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DOE OSTI2025

Decoding substrate specificity determining factors in glycosyltransferase-B enzymes – insights from machine learning models

Substrate specificity is an essential characteristic of any enzyme's function and an understanding of the factors that determine this specificity is crucial for enzyme engineering. Unlike the structure of an enzyme which is directly impacted by its sequence, substrate specificity as an enzyme attribute involves a rather indirect relationship with sequence as it also depends on structural aspects that dictate substrate accessibility and active site dynamics. In this study, we explore the performance of classifier-based machine learning models trained on curated sequence and structural data for a class of glycosyltransferases (GTs), namely GT-Bs, to understand their substrate specificity determining factors. GTs enable the transfer of sugar moieties to other biomolecules such as oligosaccharides or proteins and are found in all kingdoms of life. In plants, GTs participate in the biosynthesis of plant cell wall biopolymers (e.g.: hemicelluloses and pectins) and are an integral part of the enzymatic machinery that enables the storage of carbon and energy as plant biomass. To elucidate the substrate specificity of uncharacterized GT-Bs, we constructed multi-label machine learning models (Support Vector Classifier, K-Nearest Neighbors, Gaussian Naïve-Bayes, Random Forest) that incorporate both sequence and structural features. These models achieve good predictive accuracies on test datasets. However, despite our use of structural information, we highlight that there is further scope for improvement in training these models to draw interpretable relationships between sequence, structure and substrate specificity determining motifs in GT-Bs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Precise determination of the deuteron spin structure at low to moderate Q 2 with CLAS and extraction of the neutron contribution

In this study, we present the final results for the deuteron spin structure functions obtained from the full data set collected with Jefferson Lab's CLAS in 2000-2001. Polarized electrons with energies of 1.6, 2.5, 4.2 and 5.8 GeV were scattered from deuteron ( 15 ND 3 ) targets, dynamically polarized along the beam direction, and detected with CLAS. From the measured double spin asymmetry, the virtual photon absorption asymmetry A d 1 and the polarized structure function g d 1 were extracted over a wide kinematic range (0.05 GeV2 < Q2 < 5 GeV2 and 0.9 GeV < W < 3 GeV). We use an unfolding procedure and a parametrization of the corresponding proton results to extract from these data the polarized structure functions A n 1 and g 1 n of the (bound) neutron, which are so far unknown in the resonance region, W < 2 GeV. We compare our final results, including several moments of the deuteron and neutron spin structure functions, with various theoretical models and expectations as well as parametrizations of the world data. The unprecedented precision and dense kinematic coverage of these data can aid in future extractions of polarized parton distributions, tests of perturbative QCD predictions for the quark polarization at large x, a better understanding of quark-hadron duality, and more precise values for higher-twist matrix elements in the framework of the Operator Product Expansion.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Experimental Investigation and Finite Element Analysis on Fatigue Behavior of Aluminum Alloy 7050 Single-Lap Joints

The fatigue behavior of single-lap four-riveted aluminum alloy 7050 joints was investigated by using high-frequency fatigue test and scanning electron microscope (SEM). Stress distributions obtained by finite element (FE) analysis help explain the fatigue performance. The fatigue test results showed that the fatigue lives of the joints depend on cold expansion and applied cyclic loads. FE analysis and fractography indicated that the improved fatigue lives can be attributed to the reduction in maximum stress and evolution of fatigue damage at the critical location. The beneficial effects of strengthening techniques result in tearing ridges or lamellar structure on fracture surface, decrease in fatigue striations spacing, delay of fatigue crack initiation, crack deflection in fatigue crack propagation and plasticity-induced crack closure.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Effect of Hot Rolling on the Microstructure and Mechanical Properties of Nitrogen Alloyed Austenitic Stainless Steel

