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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quasi-Two-Dimensional Heterostructures (K M 1 – x Te)(LaTe 3 ) ( M = Mn and Zn) with Charge Density Waves

Layered heterostructure materials with two different functional building blocks can teach us about emergent physical properties and phenomena arising from interactions between the layers. Here, we report intergrowth compounds KLaM 1 - x Te 4 (M = Mn and Zn; $x \approx$ 0.35) featuring two chemically distinct alternating layers [LaTe 3 ] and [KM 1 - x Te]. Their crystal structures are incommensurate, determined by single X-ray diffraction for the Mn compound and a transmission electron microscope study for the Zn compound. KLaMn 1 – x Te 4 crystallizes in the orthorhombic superspace group Pmnm(01/2 gamma)s00 with lattice parameters a = 4.4815(3) Å, b = 21.6649(16) Å, and c = 4.5220(3) Å. It exhibits charge density wave order at room temperature with a modulation wave vector q = 1/2b* + 0.3478c* originating from electronic instability of Te-square nets in [LaTe 3 ] layers. The Mn analog exhibits a cluster spin glass behavior with spin freezing temperature $T_f \approx$ 5 K attributed to disordered Mn vacancies and competing magnetic interactions in the [Mn 1 - x Te] layers. The Zn analog also has charge density wave order at room temperature with a similar q-vector having the c* component similar to 0.346 confirmed by selected-area electron diffraction. Electron transfer from [KM 1 - x Te] to [LaTe 3 ] layers exists in KLaM 1 – x Te 4 , leading to an enhanced electronic specific heat coefficient. The resistivities of KLaM 1 - x Te 4 (M = Mn and Zn) exhibit metallic behavior at high temperatures and an upturn at low temperatures, suggesting partial localization of carriers in the [LaTe 3 ] layers with some degree of disorder associated with the M atom vacancies in the [M 1 - x Te] layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cryo-electron Microscopy of Adeno-associated Virus

Adeno-associated virus (AAV) has a single-stranded DNA genome encapsidated in a small icosahedrally symmetric protein shell with 60 subunits. AAV is the leading delivery vector in emerging gene therapy treatments for inherited disorders, so its structure and molecular interactions with human hosts are of intense interest. A wide array of electron microscopic approaches have been used to visualize the virus and its complexes, depending on the scientific question, technology available, and amenability of the sample. Approaches range from subvolume tomographic analyses of complexes with large and flexible host proteins to detailed analysis of atomic interactions within the virus and with small ligands at resolutions as high as 1.6 Å. Analyses have led to the reclassification of glycan receptors as attachment factors, to structures with a new-found receptor protein, to identification of the epitopes of antibodies, and a new understanding of possible neutralization mechanisms. AAV is now well-enough characterized that it has also become a model system for EM methods development. Heralding a new era, cryo-EM is now also being deployed as an analytic tool in the process development and production quality control of high value pharmaceutical biologics, namely AAV vectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multiple Sources of Riparian Wetland Suspended Solids during Episodic Rain Events: Influence on Uranium Transport

Suspended solids can be the primary vector for transporting contaminants in streams. The objective of this study was to determine whether changes in the properties of suspended solids during rain events impacted contaminant transport. Stream water was collected during five episodic events downstream from a U-contaminated wetland located in South Carolina, USA. The suspended particles were initially composed of Fe-flocs (particles formed in situ prior to the rain event) that had significantly greater Fe, Mn, organic-C, and U content than particles collected later during a sampling rain event. XANES and EXAFS revealed that U in the Fe-flocs was U(VI) and that it was not incorporated in a mineral structure but existed as inner- or outer-sphere adsorbed uranyl species associated with organic matter and Fe-oxides. The uranyl had an extraordinarily high affinity for the suspended solids, with solid to liquid U ratios of >72,000 (μg/kg)/(μg/L). After the initial flush of Fe-flocs, a greater fraction of the suspended solids had lower organic-C, Fe, Mn, and amorphous phases and were composed of more quartz, kaolinite, and gibbsite, resulting in lower U concentrations than those in the solids collected earlier in the rain event. This study highlights the importance of understanding suspended solids as transport vectors and their potential dynamic nature during rain events.

computer simulations↗
DOE OSTI2021

Crystal and Magnetic Structures of the Ternary Ho 2 Ni 0.8 Si 1.2 and Ho 2 Ni 0.8 Ge 1.2 Compounds: An Example of Intermetallics Crystallizing with the Zr 2 Ni 1–x P Prototype

