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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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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Visible-Light Photoinitiation of (Meth)acrylate Polymerization with Autonomous Post-Conversion

Conversion plateaus rapidly in radical photopolymerizations (RPPs) following discontinuation of irradiation due to rapid termination of reactive radicals, which restricts the wider use of RPPs in applications that involve nonuniform light access including those with attenuated light transmission or irregular surfaces. Based on our recent report of a radical dark-curing photoinitiator (DCPI) that continues polymerization beyond the cessation of irradiation by enabling latent redox initiation with photo-released amine in the presence of a suitable oxidant, we developed a new DCPI with an absorption spectrum that extends well into the visible range. Our design process involved a series of computational investigations of candidate molecules, including a systematic study of substituents and their position-dependent effects on absorption characteristics, electronic transitions, and the photochemical mechanism and its associated energetics. Our quantum chemical computations identified the target compound 5,7-dimethoxy-6-bromo-3-aroylcoumarin-DMPT/BPh4 and predicted that it would facilitate the dark-curing mechanism by concurrent photo-radical generation and photo-induced release of an efficient redox reductant under visible irradiation. This reductant-tethered chromophore was then synthesized and optically characterized with UV–vis spectroscopy that revealed its strong visible-light absorption with a molar absorptivity of 5710 M–1 cm–1 at 405 nm and 50 M–1 cm–1 at 455 nm. We then demonstrated extensive dark-curing of >35% additional conversion over 25 min following brief activation of the shelf-stable one-part system by irradiation with a 455 nm LED that was ceased at 20% conversion. In contrast, shuttering irradiation of the control formulation at that same point resulted in immediate cessation of conversion, which plateaued at 20%. We determined a remarkable initiator efficiency of 2.82 that results from the additional redox-generated radicals with a 77% photo-reductant generation quantum yield. The combination of superior photo- and dark-curing efficiencies of this new visible DCPI is expected to open new application opportunities in RPP, especially those involving resins that are highly light attenuating, surfaces that possess irregular features that produce uneven irradiance, and production lines where continued dark-curing downstream of the light activation step enhances line efficiencies.

absorption spectrum↗
DOE OSTI2023

Technoeconomic Model and Pathway to <$2/kg Green Hydrogen Using Integrated Halide Perovskite Photoelectrochemical Cells

The cost of gray hydrogen produced via fossil fuel-based steam-methane reforming has led the U.S. Department of Energy to specify <$\$$2/kg H 2 as a target for commercially competitive green hydrogen generation methods. Integrated photoelectrochemical cells have been proposed as a solar-to-hydrogen conversion technology. In this paper we describe a technoeconomically feasible pathway to reaching <$\$$2/kg green H 2 using integrated photoelectrochemical cells with halide perovskite photoabsorbers, low-cost conductive barriers, and low precious metal-content catalysts in an aqueous, membrane-separated cell. A base-case solar-to-hydrogen conversion efficiency of 20%, stable lifetime of 10 years, and a combined electrocatalyst-plus-panel cost of $\$$50/m 2 enabled a levelized cost of hydrogen of $\$$2.43/kg, which dropped below $\$$2/kg with improved performance metrics including material cost, improvements in process design, or subsidies. We relate these metrics to lab-scale reports to recommend best research practices for scientists and funding agencies working at this intersection of photovoltaics, electrocatalysis, and surface science.

$1/kg↗
DOE OSTI2022

Exceptional Mineral Scaling Resistance from the Surface Gas Layer: Impacts of Surface Wetting Properties and the Gas Layer Charging Mechanism

Mineral scaling is a phenomenon that occurs on submerged surfaces in contact with saline solutions. In membrane desalination, heat exchangers, and marine structures, mineral scaling reduces process efficiency and eventually leads to process failure. Therefore, achieving long-term scaling resistance is beneficial to enhancing process performance and reducing operating and maintenance costs. While evidence shows that superhydrophobic surfaces may reduce mineral scaling kinetics, prolonged scaling resistance is limited due to the finite stability of the entrained gas layer present in a Cassie–Baxter wetting state. Additionally, superhydrophobic surfaces are not always feasible for all applications, but strategies for long-term scaling resistance with smooth or even hydrophilic surfaces are often overlooked. In this study, we elucidate the role of interfacial nanobubbles on the scaling kinetics of submerged surfaces of varied wetting properties, including those that do not entrain a gas layer. We show that both solution conditions and surface wetting properties that promote interfacial bubble formation enhances scaling resistance. In the absence of interfacial bubbles, scaling kinetics decrease as surface energy decreases, while the presence of bulk nanobubbles enhances the scaling resistance of the surface with any wetting property. The findings in this study allude to scaling mitigation strategies that are enabled by solution and surface properties that promote the formation and stability of interfacial gas layers and provide insights to surface and process design for greater scaling resistance.