In the present investigation, the effect of multi-pass hot rolling in the temperature range of 700–1000 °C on the microstructure and mechanical properties of nitrogen alloyed austenitic stainless steel was studied with the aid of optical microscopy, tensile testing and x-ray diffraction measurements. The microstructural changes that occurred in the hot rolled specimens were elongation of grains in rolling direction, nucleation of new grains at the grain boundaries of elongated grains and growth of nucleated grains to form fully recrystallized grains. Elongated grains formed at lower rolling temperature (700–800 °C) due to inadequate strain/temperature for the initiation of dynamic recrystallization. At higher rolling temperature (900–1000 °C), fine grains formed due to dynamic recrystallization. Tensile properties showed strong dependency on the rolling temperature. Tensile strength increased with the decrease in the rolling temperature at the cost of ductility. Maximum strength was observed in samples hot rolled at 700 °C with yield strength of 917 MPa and ductility of 25%. This variation in the tensile properties with the rolling temperature is attributed to changes in the dislocation density and grain structure. The estimated yield strength from the dislocation density, solid solution and grain boundary strengthening closely matched with experimentally determined yield strength confirming the role of dislocation density and grain size in the strengthening.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Needle bacterial community structure across the species range of limber pine

Abstract Bacteria on and inside leaves can influence forest tree health and resilience. The distribution and limits of a tree species’ range can be influenced by various factors, with biological interactions among the most significant. We investigated the processes shaping the bacterial needle community across the species distribution of limber pine, a widespread Western conifer inhabiting a range of extreme habitats. We tested four hypotheses: (i) Needle community structure varies across sites, with site-specific factors more important to microbial assembly than host species selection; (ii) dispersal limitation structures foliar communities across the range of limber pine; (iii) the relative significance of dispersal and selection differs across sites in the tree species range; and (iv) needle age structures bacterial communities. We characterized needle communities from the needle surface and tissue of limber pine and co-occurring conifers across 16 sites in the limber pine distribution. Our findings confirmed that site characteristics shape the assembly of bacterial communities across the host species range and showed that these patterns are not driven by dispersal limitation. Furthermore, the strength of selection by the host varied by site, possibly due to differences in available microbes. Our study, by focusing on trees in their natural setting, reveals real needle bacterial dynamics in forests, which is key to understanding the balance between stochastic and deterministic processes in shaping forest tree-microbe interactions. Such understanding will be necessary to predict or manipulate these interactions to support forest ecosystem productivity or assist plant migration and adaptation in the face of global change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

3-D Prismatic Packaging Methodologies for Wide Band Gap Power Electronics Modules

In a power module the parasitic inductance limits the dynamic high-frequency performance, and the area of the cooling surfaces limits the power capability. This paper presents a new 3D power electronic design methodology based on the concept of mutual inductance cancellation and multi-sided heat transfer. New 3D prismatic packaging concepts are proposed for Wide Band Gap (WBG) power devices, where the devices can be mounted at acute angles to adjacent interconnects or other devices. Discussion is given on electrical and thermal path optimization in a 3D space. To validate the 3D prismatic packaging methodology, a 1200V/50A SiC half-bridge power module is fabricated and tested for electrical and thermal performance and results are compared with simulations. The power density calculated for the module is 12 kW/in3 (including heatsink) and shows a 31.3% inductance reduction compared to a 2D planar module. Finally, design guidance suggested for utilizing prismatic structures is provided, together with suggested future work in the area. This paper presents the first reported true 3D power module.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Air Blast Mesh Sensitivity and Pressure Mapping Study

Nose cone structural and aerodynamic characteristics are essential for intelligent design of aircraft, spacecraft, and ballistic systems. Finite element analysis can be used to help understand the structural integrity and flight characteristics of different nose cones. A mesh sensitivity study was undertaken for a particular nose cone geometry that was used in tests at LANL facilities in order to confirm the integrity of the meshed geometry. A simple cone that best matched closed-form theoretical solutions was modeled, and received good correlation to the theory. Complexity was then added back to the nose cone. Parameters applied to the simple cone were then implemented in the nose cone geometry giving assurance of accuracy after the geometry was changed. Nose cone results averaged 6.3% error for radial displacement when compared with the theoretical. Hoop stress averaged 6.0% error and meridional stress averaged 5.7% error at the finest mesh level. Meshes showed signs of convergence when compared to all three theoretical solutions. Finally, pressure time-history data from LANL computational fluid dynamics simulations was applied to the surface of the final nose cone geometry. The pressure data was interpolated from pressure gauge locations onto nearby meshed elements, which allowed for FEA software to run simulations on the cone with the pressure data as a loading condition. The pressure mapping resulted in the ability to understand the nose cone’s rigid body motion that in turn can inform design of future nose cones.

