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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 OSTI2025

CAML: Commutative Algebra Machine Learning─A Case Study on Protein–Ligand Binding Affinity Prediction

Recently, Suwayyid and Wei introduced commutative algebra as an emerging paradigm for machine learning and data science. In this work, we propose commutative algebra machine learning (CAML) for the prediction of protein−ligand binding affinities. Specifically, we apply persistent Stanley−Reisner theory, a key concept in combinatorial commutative algebra, to the affinity predictions of protein−ligand binding and metalloprotein−ligand binding. We present three new algorithms, i.e., element-specific commutative algebra, category-specific commutative algebra, and commutative algebra on bipartite complexes, to tackle the complexity of data involved in (metallo) protein−ligand complexes. We show that the proposed CAML outperforms other state-of-theart methods in (metallo) protein−ligand binding affinity predictions, indicating the great potential of commutative algebra learning.

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

Liquid Phase Modeling in Porous Media: Adsorption of Methanol and Ethanol in H-MFI in Condensed Water

Zeolites are used in the chemical and separation industries for their exceptional selectivity, adsorption capacity, regenerability, and stability in gas and liquid phase processing. Here, we developed an explicit solvation method for predicting solvent/condensed phase effects on adsorption free energies in microporous media such as zeolites based on the hybrid quantum mechanical/molecular mechanical free energy perturbation (QM/MM-FEP) technique. Our explicit solvation method for zeolite systems, called eSZS, aims to capture site-specific interactions during the adsorption process at the Brønsted acid sites of H-MFI zeolite while still considering the diverse configuration space of the solvent molecules. This strategy is ideal for chemical reactions or adsorbates that interact with the microporous medium in few distinct adsorbate/transition state configurations, i.e., the harmonic or similar approximations are acceptable for the adsorbate/transition state while such approximations break down for the solvent molecules that require extensive configuration space sampling. In this way, our approach effectively overcomes the limitations of implicit solvation models and classical force field methods for describing solvation effects on chemical reactions within porous materials such as zeolites. Specifically, in this study, we investigated various aspects of our hybrid QM/MM approach, including QM cluster size dependencies in a periodic electrostatically embedded cluster model (PEECM), rules for link atoms at the QM/MM boundary, and functional and basis set considerations for converged and reasonably accurate gas and aqueous phase methanol and ethanol adsorption free energy predictions in H-MFI. For gas phase adsorption of methanol and ethanol in H-MFI at a Brønsted acid site in T12 position, we compute adsorption free energies at 298 K of −0.61 and −0.75 eV, respectively, using a PEECM containing 50 Si and 1 Al atom with ωB97x-D/def2-TZVP level of theory. For solvent effect calculations, we sample the aqueous phase using grand canonical Monte Carlo (GCMC) simulations to (1) obtain a mean field of electrostatic interactions in the reaction system and (2) perform a rigorous free energy perturbation calculation. Similar to the experimentally and computationally observed endergonic solvation effects observed for hydrocarbon adsorption on metal surfaces, we also observe that a condensed aqueous environment destabilizes methanol and ethanol at these acid sites in H-MFI at 298 K. Specifically, the computed solvation free energies of adsorption (ΔΔG solv ) for methanol and ethanol are +0.44 and +0.54 eV, respectively. From this study, it is evident that adsorbates (methanol and ethanol) are competing with water for adsorption space inside the H-MFI zeolite, leading to an endergonic solvation effect. Here, we expect that the endergonic, aqueous solvent effect during adsorption in microporous zeolites is highly tunable by changing the pore size and hydrophobicity of the microporous material as this will affect the water density inside the pore structure.

Adsorption↗
DOE OSTI2025

Clifford Circuit-Based Heuristic Optimization of Fermion-To-Qubit Mappings

Simulation of interacting Fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analyzing Fermionic systems with a quantum computer hinges on the efficiency of Fermion-to-qubit mappings that encode nonlocal Fermionic degrees of freedom in local qubit degrees of freedom. While recent studies have highlighted the importance of designing Fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far either are restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, in this work, we address this challenge by designing a heuristic numerical optimization framework for Fermion-to-qubit mappings. To this end, we first translate the Fermion-to-qubit mapping problem to a Clifford circuit optimization problem and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all Fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% and 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6 × 6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperforms any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific Fermionic Hamiltonian.

