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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.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

IsoForma: An R Package for Quantifying and Visualizing Positional Isomers in Top-Down LC-MS/MS Data

Proteoforms, the different forms of a protein with sequence variations including post-translational modifications (PTMs), execute vital functions in biological systems such as cell signaling and epigenetic regulation. Precisely defining the stoichiometry of PTMs has been challenging because, in the widely used bottom-up proteomics methods, the detection occurs at the peptide level and thus the link between peptides and their specific modification site is lost, resulting in proteoform ambiguity. Advances in top-down mass spectrometry (MS) technology have permitted the direct characterization of intact proteoforms and their exact number of modification sites, allowing for the relative quantification of positional isomers (PI). Proteins with positional isomers refers to proteoforms with identical total mass and set of modifications but varying PTM site combinations. The relative abundance of PI can be estimated by matching proteoform-specific fragment ions to top-down tandem MS (MS2) data to localize and quantify modifications. However, current approaches heavily rely on manual annotation. Here, we present IsoForma, an open-source R package for relative quantification of PI within a single tool. We benchmarked IsoForma’s performance against two existing workflows and highlight the similarity of the results and improvements in speed. Overall, IsoForma provides a streamlined process, reduces the time of conducting isoform-based analyses, and offers an essential framework for developing customized proteoform analysis workflows. Finally, the software is open source and available at https://github.com/EMSL-Computing/isoforma-lib.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Synthetic Ligand Selection Affects Stoichiometry, Carrier Dynamics, and Trapping in CuInSe 2 Nanocrystals

CuInSe 2 nanocrystals exhibit tunable near-infrared bandgaps that bolster utility in photovoltaic applications as well as offer potential as substitutes for more-toxic Cd- and Pb-based semiconductor compositions. However, they can present a variety of defect states as well as unusual photophysics. In this work, we examine the effects of ligand composition (oleylamine, diphenylphosphine, and tributylphosphine) on carrier dynamics in these materials. Via spectroscopic measurements such as photoluminescence and transient absorption, we find that ligands present during the synthesis of CuInSe 2 nanocrystals impart non-radiative electronic states which compete with radiative recombination and give rise to low photoluminescence quantum yields. We characterize the nature of these defect states (hole vs. electron traps) and investigate whether they exist at the surface or interior of the nanocrystals. Carrier lifetimes are highly dependent on ligand identity where oleylamine-capped nanocrystals exhibit rapid trapping (< 20 ps) followed by diphenylphosphine (< 500 ps) and finally tributylphosphine (> 2 ns). A majority of carrier population localizes at indium copper antisites (electrons), copper vacancies (holes), or surface traps (electrons and/or holes), all of which are non-emissive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Bridging Structure, Magnetism, and Disorder in Iron-Intercalated Niobium Diselenide, Fe x NbSe 2 , below x = 0.25

Transition-metal dichalcogenides (TMDs) intercalated with magnetic ions serve as a promising materials platform for developing next-generation, spin-based electronic technologies. In these materials, one can access a rich magnetic phase space depending on the choice of intercalant, host lattice, and relative stoichiometry. The distribution of these intercalant ions across given crystals, however, is less well defined–particularly away from ideal packing stoichiometries–and a convenient probe to assess potential longer-range ordering of intercalants is lacking. Here, we demonstrate that confocal Raman spectroscopy is a powerful tool for mapping the onset of intercalant superlattice formation in Fe-intercalated NbSe 2 (Fe x NbSe 2 ) for 0.14 ≤ x < 0.25. We use single-crystal X-ray diffraction to confirm the presence of longer-range intercalant superstructure and employ polarization-, temperature-, and magnetic field-dependent Raman measurements to examine both the symmetry of emergent phonon modes in the intercalated material and potential magnetoelastic coupling. Magnetometry measurements further indicate a correlation between the onset of magnetic ordering and the relative degree of intercalant superlattice formation. These results show Raman spectroscopy to be an expedient, local probe for mapping intercalant ordering in this class of magnetic materials.

