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DOE OSTI2021

The Human Proteoform Project: Defining the human proteome

Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown. We propose here an ambitious initiative to define the human proteome, that is, to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented along with a call for improved technologies in a two-pronged strategy to the Human Proteoform Project.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Toward Accelerated Nuclear-physics Parameter Estimation from Binary Neutron Star Mergers: Emulators for the Tolman–Oppenheimer–Volkoff Equations

Abstract Gravitational-wave observations of binary neutron-star (BNS) mergers have the potential to revolutionize our understanding of the nuclear equation of state (EOS) and the fundamental interactions that determine its properties. However, Bayesian parameter estimation frameworks do not typically sample over microscopic nuclear-physics parameters that determine the EOS. One of the major hurdles in doing so is the computational cost involved in solving the neutron-star structure equations, known as the Tolman–Oppenheimer–Volkoff (TOV) equations. In this paper, we explore approaches to emulating solutions for the TOV equations: multilayer perceptrons (MLPs), Gaussian processes, and a data-driven variant of the reduced basis method (RBM). We implement these emulators for three different parameterizations of the nuclear EOS, each with a different degree of complexity represented by the number of model parameters. We find that our MLP-based emulators are generally more accurate than the other two algorithms, whereas the RBM results in the largest speedup with respect to the full high-fidelity TOV solver. We employ these emulators for a simple parameter inference using a potentially loud BNS observation and show that the posteriors predicted by our emulators are in excellent agreement with those obtained from the full TOV solver.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Bismuth as a Reactive Solvent in the Synthesis of Multicomponent Transition-Metal-Bearing Bismuthides

Employment of liquid bismuth (Bi) allows the facile single-crystal growth of compounds containing elements with high melting points, provided that these elements have reasonably high solubility in Bi. Utilization of the Bi flux approach yielded two new ternary bismuthides, SrNi 0.17(1) Bi 2 [a defect variant of the BaCuSn 2 type, space group Cmcm , α = 4.879(2) Å, b = 17.580(6) Å, and c = 4.696(2) Å] and CaTi 3 Bi 4 [NdTi 3 (Sn 0.1 Sb 0.9 ) 4 structure type, space group Fmmm , a = 5.6295(7) Å, b = 9.8389(1) Å, and c = 23.905(3) Å]. In addition, the ternary antimonide CaV3Sb4, isostructural with CaTi 3 Bi 4 , was synthesized from antimony (Sb) flux, and analyzed with the goal of validating structural assessment of the bismuthide analogue, where the X-ray crystallographic work proved to be very challenging. All synthesized compounds exhibit complex crystal structures featuring quasi-two-dimensional building blocks of different topologies. First-principle calculations reveal hypervalent bonding in the homoatomic Bi subunits. Lastly, physical property measurements indicate metallic conductivity and the absence of localized magnetism in the studied compounds.

36 MATERIALS SCIENCE↗

DOE OSTI2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Structure-driven development of a biomimetic rare earth artificial metalloprotein

The 2011 discovery of the first rare earth–dependent enzyme in methylotrophic Methylobacterium extorquens AM1 prompted intensive research toward understanding the unique chemistry at play in these systems. This enzyme, an alcohol dehydrogenase (ADH), features a La 3+ ion closely associated with redox-active coenzyme pyrroloquinoline quinone (PQQ) and is structurally homologous to the Ca 2+ -dependent ADH from the same organism. AM1 also produces a periplasmic PQQ-binding protein, PqqT, which we have now structurally characterized to 1.46-Å resolution by X-ray diffraction. This crystal structure reveals a Lys residue hydrogen-bonded to PQQ at the site analogously occupied by a Lewis acidic cation in ADH. Accordingly, we prepared K 142 A- and K 142 D-PqqT variants to assess the relevance of this site toward metal binding. Isothermal titration calorimetry experiments and titrations monitored by UV–Vis absorption and emission spectroscopies support that K 142 D-PqqT binds tightly (Kd = 0.6 ± 0.2 μM) to La 3+ in the presence of bound PQQ and produces spectral signatures consistent with those of ADH enzymes. These spectral signatures are not observed for WT- or K 142 A-variants or upon addition of Ca 2+ to PQQ ⸦ K 142 D-PqqT. Addition of benzyl alcohol to La 3+ -bound PQQ ⸦ K 142 D-PqqT (but not Ca 2+ -bound PQQ ⸦ K 142 D-PqqT, or La 3+ -bound PQQ ⸦ WT-PqqT) produces spectroscopic changes associated with PQQ reduction, and chemical trapping experiments reveal the production of benzaldehyde, supporting ADH activity. By creating a metal binding site that mimics native ADH enzymes, we present a rare earth-dependent artificial metalloenzyme primed for future mechanistic, biocatalytic, and biosensing applications.

