Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “structured”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Atomic protein structure refinement using all-atom graph representations and SE(3)-equivariant graph transformer

Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spiral antenna assembly with integrated feed network structure and method of manufacture

A spiral antenna assembly with an integrated feed network and method of manufacturing the same are disclosed. The spiral antenna assembly may comprise a supporting structure integrally formed with a feed network structure, thereby presenting a monolithic structure. A spiral antenna element may be disposed on a bottom surface or a top surface of the supporting structure. The feed network structure may comprise the feed network and project from a center of the top surface of the supporting structure. The feed network may comprise a microstrip balun architecture. The spiral antenna assembly may be formed by additively manufacturing the supporting structure and the feed network structure. A laser direct structuring process may write and activate the spiral antenna element on the supporting structure and the feed network on the feed network structure.

Byers, Kyle J.↗
DOE OSTI2023

Identification of over ten thousand candidate structured RNAs in viruses and phages

Structured RNAs play crucial roles in viruses, exerting influence over both viral and host gene expression. However, the extensive diversity of structured RNAs and their ability to act in cis or trans positions pose challenges for predicting and assigning their functions. While comparative genomics approaches have successfully predicted candidate structured RNAs in microbes on a large scale, similar efforts for viruses have been lacking. In this study, we screened over 5 million DNA and RNA viral sequences, resulting in the prediction of 10,006 novel candidate structured RNAs. These predictions are widely distributed across taxonomy and ecosystem. We found transcriptional evidence for 206 of these candidate structured RNAs in the human fecal microbiome. These candidate RNAs exhibited evidence of nucleotide covariation, indicative of selective pressure maintaining the predicted secondary structures. Our analysis revealed a diverse repertoire of candidate structured RNAs, encompassing a substantial number of putative tRNAs or tRNA-like structures, Rho-independent transcription terminators, and potentially cis-regulatory structures consistently positioned upstream of genes. In summary, our findings shed light on the extensive diversity of structured RNAs in viruses, offering a valuable resource for further investigations into their functional roles and implications in viral gene expression and pave the way for a deeper understanding of the intricate interplay between viruses and their hosts at the molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Directed self-assembly of chiral liquid crystals into biomimetic bouligand structures in thin film

The Bouligand structure, renowned for its helicoidal arrangement and enhanced mechanical properties, has attracted significant research interest for its ability to impart enhanced strength to intrinsically soft materials. Biomimetic approaches have centered on fibrous structures in bulk materials, but translating this architecture into thin-film regime for miniaturized-wearable devices with programmable functions remains challenging. Here, we direct the self-assembly of cholesteric liquid crystals (CLCs) into hierarchical helical structures using chemically patterned surfaces. Alternating surface anchoring regions align uniform lying-down helices at the nanoscale, guiding a secondary microscale helical structure exhibiting both left- and right-handed twists. This mimetic Bouligand structure in CLCs enables optical modulation under applied field and strain with enhanced mechanical response. Simulations reveal the structural evolution from initial Bouligand configuration in LC layers to alternating twist helices. This research provides a basis for designing and manufacturing miniaturized or wearable devices with nanometer-scale precision in regulating electro-optical and mechanical properties. Bouligand structures, which offer strength in natural materials, are of interest but difficult to obtain. Here, the authors report the development of such structures by directed self-assembly of cholesteric single crystals into hierarchical helical structures, with the secondary structure having right and left-handed twists.

