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DOE OSTI2019

Chlorine-36/beryllium-10 burial dating of alluvial fan sediments associated with the Mission Creek strand of the San Andreas Fault system, California, USA

We utilize cosmogenic-nuclide burial dating using the 36 Cl -in-K-feldspar / /10 Be -in-quartz pair in fluvially transported granitoid clasts to determine the age of alluvial sediment displaced by the Mission Creek strand of the San Andreas Fault in southern California. Due to the half-lives of 36 Cl and /10 Be are more different than those of the commonly used 26 Al$^{/10}$Be pair, 36 Cl /10 Be burial dating should be applicable to sediments in the range ca. 0.2–0.5 Ma, which is too young to be accurately dated with the 26 Al$^{/10}$Be pair, and should be more precise for Middle and Late Pleistocene sediments in general. However, using the 36 Cl$^{/10}$Be pair is more complex because the 36 Cl$^{/10}$Be production ratio varies with the chemical composition of each sample. We use 36 Cl$^{/10}$Be measurements in samples of granodiorite exposed at the surface at present to validate calculations of the 36 Cl$^{/10}$Be production ratio in this lithology, and then we apply this information to determine the burial age of alluvial clasts of the same lithology. This particular field area presents the additional obstacle to burial dating (which is not specific to the 36 Cl$^{/10}$Be pair, but would apply to any) that most buried alluvial clasts are derived from extremely rapidly eroding parts of the San Bernardino Mountains and have correspondingly extremely low nuclide concentrations, the majority of which most likely derive from nucleogenic (for 36 Cl ) and post-burial production. Even though this precludes accurate burial dating of many clasts, data from surface and subsurface samples with higher nuclide concentrations, originating from lower-erosion-rate source areas, show that the age of upper Cabezon Formation alluvium is 260 ka. This is consistent with stratigraphic age constraints as well as independent estimates of long-term fault slip rates, and it highlights the potential usefulness of the 36 Cl$^{/10}$Be pair for dating Upper and Middle Pleistocene clastic sediments.

58 GEOSCIENCES↗

DOE OSTI2025

Optimizing semi-hydrogenation of unsaturated hydrocarbons by electrolyte engineering approach

Electrochemical hydrogenation of unsaturated hydrocarbons, when powered by renewables, represents a unique opportunity to substitute current energy-intensive synthetic routes. Modulation of adsorption energies of the organic substrate and key intermediates of the reaction is critical for fine tuning of the yield, selectivity and kinetics of the reaction. Interestingly, mounting evidence exists regarding the role of electrolyte composition in the outcome of semi-hydrogenation reactions. Nevertheless, electrolyte optimization is a complex task, owing to its hybrid nature. Indeed, it is composed of water serving as a proton source, an organic solvent necessary to dissolve the organic substrate and a conducting salt. Herein, we demonstrate that varying conducting salt and organic solvent has a dramatic impact on the outcomes of semi-hydrogenation of alkynes. By varying salt and water concentrations, we demonstrate that water does not serve as a proton source, and instead addition of an acid is necessary. While increasing the acid concentration increases the yield of the reaction, at too large concentrations the hydrogen evolution reaction becomes predominant. Furthermore, by combining electrochemical measurements with spectroscopic techniques including Fourier transform infrared (FTIR) spectroscopy and small angle X-ray spectroscopy (SAXS), we demonstrate that the electrolyte solvation structure dramatically impacts the yield of the reaction. Organic solvents weakly interacting with water, including acetonitrile, form aqueous nanoheterogeneities that prevent the organic substrate from accessing the catalyst interface and thus lead to limited yields. Instead, solvents such as dimethylformamide form homogeneous mixtures with which all reactants can access the interface, leading to yields greater than 80% for optimized compositions.