42 ENGINEERING↗

DOE OSTI2017

The Recommendations for Linear Measurement Techniques on the Measurements of Nonlinear System Parameters of a Joint.

In the study of the dynamics of nonlinear systems, experimental measurements often convolute the response of the nonlinearity of interest and the effects of the experimental setup. To reduce the influence of the experimental setup on the deduction of the parameters of the nonlinearity, the response of a mechanical joint is investigated under various experimental setups. These experiments first focus on quantifying how support structures and measurement techniques affect the natural frequency and damping of a linear system. The results indicate that support structures created from bungees have negligible influence on the system in terms of frequency and damping ratio variations. The study then focuses on the effects of the excitation technique on the response for a linear system. The findings suggest that thinner stingers should not be used, because under the high force requirements the stinger bending modes are excited adding unwanted torsional coupling. The optimal configuration for testing the linear system is then applied to a nonlinear system in order to assess the robustness of the test configuration. Finally, recommendations are made for conducting experiments on nonlinear systems using conventional/linear testing techniques.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Seismic Tomography 2024

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. Finally, it remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

58 GEOSCIENCES↗

DOE OSTI2024

Probing New Physics with Tau Leptons using the CMS Detector

The Standard Model (SM) of particle physics is a thoroughly well-tested theory of all electroweak scale phenomena to date—the most recent test being the discovery of the long-predicted Higgs boson. However, there is much evidence to suggest that it is incomplete. On the formal side, the mass of the Higgs particle itself is perplexingly small, while the largest theoretical energy scale of the SM is 17 orders of magnitude larger, a puzzle known as the hierarchy problem. On the experimental side, among other things, the SM lacks a candidate for dark matter, which is now known to play an indispensable role in astrophysical large scale structure formation. Many theories that address the fundamental puzzles of the SM predict the existence of multiple Higgs bosons, including a very light boson that couples preferentially to third-generation fermions. Observation of this new light boson, either directly produced or in the decay of the recently discovered SM Higgs, would provide an unmistakable sign of new dynamics in nature. The research supported by this award used data collected by the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) to explore boosted di-tau signatures of a new light boson as a tool in the quest to understand the shortcomings of the SM. With a proton-proton collision energy of 13 trillion electron-volts (TeV) and peak instantaneous proton luminosity of over 10^34 collisions per square centimeter per second (cm –2 s –1 ), the LHC is the only facility in the world that could enable this line of research. The research sought to address the hierarchy problem and other shortcomings of the SM through a mixture of LHC data analysis, maintenance of the CMS detector to ensure high quality data, and contributions to the Phase 2 upgrade detector for the upcoming High Luminosity phase of the LHC (HL-LHC).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

A Fluid Solver for Studying Torsional Galloping in Solar-Tracking PV Panel Arrays

Solar-tracking photovoltaic arrays are susceptible to aeroelastic fluttering during high-wind events. This dynamic fluttering behavior can grow in amplitude until the panels enter an unstable mode known as torsional galloping which can lead to panel failure or total array destruction. To better understand the physics of the torsional galloping phenomenon, and to inform the discussion around panel design and recommended panel stow positions during high wind events, a fluid-structure interaction solver composed of a simulated atmospheric boundary layer with simplified panel structural responses was designed. The simulation choices and features of this solver were informed by the geometry and physical properties of an experimental panel array known to exhibit torsional galloping behavior during hind-wind events. These simulations revealed that the torsional galloping instability is driven by a combination of cyclic vortex shedding from the sun-facing side of the panel and the elastic properties of the torque tube linking the panel assemblies. Testing different stow angles across a range of wind speeds indicates that panels are generally more stable when stowed at negative angles where the leading edge is closer to the ground, hypothesized to be due to ground-blocking effects.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2018