We report two new rare-earth (R) ternary intermetallic compounds—Ho 2 Ni 0.8 T 1.2 with T = Si and Ge—that correspond to the R 5 Ni 2 T 3 phase earlier reported to form in Dy–Ni–T and Ho–Ni–T ternary systems. The compounds crystallize in a filled version of the orthorhombic Zr 2 Ni 1–x P-type structure with x = 0.52; their stoichiometry, determined from both single-crystal and powder X-ray diffraction data, is centered on Ho 2 Ni 0.8 T 1.2 with a narrow solid solubility range for the silicide, while the germanide appears to be a line phase. In addition to R = Dy and Ho, R 2 Ni 0.8 T 1.2 compounds also form for R = Y and Tb, representing the first examples of rare-earth-based compounds adopting the Zr 2 Ni 1–x P structural prototype. Bulk magnetization data reveal the main transitions of the ferrimagnetic or ferromagnetic type at TC = 38 K for Ho 2 Ni 0.8 Si 1.2 and TC = 37 K for Ho 2 Ni 0.8 Ge 1.2 , which are followed by subsequent magnetic reordering at lower temperatures. Neutron diffraction shows complex magnetic structures below T C with both ferromagnetic and antiferromagnetic components and magnetic propagation vector κ 1 = [0, 0, 0]. Below T N ≅ 24 K (22 K) for the silicide (germanide), an additional antiferromagnetic coupling following an incommensurate magnetic propagation vector κ 2 = [κ x , 0, 0] appears to coexist with the first magnetic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Low-Lying Excited States of Linear All- Trans Polyenes: Insights from Analytic Gradient and Nonadiabatic Coupling Calculations Based on Multireference Configuration Interaction

Polyenes serve as a rigorous test for theoretical models and electronic structure methods, playing a key role in advancing computational and theoretical chemistry. Here, we present a high-level theoretical investigation of linear, all-trans polyenes using energy gradients and nonadiabatic coupling vectors based on an MR-CISD wave function to describe electronic transitions involving the ground state (1 1 A g – ) and three low-lying excited states (2 1 A g – , 1 1 B u + , and 2 1 B u – ) of hexatriene, octatetraene, and decapentaene. This approach enables accurate evaluation of both adiabatic and vertical excitation and emission energies, yielding results in excellent agreement with experiment, as well as locating minima on the crossing seam between adiabatic states. Our results show that vertical excitation energies to the 1 1 B u + state are blue-shifted by 0.2–0.3 eV relative to the experimental absorption maximum, whereas the vertical emission energy from the 2 1 A g – state is red-shifted by ∼0.2 eV relative to the experimental emission maximum. Upon relaxation from the Franck–Condon geometry, the 2 1 A g – state stabilizes by around 1 eV, compared to 0.2–0.3 eV for the 1 1 B u + state. An analysis of the S 1 /S 0 crossing seam in hexatriene shows that its minimum involves asymmetric backbone deformations and provides an efficient channel for ultrafast internal conversion to the ground state, consistent with the absence of detectable fluorescence in this molecule. These results demonstrate the power of analytic gradients and nonadiabatic coupling vectors based on an MR-CISD wave function for accurately characterizing the electronic structure and photophysics of polyenes.

Excited states↗
DOE OSTI2020

Revealing the Formation Energy–Exfoliation Energy–Structure Correlation of MAB Phases Using Machine Learning and DFT

MAB phases are popular as high-temperature materials with high damage tolerance and excellent electrical conductivity that are used to exfoliate two-dimensional (2D) transition metal borides (MBenes); a promising material for developing next- generation nanodevices. In this report, we explore the correlation between the formation energy, exfoliation energy and structural factors of MAB phases using DFT and machine learning. In order to do so, we developed three different machine learning models based on the support vector machine, deep neural network, and random forest regressor to study the stability of the MAB phases by calculating their formation energies. Furthermore, our support vector machine and deep neural network models are capable of predicting the formation energies with mean absolute errors less than 0.1 eV/atom. We demonstrated that the stability of a MAB phase for a given transition metal decreases when the A element changes from Al to Tl. The density functional theory (DFT) re- vealed that M-A and M-B bond strength strongly correlates with the stability of MAB phases. In addition, the exfoliation possibility of 2D MBenes becomes higher when the A element changes from Al to Tl due to weakening of M-A and M-B bonds.