Zhang, Rongyu↗

DOE OSTI2020

Controlling the corrosion resistance of multi-principal element alloys

Multi-principal element alloys (MPEAs) offer the possibility of many degrees of freedom in the choice of alloying elements to produce either single phase solid solutions or more complex multiphase microstructures. Large ranges of material properties have been observed for MPEAs and mastery of the selection of elements and their compositions can enable novel combinations of properties not possible in traditional alloys. From the aqueous corrosion perspective, optimization of phase stability, control of heterogeneities, passive film identity and its protectiveness, as well as substrate properties such as metal-metal bond strength and activation energy associated with dissolution, can all be controlling factors governed by alloy composition and structure. These factors can mediate the electrochemical reactions controlling spontaneous corrosion. The quest for superior properties based on well-informed element choice is suggested as a path forward guiding MPEA formulations for corrosion performance. However, gaps in fundamental knowledge exist regarding (a) the specific functions of each element, (b) the behavior of elements in unusual combinations, and (c) the formation of complex protective oxides. These issues currently hold back progress in optimization of corrosion properties.

Scully, John R.↗

DOE OSTI2018

Evolution Mechanism of Oxide Inclusions in Titanium-Stabilized AISI 443 Stainless Steel

The evolution mechanism of oxide inclusions in Ti-bearing AISI 443 stainless steel was investigated by industrial experiment and thermodynamic calculation. The chemical compositions of steel and the characteristics of inclusions in steel were analyzed. After the addition of Al, the main type of inclusions in molten steel was irregular MgO·Al{sub 2}O{sub 3} spinel. The MgO·Al{sub 2}O{sub 3} inclusions were modified to be spherical CaO-Al{sub 2}O{sub 3}-MgO inclusions after calcium treatment. Thermodynamic calculation results indicated that several ppm Ca could significantly expand the liquid oxide phase field and decrease the stability of spinel. After titanium addition, two types of inclusions were formed: spherical Al{sub 2}O{sub 3}-TiO{sub x} inclusions and complex CaO-TiO{sub x}-Al{sub 2}O{sub 3}-MgO inclusions. The compositions of steel after Ti addition were mostly located in Al{sub 2}O{sub 3}-TiO{sub x} stability phase field. Based on the characteristics of inclusions in steel and thermodynamic calculation, inclusions consisting of liquid and CaTiO{sub 3} were formed in molten steel with more than 10 ppm Ca during the Ti addition process. The evolution mechanism of oxide inclusions was discussed with the consideration of the initial calcium content before Ti addition.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Environmental Durability Assessment and Development of Subcomponent Test Methods for Advanced Materials in Marine Energy Applications

Marine energy developers are beginning to rely more heavily on advanced composite materials for their load-bearing structures. Understanding how these materials respond and degrade in harsh marine environments is a complex problem. Much research has been performed at smaller laboratory scales to understand the fundamental physical and chemical degradation mechanisms, but little structural testing research has been performed at larger scales to understand how these physical and chemical interactions scale and how they should be accounted for in the design process. The Advanced Materials project is a multilaboratory research collaboration that addresses these issues with the intention of reducing risks and barriers to marine energy developers wanting to adopt advanced composite materials. The National Laboratory of the Rockies has been playing a leading role in developing larger-scale testing infrastructure and test methods to validate complex numerical degradation models and standardize testing procedures to do so. This paper reviews past structural testing activities, how they have grown into current research activities, and how they will continue to evolve to directly address industry needs. This paper covers key research areas - large-scale water absorption and subsequent structural validation testing, qualification of bolted and adhesive connections, and combined submerged fatigue testing at increasing scales. It provides insights into the complex requirements for testing infrastructure and test method development to effectively qualify materials and certify marine energy structures for harsh marine environments. This research program paves the way for better guidance and standardization within the industry when adopting advanced composite materials.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Magnetic tunability in tetragonal Mn–Rh–Ir–Sn inverse Heusler compounds

Abstract Gaining control over magnetic structure has been an ongoing challenge in materials that form complex, nanoscale, and non-collinear magnetic configurations. Recently, it was predicted that tuning the ratio of the Dzyaloshinskii–Moriya interaction to the uniaxial magnetic anisotropy in tetragonal inverse Heuslers through changes in composition could allow a range of interesting magnetic states to be accessed, from simple ferrimagnetism, to helical and antiskyrmionic phases. Here, we show tunability of the magnetic phase behavior in the Mn–Rh–Sn system through Ir substitution on the Rh substructure. Iridium substitution correlates to an increase in the strength of ferromagnetic exchange couplings, at the expense of antiferromagnetic exchange couplings. However, we do not observe the complex non-collinear magnetic phases proposed previously, likely due to the extremely narrow composition window where these phases are predicted to form in a bulk sample. This work highlights the sensitivity of complex magnetic structures to stoichiometry, which makes them difficult to discover empirically.