A peridynamic failure analysis of fiber-reinforced composite laminates using finite element discontinuous Galerkin approximations

Here, this paper presents a discontinuous Galerkin weak form for bond-based peridynamic models to predict the damage of fiber-reinforced composite laminates. To represent the anisotropy of a laminate in a peridynamic model, a lamina is simplified as a transversely isotropic medium under a plane stress condition. The laminated structure is modeled by stacking the surface mesh layers along the thickness direction according to the laminate sequence. To avoid a mesh dependence on either the fiber orientation or the discretization, the spherical harmonic expansion theory is employed to construct a function for the micro-elastic modulus in terms of the bond-fiber angle. The laminate material is decomposed into an isotropic matrix material part and a transversely isotropic material part. The bond stiffness can be evaluated using the engineering material constants, based on the equivalence between the elastic energy density in the peridynamic theory and the elastic energy density in the classic continuum mechanics theory. Benchmark tests are conducted to verify the proposed model. Numerical results illustrate that the convergence of simulations with different horizon sizes and meshes can be achieved. In terms of damage analysis, the proposed model can capture the dynamic process of the complex coupling of the inner-layer and delamination damage modes.

42 ENGINEERING↗

DOE OSTI2022

Multi-scale and multi-physics analysis, design optimization, and experimental validation of heat exchangers utilizing high performance, non-round tubes

Air-to-refrigerant heat exchangers (HXs) are fundamental components in HVAC&R systems, and considerable research has been dedicated designing continually smaller, lighter, and more efficient HX designs. In recent years, researchers have leveraged advancements in Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and optimization algorithms to consider primary tube shape and topology optimization to design highly compact, high performance HXs for a multitude of applications. In this research, we present a computationally efficient, comprehensive, multi-scale, and multi-physics analysis and optimization method for air-to-refrigerant HXs featuring automated CFD and FEA simulations and approximation-assisted optimization. This methodology was utilized to design HXs with shape-optimized, non-round tubes which outperform current state-of-the-art tube-fin HXs without compromising structural integrity. The optimal HXs were shown to deliver similar thermal performance to the baseline HXs while also achieving more than 20% reductions in airside pressure drop and core envelope volume and more than 30% reduction in internal volume. Comprehensive experimental validation of the optimization methodology was conducted through the testing of two prototypes in a standardized wind tunnel facility under multiple operating conditions. For prototype #1 under dry evaporator conditions, the predicted heat load agreed within ± 10% of measured values and the predicted airside pressure drop agreed within ± 30%, while for dehumidifying conditions, the predicted sensible and latent heat loads agreed within ± 10% and ± 20% of the measured values, respectively. For prototype #2, the predicted condenser heat load agreed within ± 3.0% of measured values, and the predicted airside pressure drop agreed within ± 27%. The acceptable agreement between simulation and experimental results for the present application highlights the flexibility of the novel optimization methodology to design next generation HXs with improved performance and reduced volume, weight, and environmental impact.

42 ENGINEERING↗

DOE OSTI2026

Unsupervised anomaly detection in MeV ultrafast electron diffraction

MeV ultrafast electron diffraction (MUED) is a pump-probe technique used to study the dynamic structural evolution of materials. An ultrashort laser pulse triggers structural changes, which are then probed by an ultrashort relativistic electron beam. To overcome low signal-to-noise ratios, diffraction patterns are averaged over thousands of shots. However, shot-to-shot instabilities in the electron beam can distort individual patterns, introducing uncertainty. Improving MUED accuracy requires detecting and removing these anomalous patterns from large datasets. In this work, we developed a fully unsupervised methodology for the detection of anomalous diffraction patterns. Using a convolutional autoencoder, we calculate the reconstruction mean squared error of the diffraction patterns. Based on the statistical analysis of this error, we provide the user an estimation of the probability that the pattern is normal, which also allows a posterior visual inspection of the images that are difficult to classify. This method has been trained with only 100 diffraction patterns and tested on 1521 patterns, resulting in a false positive rate between 0.2% and 0.4%, with a training time of 10 s per image and a test time of about 1 s per image. Here, the proposed methodology can also be applied to other diffraction techniques in which large datasets are collected that include faulty images due to instrumental instabilities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Dynamic Structure of Magnetized High Energy Density Plasmas (Final Report)

