise to mesoscale structural features such as cellulose bundles, lamella stacking, and so on. Although several studies have focused on understanding these unique structural features, a clear picture linking them to cell wall mechanics is still lacking. As a first step toward this goal, a phenomenological model of plant cell wall has been developed in this work by using available experimental data to investigate the underlying connections between mesoscale structural features and the motions of fibrils during deformation. In this model cellulose fibrils exhibit motions such as angular reorientations and kinking upon forced stretching. Furthermore, these motions are dependent on the orientation of fibrils with respect to the stretch direction, i.e., fibrils that are at an angle to the stretch direction exhibit predominant angular reorientations, while fibrils transverse to the stretch direction undergo kinking as a result of transverse compression. Varying the chain length of pectin had negligible effects on these motions. One of the main contributions from this work is the development of a simple model that can be easily fine-tuned to test other hypotheses and extended to include additional experimental knowledge about the structural aspects of cell walls in the future.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Liquid-like spin dynamics in a hybrid Heisenberg-Ising antiferromagnet

Two-dimensional (2D) materials and their heterostructures enable unconventional electronic properties and functionalities not accessible in their bulk counterparts. This approach is now being extended to magnetic materials to engineer their spin structures and magnetic fields produced by them. However, spin dynamics of 2D magnetic heterostructures remain largely unexplored. Here, we demonstrate that heterointerfacing Heisenberg square-lattice antiferromagnet (AF) Sr 2 IrO 4 with its bilayer variant Ising AF Sr 3 Ir 2 O 7 in a superlattice leads to liquid-like spin dynamics in the former, characterized by slow recovery of the AF order after its transient suppression by an optical pump, and complete absence of spin waves except in an immediate vicinity of the ordering wavevector. Instead, the spin excitation spectra are dominated by isotropic continua, which in previous works have been interpreted as fractional spin excitations, or spinons, that extends to unprecedentedly low energies. Thus, our results provide a pathway to frustrated magnetism in square lattices by heterointerfacing two distinct types of AFs.

RIXS↗

DOE OSTI2021

Computing water flow through complex landscapes – Part 3: Fill–Spill–Merge: flow routing in depression hierarchies

Abstract. Depressions – inwardly draining regions – are common to many landscapes. When there is sufficient moisture, depressions take the form of lakes and wetlands; otherwise, they may be dry. Hydrological flow models used in geomorphology, hydrology, planetary science, soil and water conservation, and other fields often eliminate depressions through filling or breaching; however, this can produce unrealistic results. Models that retain depressions, on the other hand, are often undesirably expensive to run. In previous work we began to address this by developing a depression hierarchy data structure to capture the full topographic complexity of depressions in a region. Here, we extend this work by presenting the Fill–Spill–Merge algorithm that utilizes our depression hierarchy data structure to rapidly process and distribute runoff. Runoff fills depressions, which then overflow and spill into their neighbors. If both a depression and its neighbor fill, they merge. We provide a detailed explanation of the algorithm and results from two sample study areas. In these case studies, the algorithm runs 90–2600 times faster (with a reduction in compute time of 2000–63 000 times) than the commonly used Jacobi iteration and produces a more accurate output. Complete, well-commented, open-source code with 97 % test coverage is available on GitHub and Zenodo.

58 GEOSCIENCES↗