calcite↗
DOE OSTI2025

Characterizing the Potential for Sustainable Azelaic Acid Production from High-Oleic Vegetable Oil Using Two-Step Oxidative Cleavage

Azelaic acid is a renewable monomer conventionally produced via the energy-intensive ozonolysis of oleic acid. Recent advancements have enabled the use of high-oleic vegetable oils (rather than tallow-derived oleic acid) and replaced ozonolysis with two-step oxidative cleavage using hydrogen and oxygen. Although this shift would improve process safety, the financial viability and environmental implications remain uncertain. In this study, we characterized the sustainability of azelaic acid production from high-oleic vegetable oil using two-step oxidative cleavage. Process design, simulation, technoeconomic analysis (TEA), and life cycle assessment (LCA) were executed under uncertainty using BioSTEAM. The modeled system produces azelaic acid at a market-competitive minimum selling price (MSP) of 8.32 [4.93−13.34] $\$kg$ −1 (median 5th−95th percentiles), below the minimum estimated market price of 9.93 $\$kg$ −1 . Further, it has the potential to approach carbon neutrality (0.0 [−5.5 to 5.6] kg of CO 2 -eq kg −1 ) under displacement allocation. Improvements to dihydroxylation (86 to 99%) and oxidative cleavage conversions (93 to 99%) would reduce MSP to $\$5.24$ kg −1 and carbon intensity to −1.90 kg of CO 2 -eq kg −1 (displacement). Additionally, increasing the feedstock triolein content (75 to 85%) lowers MSP by $\$0.82$ kg −1 . Overall, this research demonstrates the potential for financially viable production of azelaic acid from vegetable oils and the utility of agile TEA/LCA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Streamlining and Simplifying the Chemical Separationof Berkelium (249Bk) from Other Actinides/Lanthanides andFission Products

Abstract Separation of an individual heavy actinide from other actinides, lanthanides, and coproduced fission products is challenging not only because of their similarity in chemistry but also because the chemistry of heavy actinides is largely unknown. At present, the cation-exchange chromatography with α-hydroxyisobutyric acid (CX-AHIB) method is used to isolate milli- to picogram quantities of heavy actinides (i.e., 249Bk, 252Cf, 254Es, and 257Fm). This method allows simultaneous separation of these actinides; however, isolating a clean individual product with a high yield has proven challenging. The process is also very slow and labor-intensive and requires precise control of various chemical conditions, such as pH, temperature, and AHIB concentration. Developing a separation scheme for heavy actinides requires identifying their unique feature and then harnessing this feature in the separation process design. The unique characteristic of Bk4+ is that it does not adsorb onto anion exchange resin columns, unlike other tetravalent actinides. This article discusses what makes Bk unique and how this discovery led to a new method for separating Bk from adjacent actinides, lanthanides, and coproduced fission products. The method employed two different resin columns in tandem to separate unwanted actinides from 249Bk, followed by fine cleanup of 249Bk. The advantages of the new Bk method over the CX-AHIB method in Bk production are discussed, and the performance and robustness of the proposed method were assessed in two recent production campaigns.

Chemistry↗
DOE OSTI2025

Diffusion Model-Guided Inverse Design of Bimetallic Catalysts for Ammonia Decomposition

In the past decade, artificial intelligence and deep learning have played increasingly prominent roles in materials design and discovery. Among these, generative AI models, known for their ability to create unique and complex structures, have emerged as state-of-the-art tools for materials screening due to their high efficiency and low computational cost. In catalysis, one of the major challenges is identifying promising material candidates within an immense chemical space. This challenge can be addressed using generative approaches, such as diffusion-based inverse design models. In this study, we present a machine learning-guided workflow that employed a diffusion model for the inverse design of bimetallic alloy catalysts for low-carbon ammonia decomposition, a key reaction for ammonia emission control and sustainable hydrogen production. Catalyst candidates were evaluated using nitrogen adsorption energy as the key descriptor, inspired by multiscale modeling. The proposed workflow identified low-cost, environmentally friendly catalysts with excellent catalytic performance, which have been validated theoretically and experimentally. Our framework decoupled the generative and property-prediction components, enhancing both flexibility and accuracy in the catalytic material design process.