Hamiltonians↗
DOE OSTI2020

Atomistic Insight into Cation Effects on Binding Energies in Cu-Catalyzed Carbon Dioxide Reduction

Electrolyte properties in general and electrolyte ions in particular have been shown to have significant effects on the kinetics of electrochemical CO 2 and CO reduction at metal electrodes, but these effects have not yet been fully understood. Here, we investigate the effects of cations at the aqueous electrolyte–Cu(211) interface on adsorbate binding energies and the electrolyte structure using density functional theory (DFT). Charging the interface via explicit Na + has systematic effects on adsorbate–electrolyte interactions and conformations. We describe specific local adsorbate–ion interactions, including direct alkali ion–adsorbate coordination and hydrogen bonding via ion-coordinated water molecules. The relative importance of these specific interactions and purely electrostatic field–adsorbate interactions is investigated by comparing the DFT-calculated ion effects to those predicted by purely electrostatic models of the interface and the adsorbates. We find that the trend in ion effects among different adsorbates at constant surface charge density is well explained by a purely electrostatic interaction model. The binding energy of OCCHO is found to depend strongly on the surface charge density as well as the spatial distribution of ions at constant surface charge density. These effects are also explained by a purely electrostatic local electrostatic field–adsorbate model. This indicates that alkali ion effects can be mainly attributed to purely electrostatic field interactions and that the local field at ion-stabilized active sites can depend significantly on both the overall charge density and on the spatial distribution of ions at constant charge density. This work provides new insight on alkali ion effects on a variety of adsorbates relevant to the CO 2 and CO reduction reactions by describing specific local ion–adsorbate interactions, systematic changes in adsorbate–electrolyte interactions induced by explicit surface charge, and comparisons of the calculated effects on binding energies to simple electrostatic field–adsorbate models to explain trends among various adsorbates and at varying surface charge densities and supercell configurations.

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

Relationships between Water’s Structure and Solute Affinity at Polypeptoid Brush Surfaces

Excellent antifouling surfaces are generally thought to create a tightly bound layer of water that resists solute adsorption, and highly hydrophilic surfaces such as those with zwitterionic functionalities are of significant current interest as antifoulant strategies. Furthermore, despite significant proofs-of-concept, we still lack a fundamental understanding of how the nanoscopic structure of this hydration layer translates to reduced fouling, how surface chemistry can be tuned to achieve antifouling through hydration water, and why, in particular, zwitterionic surfaces seem so promising. Here, we use molecular dynamics simulations and free energy calculations to investigate the molecular relationships among surface chemistry, hydration water structure, and surface–solute affinity across a variety of surface-decorated chemistries. Specifically, we consider polypeptoid-decorated surfaces that display well-known experimental antifouling capabilities and that can be synthesized sequence specifically, with precise backbone positioning of, e.g., charged groups. Through simulations, we calculate the affinities of a range of small solutes to polypeptoid brush surfaces of varied side-chain chemistries. We then demonstrate that measures of the structure of surface hydration water in response to a particular surface chemistry signal solute–surface affinity; specifically, we find that zwitterionic chemistries produce solute–surface repulsion through highly coordinated hydration water while suppressing tetrahedral structuring around the solute, in contrast to uncharged surfaces that show solute–surface affinity. Based on the relationship of this structural perturbation to the affinity of small-molecule solutes, we propose a molecular mechanism by which zwitterionic surface chemistries enhance solute repulsion, with broader implications for the design of antifouling surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Ion Pairing Mediates Molecular Organization Across Liquid/Liquid Interfaces