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

Evaluating the effects of structural disorder on the magnetic properties of Nd 2 Zr 2 O 7

Motivated by the variation in reported lattice parameters of floating-zone-grown Nd 2 Zr 2 O 7 crystals, we have performed a detailed study of the relationship between synthesis environment, structural disorder, and magnetic properties. Using a combination of polycrystalline standards, electron-probe microanalysis, and scattering techniques, we show that crystals grown under atmospheric conditions have a reduced lattice parameter relative to pristine polycrystalline powders due to occupation of the Nd site by excess Zr (i.e., negative stuffing). In contrast, crystals grown under high-pressure Ar are nearly stoichiometric with an average lattice parameter approaching the polycrystalline value. While minimal disorder of the oxygen sublattices is observed on the scale of the average structure, neutron pair-distribution function analysis indicates a highly local disorder of the oxygen coordination, which is only weakly dependent on growth environment. Most importantly, our magnetization, heat capacity, and single-crystal neutron scattering data show that the magnetic properties of crystals grown under high-pressure Ar match closely with those of stoichiometric powders. Neutron scattering measurements reveal that the signature of magnetic moment fragmentation—the coexistence of all-in-all-out (AIAO) magnetic Bragg peaks and diffuse pinch-point scattering due to spin-ice correlations–persists in these nearly stoichiometric crystals. However, in addition to an increased AIAO transition temperature, the diffuse signal is seemingly stabilized and remains nearly unchanged upon warming to 800 mK. This behavior indicates that both the AIAO magnetic order and spin-ice correlations are sensitive to deviations of the Nd stoichiometry.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Single Nanoflake Photoelectrochemistry Reveals Intrananoflake Doping Heterogeneity That Explains Ensemble-Level Photoelectrochemical Behavior

Transition metal dichalcogenide (TMD) nanoflake thin films are attractive electrode materials for photoelectrochemical (PEC) solar energy conversion and sensing applications, but their photocurrent quantum yields are generally lower than those of bulk TMD electrodes. The poor PEC performance has been primarily attributed to enhanced charge carrier recombination at exposed defect and edge sites introduced by the exfoliation process. Here, a single nanoflake PEC approach reveals how an alternative effect, doping heterogeneity, limits ensemble-level PEC performance. Photocurrent mapping and local photocurrent–potential (i–E) measurements of MoS 2 nanoflakes exfoliated from naturally occurring bulk crystals revealed the presence of n- and p-type domains within the same nanoflake. Interestingly, the n- and p-type domains in the natural MoS 2 nanoflakes were equally efficient for iodide oxidation and tri-iodide reduction (IQE values exceed 80%). At the single domain-level, the natural MoS 2 nanoflakes were nearly as efficient as nanoflakes exfoliated from synthetic n-type MoS 2 crystals. Single domain-level i–E measurements explain why natural MoS 2 nanoflakes exhibit an n-type to p-type photocurrent switching effect in ensemble-level measurements: the n- and p-type diode currents from individual domains oppose each other upon illuminating the entire nanoflake, resulting in zero photocurrent at the switching potential. Furthermore, the doping heterogeneity effect is likely due to nonideal stoichiometry, where p-type domains are S-rich according to XPS measurements. Although this doping heterogeneity effect limits photoanode or photocathode performance, these findings open the possibility to synthesize efficient TMD nanoflake photocatalysts with well-defined lateral p- and n-type domains for enhanced charge separation.

14 SOLAR ENERGY↗
DOE OSTI2023

Highly Nonstoichiometric YAG Ceramics with Modified Luminescence Properties

Abstract Y 3 Al 5 O 12 (YAG) is a widely used phosphor host. Its optical properties are controlled by chemical substitution at its YO 8 or AlO 6 /AlO 4 sublattices, with emission wavelengths defined by rare‐earth and transition‐metal dopants that have been explored extensively. Nonstoichiometric compositions Y 3+x Al 5‐x O 12 ( x ≠ 0) may offer a route to new emission wavelengths by distributing dopants over two or more sublattices simultaneously, producing new local coordination environments for the activator ions. However, YAG typically behaves as a line phase, and such compositions are therefore challenging to synthesize. Here, a series of highly nonstoichiometric Y 3+x Al 5‐x O 12 with 0 ≤ x ≤ 0.40 is reported, corresponding to ≤20% of the AlO 6 sublattice substituted by Y 3+ , synthesized by advanced melt‐quenching techniques. This impacts the up‐conversion luminescence of Yb 3+ /Er 3+ ‐doped systems, whose yellow‐green emission differs from the red‐orange emission of their stoichiometric counterparts. In contrast, the YAG:Ce 3+ system has a different structural response to nonstoichiometry and its down‐conversion emission is only weakly affected. Analogous highly nonstoichiometric systems should be obtainable for a range of garnet materials, demonstrated here by the synthesis of Gd 3.2 Al 4.8 O 12 and Gd 3.2 Ga 4.8 O 12 . This opens pathways to property tuning by control of host stoichiometry, and the prospect of improved performance or new applications for garnet‐type materials.