This report summarizes results of project DE-SC0022202 ``Dynamic Structure of Magnetized High Energy Density Plasmas,'' which was originally funded for the period 08/01/2021 - 7/31/2022, but was no-cost extended to 7/31/2023. The primary objectives of the work, as stated in the original proposal, were ``develop a theory to describe a novel state of magnetized high energy density plasmas, benchmark the theory using first-principles molecular dynamics simulations, and apply the results to develop a means to interpret x-ray scattering measurements in future experiments.'' These were the goals of the original project proposal, which was for a 3 year project. The project was ultimately funded for 1 year, and so the work completed focused on the goals described for only the first year of the proposed work. This included further developing a kinetic theory for strongly magnetized plasmas, applying it to compute fluid-scale (MHD) transport coefficients, and to test the predictions using molecular dynamics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Exploring pH Dynamics in Amino Acid Solutions Under Low-Temperature Plasma Exposure

Low-temperature plasma (LTP) offers a promising alternative for cancer therapy, as it targets malignant cells selectively while minimizing damage to healthy tissues. Upon interaction with an aqueous solution, LTP generates reactive oxygen and nitrogen species and thereby influences the solution’s pH, which is a crucial factor in cancer proliferation and response to treatment. This study investigated the effects of LTP on the pH of aqueous solutions, with a focus on the effect of LTP parameters such as voltage, frequency, and irradiation time. In addition, it explored the influence of solution composition, specifically the presence of the amino acids, glycine and serine, on pH changes; these amino acids are known to play significant roles in cancer proliferation. Our results indicated that LTP induces acidification in deionized water, in which the extent of acidification increased proportionally with plasma parameters. In glycine-containing solutions, pH changes were concentration-dependent, whereas serine-containing solutions maintained a constant pH across all tested concentrations. To investigate potential changes to the structural properties of glycine and serine exposed to LTP that could be responsible for different pH responses, we analyzed the samples using FTIR spectroscopy. A significant decrease in absorbance was observed for solutions with low concentrations of amino acids, suggesting their degradation.

Biochemistry & Molecular Biology↗

DOE OSTI2019

Episodes of Warm-Air Advection Causing Cloud-Surface Decoupling During the MARCUS

It has been understood for decades that advection of a cloud-topped marine boundary layer (CTBL) over warmer sea surface causes the stratification (or decoupling) of the CTBL via the entrainment feedback, a mechanism commonly known as “deepening-warming” decoupling that is typical in subtropics. This study focuses on the opposite direction of advection, that is, low-level warm air advection (LLWAA), and its impacts on the decoupling degree of a CTBL. Our hypothesis is that LLWAA stabilizes a CTBL, causing a decoupling of the CTBL. It is tested for three LLWAA episodes observed during the Measurements of Aerosols, Radiation, and CloUds over the Southern Ocean (MARCUS) field campaign between the Hobart (43°S, 147°E), Australia, and several Antarctic coast stations. By synthesizing the shipborne measurements of CTBL structure, Himawari-8 satellite imagery of cloud fields, and reanalysis of meteorological field, four common characteristics of CTBLs under the LLWAA are found: (1) CTBLs are highly stratified to the extent that penetrations of cumulus into main temperature inversions, which are common for subtropical decoupled CTBLs, do not exist; (2) sea surface temperature is 1–2 K lower than the near-surface air temperature; (3) clouds manifest stratiform with lifetime as long as several tens of hours; and (4) they locate in warm sectors of middle-latitude cyclones. Possible mechanisms for the maintenance of decoupled clouds under LLWAA are discussed in terms of dynamic and thermodynamic factors. Lapse rates of the decoupled CTBLs are markedly lower than those commonly used for passive satellite estimation of cloud top heights.

54 ENVIRONMENTAL SCIENCES↗