Liquid/liquid interfaces play a central role in scientific fields ranging from nanomaterial synthesis and soft matter electronics to nuclear waste remediation and chemical separations. This diversity of functions arises from an interface’s ability to respond to changing conditions in its neighboring bulk phases. Understanding what drives this interfacial flexibility can provide novel avenues for designing new functional interfaces. However, limiting this progress is an inadequate understanding of the subtle intermolecular and interphase interactions taking place at the molecular level. Here, we use surface-specific vibrational sum frequency generation spectroscopy combined with atomistic molecular dynamics simulations to investigate the self-assembly and structure of model ionic oligomers consisting of an oligodimethylsiloxane (ODMS) tail covalently attached to a positively charged methyl imidazolium (MIM + ) head group at buried oil/aqueous interfaces. We show how the presence of seemingly innocuous salts can impart dramatic changes to the ODMS tail conformations in the oil phase via specific ion effects and ion-pairing interactions taking place in the aqueous phase. These specific ion interactions are shown to drive enhanced amphiphile adsorption, induce morphological changes, and disrupt emergent hydrogen-bonding structures at the interface. Tuning these interactions allows for independent control over the oligomer structure in the oil phase versus interfacial population changes and represents key mechanistic insight that is needed to control chemical reactions at liquid/liquid interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Coordination-Dependent Chemical Reactivity of TFSI Anions at a Mg Metal Interface

Charge transfer across the electrode–electrolyte interface is a highly complex and convoluted process involving diverse solvated species with varying structures and compositions. Despite recent advances in in situ and operando interfacial analysis, molecular specific reactivity of solvated species is inaccessible due to a lack of precise control over the interfacial constituents and/or an unclear understanding of their spectroscopic fingerprints. However, such molecular-specific understanding is critical to the rational design of energy-efficient solid–electrolyte interphase layers. We have employed ion soft landing, a versatile and highly controlled method, to prepare well-defined interfaces assembled with selected ions, either as solvated species or as bare ions, with distinguishing molecular precision. Equipped with precise control over interfacial composition, we employed in situ multimodal spectroscopic characterization to unravel the molecular specific reactivity of Mg solvated species comprising (i.e., bis(trifluoromethanesulfonyl)imide, TFSI – ) anions and solvent molecules (i.e., dimethoxyethane, DME/G1) on a Mg metal surface relevant to multivalent Mg batteries. In situ multimodal spectroscopic characterization revealed higher reactivity of the undercoordinated solvated species [Mg-TFSI-G1] + compared to the fully coordinated [Mg-TFSI-(G1) 2 ] + species or even the bare TFSI – . These results were corroborated by the computed reaction pathways and energy barriers for decomposition of the TFSI – within Mg solvated species relative to bare TFSI – . Finally, we evaluated the TFSI reactivity under electrochemical conditions using Mg(TFSI) 2 –DME-based phase-separated electrolytes representing different solvated constituents. Based on our multimodal study, we report a detailed understanding of TFSI – decomposition processes as part of coordinated solvated species at a Mg-metal anode that will aid the rational design of improved sustainable electrochemical energy technologies.

25 ENERGY STORAGE↗
DOE OSTI2023

Fluorinated High-Voltage Electrolytes To Stabilize Nickel-Rich Lithium Batteries

As state-of-the-art (SOA) lithium-ion (Li-ion) batteries approach their specific energy limit (~250 Wh kg -1 ), layer-structured, nickel-rich (Ni-rich) lithium transition metal oxide-based cathode materials, e. g., LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), have attracted great interest owing to their practical high specific capacities (>200 mAhg -1 ). Coupled with their high average discharge voltages (~4 V vs Li/Li + ), Ni-rich cathode-based lithium batteries possess a great potential to achieve much higher specific energies (>350 Wh kg -1 at the cell level) than the SOA Li-ion counterparts. In addition, Ni-rich oxides are low-cost battery cathode materials due to their low cobalt contents. However, Ni-rich cathode-based lithium batteries suffer quick capacity degradations upon cycling, particularly at high upper cutoff voltages (e.g., ≥= 4.5 V vs Li/Li + ), due to crystal structure changes of the active cathode materials and parasitic side reactions at the electrolyte/electrode interfaces. In this study, a fluorinated-solvent-based, high-voltage stable electrolyte (HVE), i.e., 1 M Li bis(trifluoromethanesulfonyl)imide (LiTFSI) in fluoroethylene carbonate (FEC), bis(2,2,2-trifluoroethyl) carbonate (FDEC), and methyl (2,2,2-trifluoroethyl) carbonate (FEMC) with Li difluoro(oxalate)borate (LiDFOB) additive, was formulated and evaluated in Li/NMC811 battery cells. Further, to the best of our knowledge, this class of electrolyte has not been investigated for Ni-rich cathode-based lithium batteries. Li/NMC811 cells with HVE exhibited a superior long-term cycle performance stability, maintaining ~80% capacity after ~500 cycles at a high cutoff voltage of 4.5 V (vs Li/Li + ) than a baseline carbonate-solvent-based electrolyte (BE). The superior cycle stability of the Li/NMC811 cells is attributed to the inherently high-voltage stability of HVE, supported by the physical and electrochemical analyses. This conclusion is supported by our density functional theory (DFT) modeling where HVE shows a less tendency of deprotonation/oxidation than BE, leading to the observed cycle stability. The findings in this study are important to help tackle the technical challenges facing Ni-rich cathode-based lithium batteries to realize their high energy density potentials with a long cycle life.