Bouligand structure↗
DOE OSTI2024

Structural determination of a full-length plant cellulose synthase informed by experimental and in silico methods

Three-dimensional structure determination and prediction of proteins with intrinsically disordered regions, unstructured regions, conformational flexibility, and lacking homologous structures are challenging. We previously predicted and refined an in silico structure of a plant cellulose synthase from cotton (GhCESA1), and more recently, cryo-electron microscopy (cryo-EM) has resolved a majority of the lengths of two CESA structures from poplar (PttCESA8) and cotton (GhCESA7). However, 26–30% of these cryo-EM structures remain unresolved, including the N-terminal domain, half of the class-specific region, the gating loop region, and the C-terminal domain. Here, we describe the generation and evaluation of a full-length hybrid GhCESA1 model based on this cryo-EM PttCESA8 structure, with unresolved regions completed using this in silico refined GhCESA1 model. All-atom molecular dynamics simulations and subsequent energy minimizations were performed for the in silico and hybrid GhCESA1 models in a lipid bilayer-water-ion environment, and structural stability, dynamics, energetics, contacts, and quality were evaluated. The unresolved regions were found to be the most dynamic, in agreement with their poor electron density with cryo-EM. The hybrid model exhibited a higher total secondary structure content, more favorable intra-protein and protein-lipid interaction energies, and improved quality metrics. Moreover, hydrogen bonding was revealed to be a primary mechanism for intra-protein and protein-lipid contacts. These results demonstrate that in silico structure prediction and refinement may be useful to augment experimental structure determination, especially for disordered and unstructured regions. Furthermore, this hybrid model can serve as a steppingstone to derive full-length homology models of other CESAs found in more experimentally tractable organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Protein remote homology detection and structural alignment using deep learning

Exploiting sequence–structure–function relationships in biotechnology requires improved methods for aligning proteins that have low sequence similarity to previously annotated proteins. We develop two deep learning methods to address this gap, TM-Vec and DeepBLAST. TM-Vec allows searching for structure–structure similarities in large sequence databases. It is trained to accurately predict TM-scores as a metric of structural similarity directly from sequence pairs without the need for intermediate computation or solution of structures. Once structurally similar proteins have been identified, DeepBLAST can structurally align proteins using only sequence information by identifying structurally homologous regions between proteins. It outperforms traditional sequence alignment methods and performs similarly to structure-based alignment methods. We show the merits of TM-Vec and DeepBLAST on a variety of datasets, including better identification of remotely homologous proteins compared with state-of-the-art sequence alignment and structure prediction methods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Pressure-induced order–disorder transitions in β-In 2 S 3 : an experimental and theoretical study of structural and vibrational properties

We report this joint experimental and theoretical study of the structural and vibrational properties of β-In 2 S 3 upon compression shows that this tetragonal defect spinel undergoes two reversible pressure-induced order–disorder transitions up to 20 GPa. We propose that the first high-pressure phase above 5.0 GPa has the cubic defect spinel structure of α-In 2 S 3 and the second high-pressure phase ($\phi$-In 2 S 3 ) above 10.5 GPa has a defect α-NaFeO 2 -type (R$\bar{3}$) structure. This phase, related to the NaCl structure, has not been previously observed in spinels under compression and is related to both the tetradymite structure of topological insulators and to the defect LiTiO 2 phase observed at high pressure in other thiospinels. Structural characterization of the three phases shows that α-In 2 S 3 is softer than β-In 2 S 3 while $\phi$-In 2 S 3 is harder than β-In 2 S 3 . Vibrational characterization of the three phases is also provided, and their Raman-active modes are tentatively assigned. Our work shows that the metastable α phase of In 2 S 3 can be accessed not only by high temperature or varying composition, but also by high pressure. On top of that, the pressure-induced β–α–$\phi$ sequence of phase transitions evidences that β-In 2 S 3 , a B III 2 X V 3 compound with an intriguing structure typical of A II B III 2 X VI 4 compounds (intermediate between thiospinels and ordered-vacancy compounds) undergoes: (i) a first phase transition at ambient pressure to a disordered spinel-type structure (α-In 2 S 3 ), isostructural with those found at high pressure and high temperature in other B III 2 X V 3 compounds; and (ii) a second phase transition to the defect α-NaFeO 2 -type structure ($\phi$-In 2 S 3 ), a distorted NaCl-type structure that is related to the defect NaCl phase found at high pressure in A II B III 2 X VI 4 ordered-vacancy compounds and to the defect LiTiO 2 -type phase found at high pressure in A II B III 2 X VI 4 thiospinels. This result shows that In 2 S 3 (with its intrinsic vacancies) has a similar pressure behaviour to thiospinels and ordered-vacancy compounds of the A II B III 2 X VI 4 family, making β-In 2 S 3 the union link between such families of compounds and showing that group-13 thiospinels have more in common with ordered-vacancy compounds than with oxospinels and thiospinels with transition metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The influence of the 6s 2 configuration of Bi 3+ on the structures of A′BiNb 2 O 7 (A′ = Rb, Na, Li) layered perovskite oxides