Chemistry↗
DOE OSTI2020

Does the leaf economic spectrum hold within plant functional types? A Bayesian multivariate trait meta-analysis

The leaf economic spectrum is a widely-studied axis of plant trait variability that defines a trade-off between leaf longevity and productivity. While this has been investigated at the global scale, where it is robust, and at local scales, where deviations from it are common, it has received less attention at the intermediate scale of PFTs. We investigated whether global leaf economic relationships are also present within the scale of plant functional types (PFTs) commonly used by Earth System models, and the extent to which this global-PFT hierarchy can be used to constrain trait estimates. We developed a hierarchical multivariate Bayesian model that assumes separate means and covariance structures within and across PFTs and fit this model to seven leaf traits from the TRY database related to leaf longevity, morphology, biochemistry, and photosynthetic metabolism. Although patterns of trait covariation were generally consistent with the leaf economic spectrum, we found three approximate tiers to this consistency. Relationships among morphological and biochemical traits (SLA, N, P) were the most robust within and across PFTs, suggesting that covariation in these traits is driven by universal leaf construction trade-offs and stoichiometry. Relationships among metabolic traits (R_d, V_{c,max}, J_max) were slightly less consistent, reflecting in part their much sparser sampling (especially for high-latitude PFTs), but also pointing to more flexible plasticity in plant metabolistm. Finally, relationships involving leaf lifespan were the least consistent, indicating that leaf economic relationships related to leaf lifespan are dominated by across-PFT differences and that within-PFT variation in leaf lifespan is more complex and idiosyncratic. Across all traits, these covariance were an important source of information, as evidenced by the improved imputation accuracy and reduced predictive uncertainty in multivariate models compared to univariate models. Ultimately, our study reaffirms the value of studying not just individual traits but the multivariate trait space and the utility of hierarchical modeling for studying the scale dependence of trait relationships.

biodiversity, ecological modeling, ecology, leaf b↗
DOE OSTI2025

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Structural modulation, physical properties, and electronic band structure of the kagome metal UCr 6 ⁢Ge 6

The chemical flexibility of the 𝑅⁢𝑀 6 ⁢𝑋 6 stoichiometry, where an 𝑓-block element is intercalated in the CoSn structure type, allows for the tuning of flatbands associated with kagome lattices to the Fermi level and for emergent phenomena due to interactions between the 𝑓- and 𝑑-electron lattices. Yet, 5⁢𝑓 members of the “166” compounds are underrepresented compared with 4⁢𝑓 members. In this work, we report single-crystal growth of UCr 6 ⁢Ge 6 , which crystallizes in a monoclinically distorted Y 0.5⁢ Co 3 ⁢Ge 3 -type structure. The real-space character of the modulation, which is unique within the 𝑅⁢𝑀 6 ⁢𝑋 6 family, is approximated by a 3×1×2 supercell of the average monoclinic cell. The compound has kagome-lattice flatbands near the Fermi level and a moderately enhanced electronic heat capacity, as evidenced by its low-temperature Sommerfeld coefficient (𝛾=86.5 mJ mol −1 K −2 ) paired with band structure calculations. The small, isotropic magnetization and featureless resistivity of UCr 6 ⁢Ge 6 suggest itinerant uranium 5⁢𝑓 electrons and Pauli paramagnetism. Angle-resolved photoemission spectroscopy results provide evidence for uranium 5⁢𝑓 weight at the Fermi level and for a flatband near the Fermi level associated with the chromium 3⁢𝑑 kagome lattice. The isotropic magnetic behavior of the uranium 5⁢𝑓 electrons starkly contrasts with localized behavior in other uranium 166 compounds, highlighting the high tunability of the magnetic ground state across the material family.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Experimental Partitioning of Cr(3+) and Sc(3+) into Olivine: Mechanisms and Implications