Science & Technology - Other Topics↗

DOE OSTI2025

Text Mining for Process–Structure–Properties Relationships in Metals

With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery—although significant challenges remain. While LLMs offer promising few- and zero-shot learning capabilities, particularly valuable in the materials domain where expert annotations are scarce, general-purpose LLMs often fail to address key materials-specific queries without further adaptation. To bridge this gap, fine-tuning LLMs on human-labeled data is essential for effective structured knowledge extraction (Liu in The Importance of Human-Labeled Data in the Era of LLMs, 2023). Here, in this study, we introduce a novel annotation schema designed to extract generic process–structure–properties relationships from scientific literature. We demonstrate the utility of this approach using a dataset of 128 abstracts, with annotations drawn from two distinct domains: high-temperature materials (Domain I) and uncertainty quantification in simulating materials microstructure (Domain II). Initially, we developed a conditional random field (CRF) model based on MatBERT—a domain-specific BERT variant—and evaluated its performance on Domain I. Subsequently, we compared this model with a fine-tuned LLM (GPT-4o from OpenAI) under identical conditions. Our results indicate that fine-tuning LLMs can significantly improve entity extraction performance over the BERT-CRF baseline on Domain I. However, when additional examples from Domain II were incorporated, the performance of the BERT-CRF model became comparable to that of the GPT-4o model. These findings underscore the potential of our schema for structured knowledge extraction and highlight the complementary strengths of both modeling approaches.

Materials science↗

DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗

DOE OSTI2025

The Impact of Carotenoid Energy Levels on the Exciton Dynamics and Singlet–Triplet Annihilation in Isolated Bacterial Light-Harvesting 2 Complexes

The light-harvesting 2 (LH2) complex of purple phototrophic bacteria plays a critical role in absorbing solar energy and distributing the excitation energy. Exciton dynamics within LH2 complexes are controlled by the structural arrangement and energy levels of the bacteriochlorophyll (BChl) and carotenoid (Car) pigments. However, there is still debate over the competing light-harvesting versus energy-dissipation pathways. In this work, we compared five variants of the LH2 complex from genetically modified strains of Rhodobacter sphaeroides, all containing the same BChls but different Cars with increasing conjugation: zeta-carotene (N = 7; LH2 Zeta ), neurosporene (N = 9; LH2 Neu ), spheroidene (N = 10; LH2 Spher ), lycopene (N = 11; LH2 Lyco ), and spirilloxanthin (N = 13; LH2 Spir ). Absorption measurements confirmed that the Car excited-state energy decreased with increasing conjugation. Similarly, fluorescence spectra showed that the B850 BChl emission peak had an increasing red shift from LH2 Zeta →(LH2 Neu /LH2 Spher )→LH2 Lyco →LH2 Spir . In contrast, time-resolved fluorescence and ultrafast transient absorption (fs-TA) revealed similar excited-state lifetimes (∼1 ns) for all complexes except LH2 Spir (∼0.7 ns). From fs-TA analysis, an additional ∼7 ps nonradiative dissipation step from B850 BChl was observed for LH2 Zeta . Further, singlet− singlet and singlet−triplet annihilation studies showed a ∼50% average fluorescence lifetime reduction in LH2Zeta at high laser power and high repetition rate, compared to ∼10−15% reductions in LH2 Neu /LH2 Spher /LH2 Lyco and minimal lifetime change in LH2 Spir . In LH2 Zeta , the fastest decay component (<50 ps) became prominent at high repetition rates, consistent with strong singlet−triplet annihilation. Nanosecond TA measurements revealed long-lived (>40 μs) BChl triplet states in LH2 Zeta and signs of damage caused by singlet oxygen, whereas other LH2s showed faster triplet quenching (∼18 ns) by Cars. These findings highlight a key design principle of LH2 complexes: the Car triplet energy must be significantly lower than the BChl triplet energy to efficiently quench BChl triplets that otherwise act as potent “trap states,” causing exciton annihilation in laser-based experiments or photodamage in native membranes.