25 ENERGY STORAGE↗
DOE OSTI2020

Plasmon-Mediated Intramolecular Methyl Migration with Nanoscale Spatial Control

Plasmonic materials interact strongly with light to focus and enhance electromagnetic radiation down to nanoscale volumes. Due to this localized confinement, materials that support localized surface plasmon resonances are capable of driving energetically unfavorable chemical reactions. In certain cases, the plasmonic nanostructures are able to preferentially catalyze the formation of specific photoproducts, which offers an opportunity for the development of solar-driven chemical synthesis. Here, using plasmonic environments, we report inducing an intramolecular methyl migration reaction, forming 4-methylpyridine from N-methylpyridinium. Using both experimental and computational methods, we were able to confirm the identity of the N-methylpyridinium by making spectral comparisons against possible photoproducts. This reaction involves breaking a C–N bond and forming a new C–C bond, highlighting the ability of plasmonic materials to drive complex and selective reactions. Additionally, we observe that the product yield depends strongly on optical illumination conditions. This is likely due to steric hindrance in specific regions on the nanostructured plasmonic substrate, providing an optical handle for driving plasmonic catalysis with spatial specificity. Furthermore, this work adds yet another class of reactions accessible by surface plasmon excitation to the ever-growing library of plasmon-mediated chemical reactions.

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

Immunotargeting of Nanocrystals by SpyCatcher Conjugation of Engineered Antibodies

Inorganic nanocrystals such as quantum dots (QDs) and upconverting nanoparticles (UCNPs) are uniquely suited for quantitative live-cell imaging and are typically functionalized with ligands to study specific receptors or cellular targets. Antibodies (Ab) are among the most useful targeting reagents owing to their high affinities and specificities, but common nanocrystal labeling methods may orient Ab incorrectly, be reversible or denaturing, or lead to Ab-NP complexes too large for some applications. Here, we report that SpyCatcher proteins, which bind and spontaneously form covalent isopeptide bonds with cognate SpyTag peptides, can conjugate engineered Ab to nanoparticle surfaces with control over stability, orientation, and stoichiometry. Compact SpyCatcher-functionalized QDs and UCNPs may be labeled with short-chain variable fragment Ab (scFv) engineered to bind urokinase-type plasminogen activator receptors (uPAR) that are overexpressed in many human cancers. Confocal imaging of anti-uPAR scFv-QD conjugates shows the antibody mediates specific binding and internalization by breast cancer cells expressing uPAR. Time-lapse imaging of photostable scFv-UCNP conjugates shows that Ab binding causes uPAR internalization with a ~20 min half-life on the cell surface, and uPAR is internalized to endolysosomal compartments distinct from general membrane stains and without significant recycling to the cell surface. The controlled and stable conjugation of engineered Ab to NPs enables targeting of diverse receptors for live-cell study of their distribution, trafficking, and physiology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

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

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

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

A Structurally Diverse Compound Screening Library to Identify Substrates for Diamine, Polyamine, and Related Acetyltransferases