Solid state compounds which exhibit non-centrosymmetric crystal structures are of great interest due to the physical properties they can exhibit. Here, the ‘hybrid improper’ mechanism – in which two non-polar distortion modes couple to, and stabilize, a further polar distortion mode, yielding an acentric crystal structure – offers opportunities to prepare a range of novel non-centrosymmetric solids, but examples of compounds exhibiting acentric crystal structures stabilized by this mechanism are still relatively rare. Here we describe a series of bismuth-containing layered perovskite oxide phases, RbBiNb 2 O 7 , LiBiNb 2 O 7 and NaBiNb 2 O 7 , which have structural frameworks compatible with hybrid-improper ferroelectricity, but also contain Bi 3+ cations which are often observed to stabilize acentric crystal structures due to their 6s 2 electronic configurations. Neutron powder diffraction analysis reveals that RbBiNb 2 O 7 and LiBiNb 2 O 7 adopt polar crystal structures (space groups I2cm and B2cm respectively), compatible with stabilization by a trilinear coupling of non-polar and polar modes. The Bi 3+ cations present are observed to enhance the magnitude of the polar distortions of these phases, but are not the primary driver for the acentric structure, as evidenced by the observation that replacing the Bi 3+ cations with Nd 3+ cations does not change the structural symmetry of the compounds. In contrast the non-centrosymmetric, but non-polar structure of NaBiNb 2 O 7 (space group P2 1 2 1 2 1 ) differs significantly from the centrosymmetric structure of NaNdNb 2 O 7 , which is attributed to a second-order Jahn-Teller distortion associated with the presence of the Bi3+ cations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Effect of the abolition of intersubunit salt bridges on allosteric protein structural dynamics

A salt bridge, one of the representative structural factors established by non-covalent interactions, plays a crucial role in stabilizing the structure and regulating the protein function, but its role in dynamic processes has been elusive. Here, to scrutinize the structural and functional roles of the salt bridge in the process of performing the protein function, we investigated the effects of salt bridges on the allosteric structural transition of homodimeric hemoglobin (HbI) by applying time-resolved X-ray solution scattering (TRXSS) to the K30D mutant, in which the interfacial salt bridges of the wild type (WT) are abolished. The TRXSS data of K30D are consistent with the kinetic model that requires one monomer intermediate in addition to three structurally distinct dimer intermediates (I 1 , I 2 , and I 3 ) observed in WT and other mutants. The kinetic and structural analyses show that K30D has an accelerated biphasic transition from I 2 to I 3 by more than nine times compared to WT and lacks significant structural changes in the transition from R-like I 2 to T-like I 3 observed in WT, unveiling that the loss of the salt bridges interrupts the R–T allosteric transition of HbI. Besides, the correlation between the bimolecular CO recombination rates in K30D, WT, and other mutants reveals that the bimolecular CO recombination is abnormally decelerated in K30D, indicating that the salt bridges also affect the cooperative ligand binding in HbI. These comparisons of the structural dynamics and kinetics of K30D and WT show that the interfacial salt bridges not only assist the physical connection of two subunits but also play a critical role in the global structural signal transduction of one subunit to the other subunit via a series of well-organized structural transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Geometry and dynamics of passive scalar structures in compressible turbulent mixing