Adsorption↗
DOE OSTI2026

Asymmetric pathways for lithium extraction and recovery based on the two-phase equilibrium of layered oxides

Electrochemical intercalation offers a promising platform for Li + extraction. However, only limited types of electrode materials have been investigated. The challenge to broaden and tailor materials for electrochemical intercalation-based Li + extraction lies in the lack of understanding of material’s response upon co-intercalation of multiple ions, therefore, paired process design to enable reversible Li + extraction and recovery. Here, we showcase the design of asymmetric ion pathways for Li + extraction and recovery for host material with complex Li + and Na + interaction using layered cobalt oxide as a model material. The two-phase equilibrium of Na 0.48 CoO 2 and Li 0.94 CoO 2 governs Li + selectivity when a high depth of intercalation is achieved (low vacancy level). We show that the relative rate between ion exchange and intercalation is critical to determine the ion pathways. The relationship can be quantitatively compared using the average pseudo ion exchange rate (C pseudoIX ) and the intercalation rate (C inter ). The ion pathways at the three regimes with C pseudoIX > C inter , C pseudoIX ~ C inter , and C pseudoIX < C inter are constructed. By selecting the optimized ion pathway and particle size, we demonstrate 9.7×10 4 Li + selectivity with 99% purity Li + recovery from an initial 1:1000 Li: Na molar ratio solution using 115 mAh/g specific capacity.

electrochemistry↗
DOE OSTI2020

Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images

Cutting edge deep learning techniques allow for image segmentation with great speed and accuracy. However, application to problems in materials science is often difficult since these complex models may have difficultly learning meaningful image features that would enable extension to new datasets. In situ electron microscopy provides a clear platform for utilizing automated image analysis. In this work, we consider the case of studying coarsening dynamics in supported nanoparticles, which is important for understanding, for example, the degradation of industrial catalysts. By systematically studying dataset preparation, neural network architecture, and accuracy evaluation, we describe important considerations in applying deep learning to physical applications, where generalizable and convincing models are required. With a focus on unique challenges that arise in high-resolution images, we propose methods for optimizing performance of image segmentation using convolutional neural networks, critically examining the application of complex deep learning models in favor of motivating intentional process design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Towards the holistic design of alloys with large language models

Large language models are very effective at solving general tasks, but can also be useful in materials design and extracting and using information from the scientific literature and unstructured corpora. For instance, in the domain of alloy design and manufacturing, they can expedite the materials design process and enable the inclusion of holistic criteria.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Inverse design of nanoporous crystalline reticular materials with deep generative models

Reticular frameworks are crystalline porous materials that form via the self-assembly of molecular building blocks in different topologies, with many having desirable properties for gas storage, separation, catalysis, biomedical applications and so on. The notable variety of building blocks makes reticular chemistry both promising and challenging for prospective materials design. Here we propose an automated nanoporous materials discovery platform powered by a supramolecular variational autoencoder for the generative design of reticular materials. We demonstrate the automated design process with a class of metal–organic framework (MOF) structures and the goal of separating carbon dioxide from natural gas or flue gas. Our model shows high fidelity in capturing MOF structural features. Here, we show that the autoencoder has a promising optimization capability when jointly trained with multiple top adsorbent candidates identified for superior gas separation. MOFs discovered here are strongly competitive against some of the best-performing MOFs/zeolites ever reported.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Pushing the limits of size selectivity in nanoscale solute separations

Transport of a spherical solute through a cylindrical pore has been modelled for decades using well-established hindered transport theory, predicting solutes with a size smaller than the pore to be rejected nonetheless because of convective and diffusive hindrance; this rejection mechanism prevents extremely sharp solute separations by a membrane. Whereas the model has been historically verified, solute transport through near-perfect isoporous membranes may finally overcome this limitation. Here, in this study, encouraging solute rejections are achieved using nanofabricated, defect-free silicon nitride isoporous membranes. The membrane is challenged by a recirculated feed to increase the opportunity for interactions between solutes and the pore array. Results show the membrane completely reject solutes with greater size than the pore size while effectively allowing smaller solutes to permeate through. With effectively increasing the number of interactions, we propose that a steeper size-selective rejection curve may be achieved. With this traditional hurdle overcome, there is new promise for unprecedented membrane separations through judicious process design and extremely tight pore-size distributions.