Spermidine/spermine N-acetyltransferases (SSATs) and other types of polyamine acetyltransferases (PAATs) acetylate diamines and/or polyamines. These enzymes are evolutionarily related and belong to the Gcn5-related N-acetyltransferase (GNAT) superfamily, yet we lack a fundamental understanding of their substrate specificity and/or promiscuity toward different compounds. Many of these enzymes are known or are predicted to acetylate polyamines, but in the cell there are other types of compounds that contain moieties derived from polyamines that may be the native substrates for these enzymes. To learn more about the identity of substrates that are acetylated, we selected and screened 17 different GNAT enzymes for activity toward a set of structurally diverse compounds that contained different types of amine moieties (e.g., aminopropyl, aminobutyl, etc.). These compounds included diamines, triamines, and polyamines containing primary amino groups, and they had structural diversity with variation of the chain length and presence or absence of internal amino groups and other functional groups. We found 12 of the 17 enzymes acetylated at least one of the compounds. Some enzymes were selective toward acetylating only one compound while others exhibited substrate promiscuity toward numerous compounds. Our experimental results ultimately allowed us to pinpoint specific substrates that could be further investigated to more fully understand substrate specificity versus promiscuity of GNAT enzymes and the role of acetylated small molecules in cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Microwave-Based Synthesis of Functional Morphological Variants and Carbon Nanotube-Based Composites of VS 4 for Electrochemical Applications

A novel facile, fast, and efficient microwave-assisted method was developed to synthesize a number of diverse nanostructured motifs (ranging from nanorods to nanoflowers) of VS 4 along with its associated composite heterostructures, VS 4 /multi-walled carbon nanotube (MWNT; i.e., multi-walled carbon nanotubes). Specifically, we have probed and correlated the effects of a number of specific experimental variables, including primarily precursor, solvent, temperature, and time. We noted that nanorods formed more readily with VO(acac) 2 as the vanadium precursor and n-methyl-2-pyrrolidone (NMP) as a polar reaction solvent. By contrast, we determined that hierarchical three-dimensional (3D) nanoflower-like assemblies, ranging in size from 100 to 200 nm in average diameter, could be controllably synthesized by using Na 3 VO 4 as the vanadium precursor and an aqueous water: polar solvent mixture as the reaction medium. We also observed that VS 4 disintegrates, when in the presence of either air, solution, or a combination of these environments, and established that the extent of VS4 nanorod decomposition could be almost fully prevented by storage under nitrogen. From an application’s perspective, our VS 4 is electrochemically active and shows behavior, consistent with the literature. In particular, as compared with pristine VS 4 nanorods alone, we observed enhanced electrochemical activity with (i) 3D hierarchical flower-like motifs, (ii) unique necklace-like VS 4 nanorod–MWNT composites, and (iii) samples in which as-prepared VS4 nanorods had been annealed. Moreover, we found that the rational application of specific physical and chemical processing treatments, such as (i) thermal annealing to improve crystallinity, (ii) the addition of MWNTs to form conductive composites, and (iii) the evolution of morphology from one-dimensional (1D) nanorods to more complex 3D nanoflowers, was favorable to the resulting electrochemical performance with respect to increasing stability and reversibility.

25 ENERGY STORAGE↗
DOE OSTI2024

Sustainable and Energy-Efficient Production of Rare-Earth Metals via Chloride-Based Molten Salt Electrolysis

Neodymium metal is a critical component of rare earth magnets, essential for electric vehicles and the green energy transition, but its production has severe environmental impacts across its mining, separation, purification, and metal electrowinning steps. Specifically, conventional neodymium electrowinning in oxyfluoride molten salts using a consumable graphite anode generates greenhouse gases, e.g., carbon dioxide and perfluorocarbon (PFC). We propose an alternative chloride-based molten salt electrolysis process utilizing a novel dimensionally stable anode (DSA). Our process lowers the specific electrical energy consumption compared to the state of the art, while producing reusable chlorine gas and eliminating direct CO 2 and PFC emissions. Chloride-based molten salt electrolysis of NdCl 3 (1.65 M) added to a LiCl–KCl eutectic (45:55 wt %), while using a RuO 2 -coated DSA enables high Coulombic efficiency (>80%), low specific energy consumption (2.3 kWh/kg-Nd), and excellent electrowon Nd product purity (>97 wt %). Life cycle analysis, excluding the common input feedstock (Nd 2 O 3 ), shows that the global warming potential for the proposed chloride-based electrolysis approach is 5 kg CO 2 equivalent, compared to 9–16 kg CO 2 equivalent for the conventional process, representing a 44–69% reduction in CO 2 emissions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Development of an Energy-Efficient and High-Productivity Ammonia Recovery and Removal Process Using Resin-Wafer Electrodeionization