Physics↗

DOE OSTI2025

genomeocean: a pretrained microbial genome foundational model (genomeoceanLLM) v1.0

We present Genomeocean, a foundational genome language model that represents the microbial genome sequences from complex environmental samples. By training on a large, diverse metagenomic dataset, Genomeocean learns species-specific sequence composition and can generate long, realistic open reading frames (ORFs). Our model employs a Byte-pair-encoding (BPE) tokenization strategy, allowing it to efficiently process large genomic datasets and generate long sequences up to 50kb. We demonstrate that fine-tuning Genomeocean can generate novel gene clusters encoding biosynthetic pathways, showcasing its ability to model both fundamental and complex biological processes. Our work establishes Genomeocean as a powerful tool for understanding microbial genome biology and paves the way for its application in a range of fields, from synthetic biology to microbiome research.

Wang, Zhong [Lawrence Berkeley National Laboratory↗

DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats: Integration of Additive Manufacturing and Reinforced Polymer Composite

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

A Novel Manufacturing Process of Lightweight Automotive Seats (Integration of Additive Manufacturing and Reinforced Polymer Composite)

Lightweight automotive seats offer multiple benefits to original equipment manufacturers in terms of cost savings from various aspects, including less material usage, more integrated processes, and compliance with Corporate Average Fuel Economy Standards. Original equipment manufacturers have been focusing on innovative ways to produce light weight automotive seats. The commercially available automotive seats are currently made of multiple metal components combined through welding and fasteners. The use of additive manufacturing and composite structures is particularly useful for light weighting the automotive components. Additive manufacturing (AM) offers multiple advantages over traditional manufacturing processes such as freedom of design thereby enabling complex structural geometries, mass customization and waste minimization, and control over the fiber alignment through deposition in a predetermined pattern. Combining metal inserts with polymer composites through a novel manufacturing process allows design of lightweight and high-performance materials for automotive components. However, fabricating these metal polymer composite structures through traditional manufacturing processes limits their mechanical properties due to limited design freedom, lack of control over fiber orientation in composite parts, and poor interfacial bonding between the constituent materials. It is essential to develop a novel manufacturing process to enable high throughput production of lightweight automotive seats using metal and polymer composites. As such it is important to design the automotive seat suitable for manufacturing via this process and perform mechanical characterization on various subcomponents of the seat to ensure that the design and performance requirements provided by the auto manufacturer are met. The aim of this project is to develop a novel manufacturing technique to produce lightweight automotive seat by combining AM with conventional manufacturing processes. The car seat back panel will be designed via topology optimization and numerical simulations to minimize the overall weight while ensuring it meets all the performance requirements. The optimization of the seat back structure will be based on computational stress analysis to maximize the stiffness and minimize the weight. Materials currently used by Ford Motor Company will be adopted for a few subcomponents while the in-house composite materials will be used for the rest of the seat back. The composite and metallic materials will be tested to determine their mechanical properties as these are necessary for simulations. A novel manufacturing process will be developed to integrate AM metal inserts with discontinuous reinforced composite through large scale additive manufacturing and compression overmolding processes. The developed manufacturing technique will be used to fabricated various subcomponents suitable for the seat back design and mechanically tested to determine their properties. The manufacturing of the lightweight seat back design through this process involves integrated AM metal inserts with the composite structure for recliner connection. The manufacturing of the entire seat back which is lightweight through the novel manufacturing process will be discussed. The performance of the designed seat back will be investigated through numerical simulations and shown to meet all the requirements provided by the auto manufacturer. The final goal of developing a novel manufacturing process for lightweight automotive seats is met through design optimization of seat back, manufacturing of subcomponents, mechanical characterization, and validation through numerical simulations. The routes to achieve the final goal of the project and the depth in which they were investigated changed throughout the project due to personnel changes and the COVID-19 pandemic. The project resulted in the development of a novel manufacturing process to integrate metal inserts with tailored polymer composite preforms through overmolding. Leveraging this proven manufacturing process, a lightweight seat back was designed through topology optimization and numerical simulations. The designed seat back uses AM metal inserts and compression overmolding of tailored polymer composite preforms obtained via large scale additive manufacturing. The metal polymer composite structures fabricated through this process exhibited enhancement in stiffness and improved ductility upon testing. Overall, the project provided an alternative design and manufacturing technique for automotive seat back that enables weight saving while meeting the safety and performance requirements.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A Graphics Processing Unit–Based, Industrial Grade Compositional Reservoir Simulator