Gao, Feng↗
DOE OSTI2021

Nucleation and growth of blue phase liquid crystals on chemically-patterned surfaces: a surface anchoring assisted blue phase correlation length

In condensed matter, the correlation length is an essential parameter which describes the distance over which a material maintains its structural properties. In liquid crystals, for the orientational order parameter this characteristic length is of the order of nanometers, while in solid crystals it can extend to macroscopic length scales. Here, we report the measurement of the correlation length, or persistence length, of the crystallographic orientation of blue phases (BPs)—chiral liquid crystals with long-range 3D-crystalline structures and submicron-sized lattice-parameters. These materials exhibit phase transformations that have been identified as the liquid analog of crystal-crystal martensitic transformations. In this work, we use liquid epitaxial growth to achieve spontaneous BP-crystal nucleation and subsequent growth. Specifically, we design patterned substrates made of a binary array of regions with different liquid crystal anchoring, which facilitate a uniform nucleation and growth of BP-crystals with (100)-lattice orientation and a simple cubic symmetry. Furthermore, our results indicate that this simple cubic BP, the so-called blue phase II (BPII), forms first on the patterned surface, thereby propagating the growth of domains in directions parallel or perpendicular to the patterned regions. These results are used to understand the emergence of a surface anchoring assisted BPII-correlation length, taken as the distance over which the BP preserves its lattice orientation, as a function of time and pattern characteristics. We found that BPII single crystals can be achieved on patterned regions whose lateral dimensions are equal to or larger than 10 μm, consistent with our measurements of the BPII-correlation length. This newly acquired understanding of the role of surfaces on the formation of BPs is then used to design processes that permit formation of macroscopically large mono-domain, single-crystal BPs by relying on significantly reduced patterned areas (only part of the area is patterned), a feature that could benefit the applications of this intriguing class of materials.

correlation length↗
DOE OSTI2022

Synthesis of platinum nanoparticles on strontium titanate nanocuboids via surface organometallic grafting for the catalytic hydrogenolysis of plastic waste

Pt/SrTiO 3 (Pt/STO), prepared on small scale by atomic layer deposition (ALD), is a capable heterogeneous catalyst for the selective hydrogenolysis of polyolefins to hydrocarbon oils, providing a promising approach for upcycling plastic waste. However, because deposition by ALD is costly and resource-intensive, a new synthesis of Pt/STO is needed to effectively scale catalyst production and pursue the commercialization of upcycling processes. To that effect, this work details a scalable deposition method for Pt/STO made by surface organometallic chemistry (SOMC) techniques using Pt(II) acetylacetonate or and trimethyl(methylcyclopentadienyl)platinum. The STO support was calcined (550 °C), treated with ozone (200 °C), and finally steamed (200 °C) to afford a clean STO surface populated with only hydroxyl groups. Pt precursors were dissolved in toluene and deposited onto STO. After reduction at 300 °C, the STO support was decorated with 1.0–1.5 nm Pt nanoparticles. The size and loading of these nanoparticles were varied by employing a multi-cycle deposition and oxidation and/or reduction process designed to ALD techniques. In conclusion, these Pt/STO catalysts hydrogenolyzed isotactic polypropylene into liquid products (>95% yield) with average molecular weights of 200–300 Da (~25 carbon atoms) and narrow size distributions at 300 °C and 180 psi H 2 .

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

A General Binary Isotherm Model for Amines Interacting with CO 2 and H 2 O

CO 2 capture by primary or secondary amines has been of great research interests for a century because of its industrial importance. Interest has grown even more, because of the need to eliminate the CO 2 emissions that drive global warming. Experimental evidence shows that CO 2 sorption in primary or secondary amines is accompanied by co-absorption of H 2 O. A quantitative analysis of such CO 2 -H 2 O co-absorption behavior is important for practical process design and theoretical understanding. Even though there is almost an experimental consensus that water enhances CO 2 uptake capacity, an analytic model to explain this phenomenon is not well established. Instead, some empirical models such as the Toth model are used to describe the isotherm without accounting for the presence of water. Recently, we have demonstrated that the isotherm equation of CO 2 sorption into strong-base anion exchange materials with quaternary ammonium can be derived from that of strong-base aqueous alkaline solutions by correcting for the drastic change in water activity and by including an appropriate parameterization of the water activity terms. In this paper, we generalize this model from quaternary ammonium to primary, secondary and tertiary amines either in solutions or as functional groups in polymer resins. For primary, secondary and tertiary amines, the isotherm equation can be derived by extending that of a weak-base aqueous alkaline solution such as aqueous ammonia. The model has been validated using experimental data of aqueous ammonia in literature. Furthermore, this general model even includes quaternary ammonium as a special limit. Hence, this general model offers a platform that can treat the isotherms of solid amines, aqueous amines and aqueous alkaline solutions in a unified way.