We present a structure-based numerical analysis of passive scalar mixing in decaying homogeneous isotropic turbulence (DHIT) and shock-turbulence interaction canonical configurations. The analysis focuses on the temporal evolution of ensembles of passive scalar structures, initialized as spheres of different sizes relative to the Taylor microscale. An algorithm is introduced to track the evolution of each individual structure and the interactions with other structures in the ensemble, relating changes in the surface geometry and the underlying physical processes (turbulent transport, scalar dissipation, and shock compression). The tracking algorithm is applied to datasets from shock-capturing direct numerical simulations of DHIT, with Taylor microscale Reynolds number Re λ =40 and turbulence Mach number M t =0.2 ⁠, and STI cases in which the turbulence is processed by a shock wave at Mach numbers M = 1.5 and 3.0. Temporal surface convolution increases for initially larger structures, resulting in a higher probability of locally hyperbolic geometries where breakup into smaller structures occurs. Shock-induced deformation of the structures amplifies breakup processes, enhancing mixing, particularly for larger structures. Mixing enhancement by the shock is manifested as an amplification of the surface-averaged scalar gradient, which increases for initially larger structures. The alignment between the scalar gradient and the most extensional strain-rate eigendirection on the scalar isosurfaces also increases across the shock. Larger magnitudes of the scalar gradient and its alignment with the most compressive strain-rate eigendirection correlate with flatter surface regions. Shock-induced structure compression increases the area coverage of flat regions, where the amplification of scalar gradient is localized.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Predicted structural proteome of Sphagnum divinum and proteome-scale annotation

Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental crystal structure from any Sphagnum species exists in the Protein Data Bank and fewer than 200 Sphagnum-related genes have structural models available in the AlphaFold Protein Structure Database. Tools and resources are needed to help bridge these gaps, and to enable the analysis of other structural proteomes now made possible by accurate structure prediction. We present the predicted structural proteome (25,134 primary transcripts) of Sphagnum divinum computed using AlphaFold, structural alignment results of all high-confidence models against an annotated nonredundant crystallographic database of over 90,000 structures, a structure-based classification of putative Enzyme Commission (EC) numbers across this proteome, and the computational method to perform this proteome-scale structure-based annotation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Monthly averages of ED2 model simulations initialized with airborne lidar structure, Jan 1981-Dec 2018, Brazilian Amazon

Deforestation and forest degradation (selective logging, fires, fragmentation) have impacted nearly 40% of the original extent of the Brazilian Amazon, and have markedly impacted forest structure across the region. To date, few studies analysed how shifts in forest structure from degradation influence the forest sensitivity to climate extremes, because of the complex interactions between forest structure and micro-environmental conditions. To address this knowledge gap, we carried out a series of simulations across the Brazilian Amazon using the Ecosystem Demography Model (ED2), using observed forest structure derived from 541 airborne lidar transects (375 ha each) and two scenarios representing forest recovery and expansion of degradation to investigate how shifts in forest structure impact ecosystem function under near-average and extreme climate conditions, as part of the manuscript Longo et al 2025 "Degradation and Deforestation Increase the Sensitivity of the Amazon Forest to Climate Extremes". This dataset provides the output results from the ED2 model simulations for the three simulations at monthly time scales, in NetCDF format. For all simulations, we used bias-corrected hourly reanalyses (WFDE5) for most meteorological drivers, except for precipitation, which was obtained from CHIRPS. The meteorological drivers used in the study span 38 years (Jan 1981–Dec 2018). The output results correspond to the last 38 years of simulation (one full cycle of meteorological drivers), in which ED2 simulations used static stand structure (i.e., the forest structure was held constant). The following files are provided:ED2_emean_Global_R004_BrAmaz_s1c0t0l0f0.nc. This corresponds to the Control simulation. The forest structure was obtained from the airborne lidar.ED2_emean_Global_R005_BrAmaz_s1c0t1l1f0.nc. This corresponds to the Degraded simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that expanded deforestation and selective logging across the Amazon.ED2_emean_Global_R006_BrAmaz_s1c0t1l0f0.nc. This corresponds to the Recovery simulation. The forest structure was obtained from a spin-up simulation initialized with airborne lidar and a scenario that completely halted deforestation and degradation, allowing degraded forests to recover for 38 years.We also provide file ED2_zones_R004_BrAmaz_s1c0t0l0f0.nc, which classifies each grid cell into zones used in the reference manuscript: 1: Southeast. 2: South. 3: West. 4: Central. 5: Northeast. 6: North. 7: Northwest". Index 0 corresponds to grid cells excluded from sub-region analyses because they were dominated by flooded forests, deforestation, and naturally non-forest vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Development of Large Scale Extrusion Deposition for Structural Applications