Olivine (Mg, Fe)Si2O4 does not, by stoichiometry, accept cations such as Sc(3+) or Cr(3+). However, the partition coefficients of Sc and Cr between olivine and liquid are significant 0.2-1.0. We have measured Cr(3+) partition coefficients of near unity and have grown olivines with nearly 3 wt.% Sc2O3. Therefore, there must be a simple means of charge balancing 3+ ions in a crystal structure that was obviously not designed to receive other than 2+ ions on the olivine M sites. The simplest explanation is that two 3+ ions enter the olivine structure by displacing three 2+ ions and creating an M site vacancy. Even this explanation has difficulties. For minor elements in our experiments (~1 wt.%) the odds of a minor element 3+ ion finding a second 3+ for charge balance are of the order of 100:1 against. Because of the reducing conditions of our experiments, Fe(3+) will not suffice; and Al(3+) is not in sufficient quantity in olivine for charge balance. Therefore, Cr or Sc must, in effect, charge balance itself. For true trace elements, the problem is compounded many times. For an ion at the 10 ppm level the chances of finding a second (for example) Sc ion is approx.10(exp 5):1 against. Of course, any other 3+ ion would suffice but comparisons between percent level doping experiments and trace level partitioning indicate that Henry s law is obeyed. This implies that the same substitution mechanism occurs at both the percent and tens of ppm levels. There are two simple solutions to this problem: (i) The electrical conductivity of olivine is such that charge balance need not be local. This requires substantial domains within the olivine crystal in electrical contact by migration of vacancies or electronic defects. (ii) The 3+ cation brings along its own charge-balancing ion because it existed as a dimer in the silicate liquid. Olivine is not a true insulator but is actually a p-type semiconductor. Even so, electrical communication by this means is unlikely over the tens or hundreds of unit cells that would be required for charge balance to be local. Therefore, we cautiously favor the idea that melt speciation is the means by which 3+ ions enter the olivine structure. Possibly this model might be tested by in situ XAFS measurements or by molecular dynamical calculations.

Jones, John↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2021

Characterization of cellular oxidative stress response by stoichiometric redox proteomics

The thiol redox proteome refers to all proteins whose cysteine thiols are subjected to various redox-dependent posttranslational modifications (PTMs) including S-glutathionylation (SSG), S-nitrosylation (SNO), S-sulfenylation (SOH), and S-sulfhydration (SSH). These modifications can impact various aspects of protein function, including activity, binding, conformation, localization, and interactions with other molecules. It is highly desirable to have robust redox proteomics methods that can provide global, site-specific, and stoichiometric quantification of redox PTMs in order to elucidate the complex redox landscape and identify novel redox regulators in signaling and regulation. Mass spectrometry-based redox proteomics has emerged as the primary platform for enabling the broad characterization of thiol PTMs in cells and tissues. Herein we review recent advances in MS-based redox proteomics approaches for quantitative profiling of redox PTMs in cells and tissues at physiological or oxidative stress conditions and highlight some recent applications using these enabling techniques. Considering the relative maturity of available methods, a primary emphasis will be on two types of modifications: 1) total oxidation (i.e., all reversible thiol modifications), the level of which represents the overall redox state, and 2) S-glutathionylation, a major form of reversible thiol oxidation. We also discuss the significance of stoichiometric measurements of thiol PTMs as well as future perspectives towards a better understanding of cellular redox regulatory networks in cells and tissues.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