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

“Freedom of design” in chemical compound space: towards rational in silico design of molecules with targeted quantum-mechanical properties

The rational design of molecules with targeted quantum-mechanical (QM) properties requires an advanced understanding of the structure–property/property–property relationships (SPR/PPR) that exist across chemical compound space (CCS). In this work, we analyze these fundamental relationships in the sector of CCS spanned by small (primarily organic) molecules using the recently developed QM7-X dataset, a systematic, extensive, and tightly converged collection of 42 QM properties corresponding to ≈4.2M equilibrium and non-equilibrium molecular structures containing up to seven heavy/non-hydrogen atoms (including C, N, O, S, and Cl). By characterizing and enumerating progressively more complex manifolds of molecular property space—the corresponding high-dimensional space defined by the properties of each molecule in this sector of CCS—our analysis reveals that one has a substantial degree of flexibility or “freedom of design” when searching for a single molecule with a desired pair of properties or a set of distinct molecules sharing an array of properties. To explore how this intrinsic flexibility manifests in the molecular design process, we used multi-objective optimization to search for molecules with simultaneously large polarizabilities and HOMO–LUMO gaps; analysis of the resulting Pareto fronts identified non-trivial paths through CCS consisting of sequential structural and/or compositional changes that yield molecules with optimal combinations of these properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Security constrained optimal power shutoff for wildfire risk mitigation

Abstract Electric grid faults are increasingly the source of ignition for major wildfires. To reduce the likelihood of such ignitions in high risk situations, utilities use preemptive de‐energization of power lines, commonly referred to as Public Safety Power Shutoffs (PSPS). Besides raising challenging trade‐offs between power outages and wildfire safety, PSPS removes redundancy from the network at a time when component faults are likely to happen. This may leave the network particularly vulnerable to unexpected line faults that may occur while the PSPS is in place. Previous works have not explicitly considered the impacts of these outages. To address this gap, the Security Constrained Optimal Power Shutoff problem is proposed which uses post‐contingency security constraints to model the impact of unexpected line faults when planning a PSPS. This model enables, for the first time, the exploration of a wide range of trade‐offs between both wildfire risk and pre‐ and post‐contingency load shedding when designing PSPS plans, providing useful insights for utilities and policy makers considering different approaches to PSPS. The efficacy of the model is demonstrated using the EPRI 39‐bus system as a case study. The results highlight the potential risks of not considering security constraints when planning PSPS and show that incorporating security constraints into the PSPS design process improves the resilience of current PSPS plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Reliability-based hull geometry optimisation of a point-absorber wave energy converter with power take-off structural reliability objectives

Recent studies have focused on optimising wave energy converter (WEC) designs, maximising their power performance and techno-economic feasibility. Reliability has yet to be fully considered in these formulations, despite its impact on cost and performance. In this study, this gap is addressed by developing a reliability-based design optimisation framework for WEC hull geometries to explore the trade-off between power performance and power take-off (PTO) system damage equivalent loading (DEL). Optimised hull geometries for two sites are considered (from the centre of the North Sea and off the west coast of Norway), and two directions of motions (heave and surge). Results indicate that site characteristics affect the potential power production and DEL for an optimal WEC design. These are also affected by the direction of motion for power extraction, which also significantly changes optimal hull shape characteristics. Optimal surging WEC designs have edges facing oncoming wave directions, while heaving WECs have pointed bottoms, both to streamline movement. Larger, more convex WECs result in greater power production and DEL, while smaller, more concave WECs result in lesser power production and DEL. These findings underline the importance of considering WEC hull geometry in early design processes to optimise cost, power production, and reliability.

16 TIDAL AND WAVE POWER↗