Absorption↗

DOE OSTI2025

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

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

RIXS↗

DOE OSTI2020

Lanthanide-dependent alcohol dehydrogenases require an essential aspartate residue for metal coordination and enzymatic function

The lanthanide elements (Ln 3+ ), those with atomic numbers 57–63 (excluding promethium, Pm 3+ ), form a cofactor complex with pyrroloquinoline quinone (PQQ) in bacterial XoxF methanol dehydrogenases (MDHs) and ExaF ethanol dehydrogenases (EDHs), expanding the range of biological elements and opening novel areas of metabolism and ecology. Other MDHs, known as MxaFIs, are related in sequence and structure to these proteins, yet they instead possess a Ca 2+ -PQQ cofactor. An important missing piece of the Ln 3+ puzzle is defining what features distinguish enzymes that use Ln 3+ -PQQ cofactors from those that do not. In this work, using XoxF1 MDH from the model methylotrophic bacterium Methylorubrum extorquens AM1, we investigated the functional importance of a proposed lanthanide-coordinating aspartate residue. We report two crystal structures of XoxF1, one with and another without PQQ, both with La 3+ bound in the active-site region and coordinated by Asp 320 . Using constructs to produce either recombinant XoxF1 or its D320A variant, we show that Asp 320 is needed for in vivo catalytic function, in vitro activity, and La 3+ coordination. XoxF1 and XoxF1 D320A, when produced in the absence of La 3+ , coordinated Ca 2+ but exhibited little or no catalytic activity. We also generated the parallel substitution in ExaF to produce ExaF D319S and found that this variant loses the capacity for efficient ethanol oxidation with La 3+ . These results provide evidence that a Ln 3+ -coordinating aspartate is essential for the enzymatic functions of XoxF MDHs and ExaF EDHs, supporting the notion that sequences of these enzymes, and the genes that encode them, are markers for Ln 3+ metabolism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Label-free affinity screening, design and synthesis of inhibitors targeting the Mycobacterium tuberculosis L-alanine dehydrogenase

The ability of Mycobacterium tuberculosis (Mtb) to persist in its host may enable an evolutionary advantage for drug resistant variants to emerge. A potential strategy to prevent persistence and gain drug efficacy is to directly target the activity of enzymes that are crucial for persistence. We present a method for expedited discovery and structure-based design of lead compounds by targeting the hypoxia-associated enzyme L-alanine dehydrogenase (AlaDH). Biochemical and structural analyses of AlaDH confirmed binding of nucleoside derivatives and showed a site adjacent to the nucleoside binding pocket that can confer specificity to putative inhibitors. Using a combination of dye-ligand affinity chromatography, enzyme kinetics and protein crystallographic studies, we show the development and validation of drug prototypes. Crystal structures of AlaDH-inhibitor complexes with variations at the N6 position of the adenyl-moiety of the inhibitor provide insight into the molecular basis for the specificity of these compounds. We describe a drug-designing pipeline that aims to block Mtb to proliferate upon re-oxygenation by specifically blocking NAD accessibility to AlaDH. The collective approach to drug discovery was further evaluated through in silico analyses providing additional insight into an efficient drug development strategy that can be further assessed with the incorporation of in vivo studies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Structural characterization of ligand binding and pH-specific enzymatic activity of mouse Acidic Mammalian Chitinase