As efforts to develop various energy resources, ammonia energy is emerging as a promising carbon-free fuel alternative. Recovering high-concentration ammonia and ammonium from wastewater potentially offers significant environmental and economic benefits. However, research on recovery technologies for industries such as semiconductors remains limited. This study develops an efficient, energy-saving ammonia recovery technology using Resin Wafer Electrodeionization (RW-EDI), specifically for the semiconductor industry. RW-EDI shows promise for recovering ammonia from high-concentration wastewater. By optimizing parameters, such as voltage and initial concentration, a balance between productivity and energy consumption is achieved. Results indicate that ammonium and fluoride ion transport kinetics are similar, with minimal competition and selectivity values between 0.95 and 1.08. As the initial ammonia/ammonium concentration increases from 500 to 8000 ppm, reaction rate constants and the overall mass transfer coefficient decrease. Increasing the voltage can enhance mass transfer and eliminate barriers. Ion transport primarily occurs in the RW solid phase, accounting for 93.89% of the total current. Additionally, RW-EDI shows superior specific energy consumption within a concentration range of 500 ppm to 8000 ppm, outperforming technologies like electrodialysis by reducing specific energy consumption from 8−15 kWh/kg-NH 4 + to 1.2−2.5 kWh/kg-NH 4 + . This study highlights RW-EDI’s potential for ammonia recovery, providing valuable insights for future applications in wastewater treatment.

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

Greenhouse Gas Accounting Procedures in Low Carbon Fuel Policies Overlook the Spatial Variability of Miscanthus-Derived Sustainable Aviation Fuel

Low carbon fuel policies such as the U.S. Renewable Fuel Standard (RFS), Canada Clean Fuel Regulations (CFR), and California Low Carbon Fuel Standard (LCFS) as well as the 45Z tax credit are intended to reduce greenhouse gas (GHG) emissions from transportation. Cellulosic feedstocks, optimized biorefineries, and favorable farming locations can significantly reduce biofuel carbon intensity (CI). Despite advances in field-to-fuel GHG monitoring and flexibility in resource allocation within biorefineries (e.g., governing net electricity production), rigid CI accounting procedures in current policies may limit CI responsiveness across candidate sites and processing facilities. Here, this work examines a hypothetical biomass-to-sustainable aviation fuel (SAF) pathway using miscanthus and alcohol-to-jet (i) to demonstrate how GHG accounting requirements drive estimates of biofuel CIs and (ii) to explore potential CI and financial implications of scenario-specific life cycle assessment (LCA). Results demonstrate that GHG accounting using the CFR/LCFS can reasonably account for distinct levels of net electricity production by a biorefinery, but only the CFR yields similar CI sensitivity to spatially explicit factors (feedstock CI, grid electricity CI) as scenario-specific LCA: most GHG accounting frameworks do not capture CI variation across candidate sites in the United States. Ultimately, this work demonstrates the importance of LCA methodological specifications in low carbon fuel policies and tax credits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Self-Assembly of Atomically Aligned Nanoparticle Superlattices from Pt–Fe 3 O 4 Heterodimer Nanoparticles

Multicomponent nanoparticle superlattices (SLs) promise the integration of nanoparticles (NPs) with remarkable electronic, magnetic, and optical properties into a single structure. Here, we demonstrate that heterodimers consisting of two conjoined NPs can self-assemble into novel multicomponent SLs with a high degree of alignment between the atomic lattices of individual NPs, which has been theorized to lead to a wide variety of remarkable properties. Specifically, by using simulations and experiments, we show that heterodimers composed of larger Fe 3 O 4 domains decorated with a Pt domain at one vertex can self-assemble into an SL with long-range atomic alignment between the Fe 3 O 4 domains of different NPs across the SL. The SLs show an unanticipated decreased coercivity relative to nonassembled NPs. In situ scattering of the self-assembly reveals a two-stage mechanism of self-assembly: translational ordering between NPs develops before atomic alignment. Here our experiments and simulation indicate that atomic alignment requires selective epitaxial growth of the smaller domain during heterodimer synthesis and specific size ratios of the heterodimer domains as opposed to specific chemical composition. This composition independence makes the self-assembly principles elucidated here applicable to the future preparation of multicomponent materials with fine structural control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