Large Scale Extrusion Deposition (LSED) is an evolving additive manufacturing (AM) technology that research, such as that taking place at Oak Ridge National Laboratory (ORNL) and companies like Local Motors, are continuing to utilize and develop new applications. A major LSED application of interest has been molds and tooling as it allows for much shorter production time and lower cost. However, interest has been expanding into using LSED for more structural applications due to more frequent use of high performing polymer composites as feedstock. The use of LSED for structural applications is of particular interest to Local Motors as it is currently being used to create commercially viable, energy efficient electric vehicles. LSED offers a unique opportunity when compared to traditional manufacturing methods as it can significantly reduce the number of components necessary, while decreasing embodied energy and carbon emissions. Even with these benefits however, it is important that LSED is properly understood from a structural aspect as this field has not been as heavily researched as tooling. To ensure a high level of safety and repeatability is an essential responsibility of a manufacturer whose products are structural in nature. As such it is important to understand the materials and LSED process to make structural objects that the manufacturer can be confident in. The main goals of this project were to: develop and investigate materials that are of interest for structural LSED applications, further develop and understand the current machines used in LSED and develop simulations tools of LSED and the mechanical properties of the created structure. Material development focused on composite materials that have high mechanical properties and are stable in a variety of environments. The materials were tested to determine their as printed mechanical and thermal properties as these are necessary for simulations. Once the materials were investigated thoroughly, it allowed for simulations to be performed to compare to experimental data with simulations. Materials were also vetted to determine candidates for multi-material printing. The machine development focused around the areas of process monitoring, non-destructive evaluation, and quality control. Finally, the goal of the simulations was to develop a realistic model of printed structures, including in-process simulation and dynamic simulation. The routes to get to some of these goals and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. This project resulted in many valuable results such as the development of an nondestructive evaluation (NDE) technique for interlayer defects, proof of simulation for warpage in simple parts, the development and utilization of a profilometer to monitor a print for defects or inconsistencies, thorough investigation of a material used commercially for structural LSED applications and valuable experimental data on the applicability and advantages of multi-material crush structures versus their neat counterparts by creation and testing of samples.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimizing group structures using hierarchical division

Creating group structures with few groups that give low errors is a difficult problem in reactor analysis. In recent years, automated optimization techniques have been applied to this task. We continue this trend by applying the hierarchical division algorithm to generate optimized group structures that minimize a cost function. At each stage, the algorithm adds a single group boundary to an existing group structure, dividing one group into two to increase the resolution of the group structure. The location of the added boundary is the one that gives the lowest error over all possible new boundary locations. Our implementation requires a beginning group structure, a set of candidate new boundary locations, and a set of reference reaction rates. As a proof of concept, we used WIMS-69 as the initial group structure, XMAS-172 as the ending group structures, and a 344-group reference group structure. Testing on two simple, homogenized reactor problems, we found that hierarchical division was able to reduce the error by a factor of around 5 with an increase of only 15% in the number of groups. Because hierarchical division can get stuck in local minima, it often reaches a plateau in its error reduction capability as many groups are added. Nevertheless, we find hierarchical division has strong potential to make good group structures into great group structures at a modest increase in computational cost. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Shaker-structure interaction modeling and analysis for nonlinear force appropriation testing