Chitin is an abundant biopolymer and pathogen-associated molecular pattern that stimulates a host innate immune response. Mammals express chitin-binding and chitin-degrading proteins to remove chitin from the body. One of these proteins, Acidic Mammalian Chitinase (AMCase), is an enzyme known for its ability to function under acidic conditions in the stomach but is also active in tissues with more neutral pHs, such as the lung. Here, we used a combination of biochemical, structural, and computational modeling approaches to examine how the mouse homolog (mAMCase) can act in both acidic and neutral environments. We measured kinetic properties of mAMCase activity across a broad pH range, quantifying its unusual dual activity optima at pH 2 and 7. We also solved high-resolution crystal structures of mAMCase in complex with oligomeric GlcNAcn, the building block of chitin, where we identified extensive conformational ligand heterogeneity. Leveraging these data, we conducted molecular dynamics simulations that suggest how a key catalytic residue could be protonated via distinct mechanisms in each of the two environmental pH ranges. These results integrate structural, biochemical, and computational approaches to deliver a more complete understanding of the catalytic mechanism governing mAMCase activity at different pH. Engineering proteins with tunable pH optima may provide new opportunities to develop improved enzyme variants, including AMCase, for therapeutic purposes in chitin degradation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2018

NASA's Space Launch System Moves into Testing and Integration

NASA's Space Launch System (SLS) has moved from design and manufacturing into testing and integration for its first flight in fiscal year 2020. In 2017, the NASA/industry team completed manufacturing of all major structural elements for the launch vehicle for Exploration Mission-1 (EM-1). This work included shipping the first major flight hardware element to the launch site. Current work is focused on the initial Block 1 variant of SLS, capable of launching more than 70 metric tons (t) to low Earth orbit (LEO). As the needs of the nation's deep space exploration program grow, SLS performance is designed to evolve to a payload mass of 130 t to LEO and up to 45 metric tons (t) to trans-lunar injection (TLI). The advantages of this mass - as well as volume - are critical to the entire exploration architecture for deep space exploration. They translate to greater capability, greater infrastructure and operational simplicity, less overall mission risk, and opportunities to accomplish unprecedented exploration and discovery.

Honeycutt, John↗

DOE OSTI2026

Rational Design of Lanmodulin Variants for Size-Based Selectivity of Individual Rare Earth Elements

Rare earth elements (REEs) are essential to modern technologies, yet their high physical and chemical similarity makes separation of individual REEs difficult and environmentally taxing. Metalloproteins offer a promising alternative for selective REE binding, as they tend to have high metal ion affinity and specificity. Lanmodulin (LanM), in particular, has arisen as a potential candidate for REE separation as it exhibits picomolar affinity for elements in the REE family. Prior work has shown that the single point mutation D9N can shift LanM’s preference away from lanthanides toward actinides, motivating efforts to tune selectivity of LanM through targeted mutagenesis. Here, we tested the hypothesis that introducing selective aspartic acid to glutamic acid substitutions in the metal coordinating EF hands of LanM would impose steric constraints that would drive LanM affinity away from larger ions, such as La3+, to smaller ions, such as Y3+. To test this hypothesis, a combination of computational and experimental approaches were employed to evaluate the signal mutations LanM D5E and LanM D3E and the double mutants LanM D1ED5E and LanM D3ED9E. Surprisingly, increasing the number of mutations within the metal center did not enhance affinity for smaller REEs, or decrease affinity for larger ions. Only the single point mutation LanM D5E weakened La3+ binding by one order of magnitude relative to LanM wild type (WT), and pairing it with a second mutation to produce LanM D1ED5E drove La3+ affinity to be stronger than that seen for LanM WT. The D3E mutation alone prevented proper expression and folding, but paring it with D9E to produce LanM D3ED9E rescued expression and yielded La3+ affinities comparable to LanM WT. All variants that expressed (LanM D5E, LanM D1ED5E, LanM D3ED9E) displayed Y3+ affinities comparable to LanM WT. Overall, these results highlight the tunability of LanM’s metal-binding environment but also expose current limitations in predicting structural responses to point mutations within a protein sequence. This work establishes a foundation that can be used for refining computational and experimental strategies to engineer metalloproteins with tailored REE selectivity.