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

Shear-Induced Conformations of Salt-Free Polyelectrolytes in Semidilute Solutions

Here, we present coarse-grained molecular dynamics simulations of salt-free polyelectrolyte chains in semidilute solutions under simple shear flow, with full hydrodynamic interactions and explicit dipolar solvent. At equilibrium, chain orientation statistics follow a pseudo-Voigt distribution, and the structural correlation length and chain end-to-end vector autocorrelation function exhibit scaling behavior consistent with theoretical predictions for polyelectrolytes. Under shear, chains transition from coiled to stretched states and the end-to-end vector autocorrelation function reveals oscillatory dynamics at high Weissenberg numbers. Analysis of the gyration tensor and shear strain distributions identified three distinct chain populations with directional alignment along and against the shear gradient. Compared with their neutral polymer counterparts, polyelectrolytes exhibit stronger shear thinning and enhanced chain alignment under the same Weissenberg number, which is attributed to electrostatic interactions and shear-induced counterion release. These findings provide molecular insight into the distinct flow response of charged polymers and have implications for tailoring the rheological properties of polyelectrolyte-based materials.

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

RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ (R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. Furthermore, this result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides, providing a streamlined method for addressing genetic engineering challenges in the yeast.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Lower‐Hybrid Wave Structures and Interactions With Electrons Observed in Magnetotail Reconnection Diffusion Regions

Abstract We investigate waves close to the lower‐hybrid frequency in 12 magnetotail reconnection electron diffusion region (EDR) events with guide field levels of near‐zero to 30%. In about half of the events, the wave vector has a small component along the current sheet normal, consistent with known lower‐hybrid drift wave properties, but the perpendicular magnetic field fluctuations can be comparable or greater than the parallel component, a feature unique to the waves inside and adjacent to EDRs. Another new wave property is that the wave vector has a significant component along the current sheet normal in some events and completely along the normal for one event. In 1/4 of the events, the term has a significant contribution to the wave electric field, possibly a feature of lower‐hybrid waves more likely to exist in the diffusion region than further away from the X‐line. Electron temperature variations are correlated with the wave potential, due to wave electric field acceleration and crossings at the corrugated separatrix region with different amounts of mixing between reconnection inflowing and outflowing populations. The latter also leads to the anti‐correlation between parallel and perpendicular temperature components. Using four‐spacecraft measurements, the magnetic field line twisting is demonstrated by the correlated fluctuations in and . The lower‐hybrid wave in the EDR of weak guide field reconnection may be generated near separatrices and penetrate to the mid‐plane or locally generated, and the latter possibility is beyond the prediction of previous reconnection simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Topological Relationship–Based Flow Direction Modeling: Mesh–Independent River Networks Representation

River networks are important features in surface hydrology. However, accurately representing river networks in spatially distributed hydrologic and Earth system models is often sensitive to the model's spatial resolution. Specifically, river networks are often misrepresented because of the mismatch between the model's spatial resolution and river network details, resulting in significant uncertainty in the projected flow direction. In this study, we developed a topological relationship-based river network representation method for spatially distributed hydrologic models. This novel method uses (a) graph theory algorithms to simplify real-world vector-based river networks and assist in mesh generation; and (b) a topological relationship-based method to reconstruct conceptual river networks. The main advantages of our method are that (a) it combines the strengths of vector-based and DEM raster-based river network extraction methods; and (b) it is mesh-independent and can be applied to both structured and unstructured meshes. This method paves a path for advanced terrain analysis and hydrologic modeling across different scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Global River Topology (GRIT): A Bifurcating River Hydrography