Nonlinear force appropriation is an extension of its linear counterpart where sinusoidal excitation is applied to a structure with a modal shaker and phase quadrature is achieved between the excitation and response. While a standard practice in modal testing, modal shaker excitation has the potential to alter the dynamics of the structure under test. Previous studies have been conducted to address several concerns, but this work specifically focuses on a shaker-structure interaction phenomenon which arises during the force appropriation testing of a nonlinear structure. Under pure-tone sinusoidal forcing, a nonlinear structure may respond not only at the fundamental harmonic but also potentially at sub- or superharmonics, or it can even produce aperiodic and chaotic motion in certain cases. Shaker-structure interaction occurs when the response physically pushes back against the shaker attachment, producing non-fundamental harmonic content in the force measured by the load cell, even for pure tone voltage input to the shaker. This work develops a model to replicate these physics and investigates their influence on the response of a nonlinear normal mode of the structure. Experimental evidence is first provided that demonstrates the generation of harmonic content in the measured load cell force during a force appropriation test. This interaction is replicated by developing an electromechanical model of a modal shaker attached to a nonlinear, three-mass dynamical system. Several simulated experiments are conducted both with and without the shaker model in order to identify which effects are specifically due to the presence of the shaker. Finally, the results of these simulations are then compared to the undamped nonlinear normal modes of the structure under test to evaluate the influence of shaker-structure interaction on the identified system’s dynamics.

42 ENGINEERING↗
DOE OSTI2023

Li 2 GeS 3 : Lithium Ionic Conductor with an Unprecedented Structural Type

Lithium-ion batteries (LIBs) are widely used in electric vehicles, mobile electronic devices, and large-scale stationary energy storage systems. However, their liquid electrolytes present significant safety concerns due to their inherent flammability. To address this, the focus has shifted toward all-solid-state batteries (ASSBs) utilizing inorganic solid electrolytes that promise enhanced safety. In this work, we report the discovery of a new crystal structural type of Li-ion conductor, Li 2 GeS 3 , with a unique structure, synthesized by a solid-state reaction from Li 2 S and GeS 2 . It was first reported in 2000 with an orthorhombic unit cell, but its detailed crystal structure remains veiled. Here, we have unveiled its structure for the first time, employing an ab initio structure determination technique from powder X-ray and time-of-flight neutron diffraction data. The compound has an unprecedented crystal structural type with a hexagonal $P6_1$ symmetry and a unit cell of α = 6.79364(4) Å and c = 17.90724(14) Å. Its structure is comprised of a distorted hexagonal close-packed arrangement of sulfur anions with three asymmetric metal atoms: Li1, Li2, and Ge are in tetrahedral cavities surrounded by sulfur atoms. The ionic conductivity of Li 2 GeS 3 was measured to be 1.63 × 10 –8 S cm –1 at 303 K and 2.45 × 10 –7 S cm –1 at 383 K. Bond valence energy landscape calculations revealed three-dimensional lithium diffusion pathways within the structure. This novel crystal structure in Li 2 GeS 3 holds the potential for developing high-performance ionic conductors through suitable chemical substitution and offers valuable insights into designing new ionic conductors for ASSBs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures

Proteins have been found to inhabit a diverse set of three-dimensional structures. The dynamics that govern protein interconversion between structures happen over a wide range of time scales-picoseconds to seconds. Our understanding of protein functions and dynamics is largely reliant upon our ability to elucidate physically populated structures. From an experimental structural characterization perspective, we are often limited to measuring the ensemble-averaged structure both in the steady-state and time-resolved regimes. Generating kinetic models and understanding protein structure–function relationships require atomistic knowledge of the populated states in the ensemble. Here, we present ensemble refinement methodologies that integrate time-resolved experimental signals with molecular dynamics models. We first discuss integration of experimental structural restraints to molecular models in disordered protein systems that adhere to the principle of maximum entropy for creating a complete set of ensemble structures. We then propose strategies to find kinetic pathways between the refined structures, using time-resolved inputs to guide molecular dynamics trajectories and the use of inference to generate tailored stimuli to prepare a desired ensemble of protein states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