AERoBOND Project Summary

Under NASA’s Convergent Aeronautics Solutions (CAS) project, the Adhesive-Free Bonding of Complex Composites (AERoBOND) project investigated off-stoichiometric epoxy polymers for fast, reliable assembly of epoxy matrix composite structures. The project goal was to demonstrate feasibility of the AERoBOND joining method by demonstrating mechanical properties greater than 80% of conventional co-cured materials while reducing structure weight by 1%. The project consisted of three convergent research areas: material and process development, systems analysis, and material and process modeling. Material and process development was the largest component of AERoBOND with approximately 6 FTE and 1WYE of support to formulate and characterize new resins, prepare carbon fiber prepregs, fabricate laminates, measure mechanical properties, analyze failure results, and select material and process improvements. The systems analysis activity estimated the potential reduction in part count and aircraft weight by comparing models of composite wing boxes with no fasteners (co-cured structure), fasteners in major joints (co-cured stringers), and fasteners in all joints. The materials and process modeling activity included a molecular model of the AERoBOND materials system to predict mechanical properties of resins with offset stoichiometry and a process model to predict the effect of resin formulation and processing conditions on the extent of mixing and degree of cure in a finished joint. As the number of airline passenger trips doubles in the next 20 years (IATA/Tourism Economics Air Passenger Forecasts, April 2019), the increased demand for new commercial aircraft is now the single greatest technical challenge to the airframe manufacturing industry. To meet efficiency requirements, new aircraft must be fabricated primarily from high performance structural composites, but manufacturing processes are inherently slow with the largest bottleneck attributed to assembly and installation of fasteners (NASA/TM–2019-220428). Manufactures of commercial transport aircraft are compelled to install more than 100,000 redundant fasteners into bonded joints to prevent failures due to unpredictable weak bonds. In structural adhesive bonds, the interface between adherend and adhesive is nearly two-dimensional making it susceptible to minute quantities of contamination, which can cause weak bonds. Currently, bond strength assessment is only possible through destructive testing (i.e., breaking the joint). For these reasons, regulatory organizations such as the Federal Aviation Administration (FAA) often require redundant load paths in secondary-bonded, primary-structures to alleviate concerns with bond performance. The AERoBOND process enables reflow of matrix resin during assembly to eliminate the material discontinuity at the interface, thereby eliminating the dependence of mechanical performance on interfacial adhesion. The AERoBOND joint is equivalent to the interlaminar region obtained during a co-cure process, so joint performance depends on the cohesive properties of the matrix resin. Conventional co-cured structures, although too costly and complex for large-scale manufacturing, are trusted by manufacturers and regulators, and are certified for flight with few or no redundant fasteners.Systems analysis performed on a composite wing model at the scale of a single-aisle commercial transport aircraft indicated that >20,000 redundant fasteners per wing could be eliminated by implementing the AERoBOND joining method. A total weight reduction of 15% was predicted in a wing box by eliminating fasteners and thinning components that must no longer support localized fastener loads and accommodate fastener dimensions. Interlaminar shear fracture toughness measured by the end-notched flexure test was greater than 1 kJ/m2 (nearly 140% of the co-cured benchmark property), which is greatly in excess of the project goals for mechanical properties. Testing was planned to measure interlaminar tensile fracture toughness as well as interlaminar tensile and shear strengths using the same AERoBOND configuration, but was delayed due to closure of LaRC facilities during the COVID-19 pandemic. The AERoBOND process model is partially validated and available for experimental use. It allows the user to input AERoBOND process parameters such as material composition, laminate configuration, and cure cycle to predict the final cure state of the AERoBOND joint. A preliminary, multi-scale material model was developed to predict AERoBOND joint mechanical properties (stiffness and strength) based on the cure state of the joint provided by the process model. The timing for transition of this technology within NASA is excellent as NASA initiates new enduring projects to address composites manufacturing rate challenges. AERoBOND technology is well suited to AAVP/AATT objectives for rapid manufacturing of a composite wing. A minimal effort (1 FTE/$15k procurement/0 WYE) is proposed in FY21 to continue a minor mechanical testing effort and maintain a SAA with ASX composites to develop commercial quality prepreg material. An RFI with the composites industry is suggested to quantify the technology gap between the current TRL and the TRL needed for transition to industry. A moderate effort [3-4 FTE/$150k/1 WYE (~$115k)] is proposed in FY22 for the “high rate composites manufacturing” project currently in planning. The partnership with ASX Composites will be expanded to produce material for sub-element/element-scale “panel-off” activities. Industry partnerships with airframe manufacturers is an expected component to explore damage tolerance and environmental stability. Further development of multi-scale modeling tools (process model, meso-scale model, and molecular model) is planned to enhance and deliver tools for rapid manufacturing infusion.

Frank Louis Palmieri↗