Existing global river networks underpin a wide range of hydrological applications but do not represent channels with divergent river flows (bifurcations, multi‐threaded channels, canals), as these features defy the convergent flow assumption that elevation‐derived networks (e.g., HydroSHEDS, MERIT Hydro) are based on. Yet, bifurcations are important features of the global river drainage system, especially on large floodplains and river deltas, and are also often found in densely populated regions. Here we developed the first raster and vector‐based Global RIver Topology that not only represents the tributaries of the global drainage network but also the distributaries, including multi‐threaded rivers, canals and deltas. We achieve this by merging a 30 m Landsat‐based river mask with elevation‐generated streams to ensure a homogeneous drainage density outside of the river mask for rivers narrower than approximately 30 m. Crucially, we employ the new 30 m digital terrain model, FABDEM, based on TanDEM‐X, which shows greater accuracy over the traditionally used SRTM derivatives. After vectorization and pruning, directionality is assigned by a series of elevation, flow angle and continuity approaches. The new global network and its attributes are validated using gauging stations, comparison with existing networks, and randomized manual checks. The new network represents 19.6 million km of streams and rivers with drainage areas greater than 50 km 2 and includes 67,495 bifurcations. With the advent of hyper‐resolution modeling and artificial intelligence, GRIT is expected to greatly improve the accuracy of many river‐based applications such as flood forecasting, water availability and quality simulations, or riverine habitat mapping.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Signature of spin-phonon coupling driven charge density wave in a kagome magnet

Abstract The intertwining between spin, charge, and lattice degrees of freedom can give rise to unusual macroscopic quantum states, including high-temperature superconductivity and quantum anomalous Hall effects. Recently, a charge density wave (CDW) has been observed in the kagome antiferromagnet FeGe, indicative of possible intertwining physics. An outstanding question is that whether magnetic correlation is fundamental for the spontaneous spatial symmetry breaking orders. Here, utilizing elastic and high-resolution inelastic x-ray scattering, we observe a c-axis superlattice vector that coexists with the 2 $$\times$$ × 2 $$\times$$ × 1 CDW vectors in the kagome plane. Most interestingly, between the magnetic and CDW transition temperatures, the phonon dynamical structure factor shows a giant phonon-energy hardening and a substantial phonon linewidth broadening near the c-axis wavevectors, both signaling the spin-phonon coupling. By first principles and model calculations, we show that both the static spin polarization and dynamic spin excitations intertwine with the phonon to drive the spatial symmetry breaking in FeGe.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A broken translational symmetry state in an infinite-layer nickelate

A defining signature of strongly correlated electronic systems is a rich phase diagram, which consists of multiple broken symmetries, such as magnetism, superconductivity, and charge order. In the recently discovered nickelate superconductors a large antiferromagnetic exchange energy has been reported, which implies the existence of strong electronic correlations. However, signatures of a broken-symmetry state other than superconductivity have not yet been observed. Here, we observe charge ordering in infinite-layer nickelates La 1-x Sr x NiO 2 using resonant x-ray scattering. The parent compound orders along the Ni-O bond direction with an incommensurate wave vector, distinct from the stripe order observed in other nickelates that propagates along a direction 45º to the Ni-O bond. The resonance profile we measure indicates that ordering originates from the nickelate layers and induces a parasitic charge modulation of lanthanum electrons. After doping, the charge order diminishes and its wave vector shifts toward commensurate, indicating that strong electronic correlations are likely to be responsible for the ordered state. Our results suggest that the existence of charge order and its potential interplay with antiferromagnetic fluctuations and superconductivity are important themes in nickel-based superconductors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Observation of electroweak production of two jets and a $Z$-boson pair

Electroweak symmetry breaking explains the origin of the masses of elementary particles through their interactions with the Higgs field. Besides the measurements of the Higgs boson properties, the study of the scattering of massive vector bosons with spin 1 allows the nature of electroweak symmetry breaking to be probed. Among all processes related to vector-boson scattering, the electroweak production of two jets and a $Z$-boson pair is a rare and important one. Here we report the observation of this process from proton–proton collision data corresponding to an integrated luminosity of 139 fb -1 recorded at a centre-of-mass energy of 13 TeV with the ATLAS detector at the Large Hadron Collider. We consider two different final states originating from the decays of the $Z$-boson pair: one containing four charged leptons and another containing two charged leptons and two neutrinos. The hypothesis of no electroweak production is rejected with a statistical significance of 5.7$σ$, and the measured cross-section for electroweak production is consistent with the Standard Model prediction. In addition, we report cross-sections for inclusive production of a $Z$-boson pair and two jets for the two final states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Pattern of global spin alignment of ϕ and K*0 mesons in heavy-ion collisions