Summary Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs has yet to emerge, and the question remains as to whether the benefits observed in black-oil simulation persist with a more complex fluid description. We present a positive answer to this question through the extension of a commercial GPU-based black-oil simulator to include a compositional description based on standard cubic equations of state (EOSs). We describe the motivations for the selected nonlinear formulation, including the choice of primary variables and iteration scheme, and support for both fully implicit methods (FIMs) and adaptive implicit methods (AIMs). We then present performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of runtime and memory scaling with respect to the number of hydrocarbon components and model size, as well as the number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth. NOTE: This paper is also published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Engineering↗

DOE OSTI2023

Compositional Modifications to Alter and Suppress Laves Phases in Al x CrMoTa y Ti Alloys

The development of refractory complex concentrated alloys in the Al–Cr–Mo–Ta–Ti alloy system is reported. Alloys with modified Al and Ta concentrations are designed using CALPHAD tools and produced via arc melting and characterized in both as-cast and annealed forms. Properties of the alloys, nature of the microstructures, and phase transformation behavior are described via X-ray diffraction, microstructural characterization, microhardness, and differential scanning calorimetry. Two alloys, namely, Al 0.25 CrMoTa 0.8 Ti and Al 0.75 CrMoTa 0.8 Ti, are represented by a body-centered-cubic matrix phase after annealing, along with a secondary Cr–Ta Laves phase of the C15 and C14 polytypes, respectively. In as-cast and annealed forms, the Al 0.75 CrMoTa 0.45 Ti alloy comprises a single-bcc phase. Microhardness of the Laves phase containing alloys demonstrates susceptibility to cracking, whereas the Al 0.75 CrMoTa 0.45 Ti alloy displays high specific hardness, signs of ductility as evidenced by slip traces near indentations, and minimal scatter of hardness values.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Structural complexity biases vegetation greenness measures

Vegetation ‘greenness’ characterized by spectral vegetation indices (VIs) is an integrative measure of vegetation leaf abundance, biochemical properties and pigment composition. Surprisingly, satellite observations reveal that several major VIs over the US Corn Belt are higher than those over the Amazon rainforest, despite the forests having a greater leaf area. This contradicting pattern underscores the pressing need to understand the underlying drivers and their impacts to prevent misinterpretations. Here we show that macroscale shadows cast by complex forest structures result in lower greenness measures compared with those cast by structurally simple and homogeneous crops. The shadow-induced contradictory pattern of VIs is inevitable because most Earth-observing satellites do not view the Earth in the solar direction and thus view shadows due to the sun–sensor geometry. The shadow impacts have important implications for the interpretation of VIs and solar-induced chlorophyll fluorescence as measures of global vegetation changes. For instance, a land-conversion process from forests to crops over the Amazon shows notable increases in VIs despite a decrease in leaf area. In conclusion, our findings highlight the importance of considering shadow impacts to accurately interpret remotely sensed VIs and solar-induced chlorophyll fluorescence for assessing global vegetation and its changes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Advanced and functional composite materials via additive manufacturing: Trends and perspectives

Additive manufacturing (AM) has many advantages over conventional subtractive manufacturing methods. The cost-effective AM allows for precise fabrication of complex structures with less material waste, making it a popular manufacturing process in many applications. The recent development of AM materials has advanced significantly. Further, by precisely controlling material distribution and microstructural features, AM facilitates the creation of new composites with specific requirements. AM techniques have contributed considerably to integrating unique functionalities for various applications. This review emphasizes multiple categories of materials, including metal alloys, polymer-based composites, and sustainable composites, as well as applications of sensing materials and strategies and emerging artificial intelligence and machine learning.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗

DOE OSTI2025

Simulating Meson Scattering on Spin Quantum Simulators

Studying high-energy collisions of composite particles, such as hadrons and nuclei, is an outstanding goal for quantum simulators. However, preparation of hadronic wave packets has posed a significant challenge, due to the complexity of hadrons and the precise structure of wave packets. This has limited demonstrations of hadron scattering on quantum simulators to date. Observations of confinement and composite excitations in quantum spin systems have opened up the possibility to explore scattering dynamics in spin models. In this article, we develop two methods to create entangled spin states corresponding to wave packets of composite particles in analog quantum simulators of Ising spin Hamiltonians. One wave-packet preparation method uses the blockade effect enabled by beyond-nearest-neighbor Ising spin interactions. The other method utilizes a quantum-bus-mediated exchange, such as the native spin-phonon coupling in trapped-ion arrays. With a focus on trapped-ion simulators, we numerically benchmark both methods and show that high-fidelity wave packets can be achieved in near-term experiments. We numerically study scattering of wave packets for experimentally realizable parameters in the Ising model and find inelastic-scattering regimes, corresponding to particle production in the scattering event, with prominent and distinct experimental signals. Our proposal, therefore, demonstrates the potential of observing inelastic scattering in near-term quantum simulators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Interplay between Composition, Electronic Structure, Disorder, and Doping due to Dual Sublattice Mixing in Nonequilibrium Synthesis of ZnSnN 2 :O

We report the opportunity for enhanced functional properties in semiconductor solid solutions has attracted vast scientific interest for a variety of novel applications. However, the functional versatility originating from the additional degrees of freedom due to atomic composition and ordering comes along with new challenges in characterization and modeling. Developing predictive synthesis-structure-property relationships is prerequisite for effective materials design strategies. Here, a first-principles based model for property prediction in such complex semiconductor materials is presented. This framework incorporates nonequilibrium synthesis, dopants and defects, and the change of the electronic structure with composition and short range order. This approach is applied to ZnSnN 2 (ZTN) which has attracted recent interest for photovoltaics. The unintentional oxygen incorporation and its correlation with the cation stoichiometry leads to the formation of a solid solution with dual sublattice mixing. A nonmonotonic doping behavior as a function of the composition is uncovered. Finally, the degenerate doping of near-stoichiometric ZTN, which is detrimental for potential applications, can be lowered into the 10 17 cm -3 range in highly off-stoichiometric material, in quantitative agreement with experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Orthogonal luminescence lifetime encoding by intermetallic energy transfer in heterometallic rare-earth MOFs

Lifetime-encoded materials are particularly attractive as optical tags, however examples are rare and hindered in practical application by complex interrogation methods. Here, we demonstrate a design strategy towards multiplexed, lifetime-encoded tags via engineering intermetallic energy transfer in a family of heterometallic rare-earth metal-organic frameworks (MOFs). The MOFs are derived from a combination of a high-energy donor (Eu), a low-energy acceptor (Yb) and an optically inactive ion (Gd) with the 1,2,4,5 tetrakis(4-carboxyphenyl) benzene (TCPB) organic linker. Precise manipulation of the luminescence decay dynamics over a wide microsecond regime is achieved via control over metal distribution in these systems. Demonstration of this platform’s relevance as a tag is attained via a dynamic double encoding method that uses the braille alphabet, and by incorporation into photocurable inks patterned on glass and interrogated via digital high-speed imaging. This study reveals true orthogonality in encoding using independently variable lifetime and composition, and highlights the utility of this design strategy, combining facile synthesis and interrogation with complex optical properties.

36 MATERIALS SCIENCE↗

DOE OSTI2024

KBase Narrative - Metabolic_reconstruction_ETDI_mangrove

Mangroves are complex and dynamic coastal ecosystems under frequent fluctuations in physicochemical conditions related to the tidal regime. The frequent variation in organic matter concentration, nutrients, and oxygen availability, among other factors, drives the microbial community composition, favoring syntrophic populations harboring a rich and diverse, stress-driven metabolism. Mangroves are known for their carbon sequestration capability, and their complex and integrated metabolic activity is essential to global biogeochemical cycling. Here, we present a metabolic reconstruction based on the genomic functional capability and flux profile between sympatric MAGs co-assembled from a tropical restored mangrove.

Laux, Marcele↗