Close, Emily [Pacific Northwest National Laborator↗

DOE OSTI2022

Land-based wind turbines with flexible rail-transportable blades – Part 2: 3D finite element design optimization of the rotor blades

Abstract. Increasing growth in land-based wind turbine blades to enable higher machine capacities and capacity factors is creating challenges in design, manufacturing, logistics, and operation. Enabling further blade growth will require technology innovation. An emerging solution to overcome logistics constraints is to segment the blades spanwise and chordwise, which is effective, but the additional field-assembled joints result in added mass and loads, as well as increased reliability concerns in operation. An alternative to this methodology is to design slender flexible blades that can be shipped on rail lines by flexing during transport. However, the increased flexibility is challenging to accommodate with a typical glass-fiber, upwind design. In a two-part paper series, several design options are evaluated to enable slender flexible blades: downwind machines, optimized carbon fiber, and active aerodynamic controls. Part 1 presents the system-level optimization of the rotor variants as compared to conventional and segmented baselines, with a low-fidelity representation of the blades. The present work, Part 2, supplements the system-level optimization in Part 1 with high-fidelity blade structural optimization to ensure that the designs are at feasible optima with respect to material strength and fatigue limits, as well as global stability and structural dynamics constraints. To accommodate the requirements of the design process, a new version of the Numerical Manufacturing And Design (NuMAD) code has been developed and released. The code now supports laminate-level blade optimization and an interface to the International Energy Agency Wind Task 37 blade ontology. Transporting long, flexible blades via controlled flapwise bending is found to be a viable approach for blades of up to 100 m. The results confirm that blade mass can be substantially reduced by going either to a downwind design or to a highly coned and tilted upwind design. A discussion of active and inactive constraints consisting of material rupture, fatigue damage, buckling, deflection, and resonant frequencies is presented. An analysis of driving load cases revealed that the downwind designs are dominated by loads from sudden, abrupt events like gusts rather than fatigue. Finally, an analysis of carbon fiber spar caps for downwind machines finds that, compared to typical carbon fibers, the use of a new heavy-tow carbon fiber in the spar caps is found to yield between 9 % and 13 % cost savings.

17 WIND ENERGY↗

NASA NTRS1988

Polymer powder prepregging: Scoping study

Early on, it was found that NEAT LARC-TPI thermoplastic polyimide powder behaved elastoplastically at pressures to 20 ksi and temperatures to 260 degrees celcius (below MP). At high resin assay, resin powder could be continuously cold-flowed around individual carbon fibers in a metal rolling mill. At low resin assay (2:1, C:TPI), fiber breakage was prohibitive. Thus, although processing of TPI below MP would be quite unique, it appears that the polymer must be melted and flowed to produce low resin assay prepreg. Fiber tow was spread to 75 mm using a venturi slot tunnel. This allowed intimate powder/fiber interaction. Two techniques were examined for getting room temperature powder onto the room temperature fiber surface. Electrostatic powder coating allows the charged powder to cling tenaciously to the fiber, even while heated with a hot air gun to above its melt temperature. A variant of the wet slurry coating process was also explored. The carbon fibers are first wetted with water. Then dry powder is sprinkled onto the wet tow and doctor-rolled between the fibers. The wet structure is then taken onto a heated roll, with hot air guns drying and sinter-melting the powder onto the fiber surfaces. In both cases SEM shows individual fibers coated with powder particles that have melted in place and flowed along the fiber surface via surface tension.

Throne, James L.↗

NASA NTRS1991

Experiments with conjugate gradient algorithms for homotopy curve tracking

There are algorithms for finding zeros or fixed points of nonlinear systems of equations that are globally convergent for almost all starting points, i.e., with probability one. The essence of all such algorithms is the construction of an appropriate homotopy map and then tracking some smooth curve in the zero set of this homotopy map. HOMPACK is a mathematical software package implementing globally convergent homotopy algorithms with three different techniques for tracking a homotopy zero curve, and has separate routines for dense and sparse Jacobian matrices. The HOMPACK algorithms for sparse Jacobian matrices use a preconditioned conjugate gradient algorithm for the computation of the kernel of the homotopy Jacobian matrix, a required linear algebra step for homotopy curve tracking. Here, variants of the conjugate gradient algorithm are implemented in the context of homotopy curve tracking and compared with Craig's preconditioned conjugate gradient method used in HOMPACK. The test problems used include actual large scale, sparse structural mechanics problems.

Irani, Kashmira M.↗