The strong force, as one of the four fundamental forces at work in the universe, governs interactions of quarks and gluons, and binds together the atomic nucleus. Notwithstanding decades of progress since Yukawa first developed a description of the force between nucleons in terms of meson exchange 1 , a full understanding of the strong interaction remains a major challenge in modern science. One remaining difficulty arises from the non-perturbative nature of the strong force, which leads to the phenomenon of quark confinement at distance scales on the order of the size of the proton. Here we show that in relativistic heavy-ion collisions, where quarks and gluons are set free over an extended volume, two species of produced vector (spin-1) mesons, namely φ and K∗0 , emerge with a surprising pattern of global spin alignment. In particular, the global spin alignment for φ is unexpectedly large, while that for K∗0 is consistent with zero. The observed spin-alignment pattern and magnitude for the φ cannot be explained by conventional mechanisms, while a model with strong force fields2, 3 accommodates the current data. This is the first time that the strong force field is experimentally supported as a key mechanism that leads to global spin alignment. We extract a quantity proportional to the intensity of the field of the strong force. Within the framework of the Standard Model, where the strong force is typically described in the quark and gluon language of Quantum Chromodynamics, the field being considered here is an effective proxy description. This is a qualitatively new class of measurement, which opens a new avenue for studying the behaviour of strong force fields via their imprint on spin alignment.

Abdallah, M. S.↗
DOE OSTI2020

A regression algorithm for accelerated lattice QCD that exploits sparse inference on the D-Wave quantum annealer

We propose a regression algorithm that utilizes a learned dictionary optimized for sparse inference on a D-Wave quantum annealer. In this regression algorithm, we concatenate the independent and dependent variables as a combined vector, and encode the high-order correlations between them into a dictionary optimized for sparse reconstruction. On a test dataset, the dependent variable is initialized to its average value and then a sparse reconstruction of the combined vector is obtained in which the dependent variable is typically shifted closer to its true value, as in a standard inpainting or denoising task. Here, a quantum annealer, which can presumably exploit a fully entangled initial state to better explore the complex energy landscape, is used to solve the highly non-convex sparse coding optimization problem. The regression algorithm is demonstrated for a lattice quantum chromodynamics simulation data using a D-Wave 2000Q quantum annealer and good prediction performance is achieved. The regression test is performed using six different values for the number of fully connected logical qubits, between 20 and 64. The scaling results indicate that a larger number of qubits gives better prediction accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Lossy compression of statistical data using quantum annealer

Abstract We present a new lossy compression algorithm for statistical floating-point data through a representation learning with binary variables. The algorithm finds a set of basis vectors and their binary coefficients that precisely reconstruct the original data. The optimization for the basis vectors is performed classically, while binary coefficients are retrieved through both simulated and quantum annealing for comparison. A bias correction procedure is also presented to estimate and eliminate the error and bias introduced from the inexact reconstruction of the lossy compression for statistical data analyses. The compression algorithm is demonstrated on two different datasets of lattice quantum chromodynamics simulations. The results obtained using simulated annealing show 3–3.5 times better compression performance than the algorithm based on neural-network autoencoder. Calculations using quantum annealing also show promising results, but performance is limited by the integrated control error of the quantum processing unit, which yields large uncertainties in the biases and coupling parameters. Hardware comparison is further studied between the previous generation D-Wave 2000Q and the current D-Wave Advantage system. Our study shows that the Advantage system is more likely to obtain low-energy solutions for the problems than the 2000Q.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Improving deep learning model performance under parametric constraints for materials informatics applications

Abstract Modern machine learning (ML) and deep learning (DL) techniques using high-dimensional data representations have helped accelerate the materials discovery process by efficiently detecting hidden patterns in existing datasets and linking input representations to output properties for a better understanding of the scientific phenomenon. While a deep neural network comprised of fully connected layers has been widely used for materials property prediction, simply creating a deeper model with a large number of layers often faces with vanishing gradient problem, causing a degradation in the performance, thereby limiting usage. In this paper, we study and propose architectural principles to address the question of improving the performance of model training and inference under fixed parametric constraints. Here, we present a general deep-learning framework based on branched residual learning (BRNet) with fully connected layers that can work with any numerical vector-based representation as input to build accurate models to predict materials properties. We perform model training for materials properties using numerical vectors representing different composition-based attributes of the respective materials and compare the performance of the proposed models against traditional ML and existing DL architectures. We find that the proposed models are significantly more accurate than the ML/DL models for all data sizes by using different composition-based attributes as input. Further, branched learning requires fewer parameters and results in faster model training due to better convergence during the training phase than existing neural networks, thereby efficiently building accurate models for predicting materials properties.

36 MATERIALS SCIENCE↗