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Results for “Structural Optimization”

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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Relationship between Ionic Conductivity and Solvation Structures of Localized High-Concentration Fluorinated Electrolytes for Lithium-Ion Batteries

Localized high concentration electrolyte (LHCE) combines a diluent with high concentration electrolyte (HCE), offering promising properties. The ions, solvent, and diluent interact to form a complex heterogenous liquid structure, where high salt concentration clusters are embedded in diluent. Optimizing LHCE for desired electrolyte properties like high ionic conductivity, low viscosity, effective solid electrolyte interphase (SEI) formability, within the vast chemical and compositional design space requires deeper understanding and theoretical guidance. For this work, we investigated the structures and conductivity of LHCEs based on a fluorinated solvent with two different diluents at varying concentrations. The 2,2,3,3-tetrafluoropropyl trifluoroacetate (TFPTFA) enters the solvation cluster due to its stronger Li-ion interactions, whereas 1,1,2,2-tetrafuoroethyl 2,2,2-trifuoroethyl ether (TFETFE) enters only at extremely high diluent concentrations. The ionic conductivity increases with decreasing diluent concentrations, with a slope change during cluster percolation. Overall, TFETFE demonstrates higher effectiveness than TFPTFA, forming higher local salt concentration clusters, and resulting in higher ionic conductivity.

cluster chemistry↗
DOE OSTI2024

Grain boundary engineering for efficient and durable electrocatalysis

Grain boundaries in noble metal catalysts have been identified as critical sites for enhancing catalytic activity in electrochemical reactions such as the oxygen reduction reaction. However, conventional methods to modify grain boundary density often alter particle size, shape, and morphology, obscuring the specific role of grain boundaries in catalytic performance. This study addresses these challenges by employing gold nanoparticle assemblies to control grain boundary density through the manipulation of nanoparticle collision frequency during synthesis. We demonstrate a direct correlation between increased grain boundary density and enhanced two-electron oxygen reduction reaction activity, achieving a significant improvement in both specific and mass activity. Additionally, the gold nanoparticle assemblies with high grain boundary density exhibit remarkable electrochemical stability, attributed to boron segregation at the grain boundaries, which prevents structural degradation. This work provides a promising strategy for optimizing the activity, selectivity, and stability of noble metal catalysts through precise grain boundary engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Finding the order in complexity: The electronic structure of 14-1-11 zintl compounds

Yb 14 MnSb 11 and Yb 14 MgSb 11 have rapidly risen to prominence as high-performing p-type thermoelectric materials. However, the fairly complex crystal structure of A 14 MX 11 Zintl compounds renders the interpretation of the electronic band structure obscure, making it difficult to chemically guide band engineering and optimization efforts. In this work, we delineate the valence-balanced Zintl chemistry of A 14 MX 11 compounds using the molecular orbital theory. By analyzing the electronic band structures of Yb 14 MgSb 11 and Yb 14 AlSb 11 , we show that the conduction band minimum is composed of either an antibonding molecular orbital originating from the (Sb 3 ) 7– trimer or a mix of atomic orbitals of A, M, and X. The singly degenerate valence band is comprised of non-bonding Sb pz orbitals primarily from the Sb atoms in the (MSb 4 ) m– tetrahedra and of isolated Sb atoms distributed throughout the unit cell. Such a chemical understanding of the electronic structure enables strategies to engineer electronic properties (e.g., the bandgap) of A 14 MX 11 compounds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Magneto-optical, structural and surface properties of RIB sputtered (Bi,Ga)-substituted DyIG films

Highlights: • The dependences of properties of (Bi,Ga):DyIG films on GGG and CMZGGG substrates on the time of crystallization annealing were studied. • It was found that the films properties depend substantially on the substrate type and the time of crystallization annealing. • A minimal time of annealing to achieve the optimal parameters of the film was determined. - Abstract: The dependences of magneto-optical, structural and morphological properties of reactive ion beam sputtered (RIBS) nanoscale (Bi,Ga)-substituted DyIG [(Bi,Ga:DyIG)] films on (111) GGG and (111) CMZGGG substrates on the time of crystallization annealing were studied using Faraday effect measurements, X-ray diffraction and scanning atomic force microscopy. It was found that the roughness, degree of crystallinity and Faraday rotation angle of the films depend substantially on the substrate type and the time of crystallization annealing. It was determined a minimal time to achieve the optimal ratio between the measured magneto-optical and structural parameters of the film.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Zirconium‐Regulation‐Induced Bifunctionality in 3D Cobalt–Iron Oxide Nanosheets for Overall Water Splitting

Abstract The design of high‐efficiency non‐noble bifunctional electrocatalysts for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is paramount for water splitting technologies and associated renewable energy systems. Spinel‐structured oxides with rich redox properties can serve as alternative low‐cost OER electrocatalysts but with poor HER performance. Here, zirconium regulation in 3D CoFe 2 O 4 (CoFeZr oxides) nanosheets on nickel foam, as a novel strategy inducing bifunctionality toward OER and HER for overall water splitting, is reported. It is found that the incorporation of Zr into CoFe 2 O 4 can tune the nanosheet morphology and electronic structure around the Co and Fe sites for optimizing adsorption energies, thus effectively enhancing the intrinsic activity of active sites. The as‐synthesized 3D CoFeZr oxide nanosheet exhibits high OER activity with small overpotential, low Tafel slope, and good stability. Moreover, it shows unprecedented HER activity with a small overpotential of 104 mV at 10 mA cm −2 in alkaline media, which is better than ever reported counterparts. When employing the CoFeZr oxides nanosheets as both anode and cathode catalysts for overall water splitting, a current density of 10 mA cm −2 is achieved at the cell voltage of 1.63 V in 1.0 m KOH.

Huang, Liangliang↗
DOE OSTI2020

Unraveling the Nature of Excellent Potassium Storage in Small-Molecule Se@Peapod-Like N-Doped Carbon Nanofibers

The potassium-selenium (K-Se) battery is considered as an alternative solution for stationary energy storage because of abundant resource of K. However, the detailed mechanism of the energy storage process is yet to be unraveled. In this work, the findings in probing the working mechanism of the K-ion storage in Se cathode are reported using both experimental and computational approaches. A flexible K-Se battery is prepared by employing the small-molecule Se embedded in freestanding N -doped porous carbon nanofibers thin film (Se@NPCFs) as cathode. The reaction mechanisms are elucidated by identifying the existence of short-chain molecular Se encapsulated inside the microporous host, which transforms to K 2 Se by a two-step conversion reaction via an "all-solid-state" electrochemical process in the carbonate electrolyte system. Through the whole reaction, the generation of polyselenides (K 2 Se n , 3 ≤ n ≤ 8) is effectively suppressed by electrochemical reaction dominated by Se-2 molecules, thus significantly enhancing the utilization of Se and effecting the voltage platform of the K-Se battery. This work offers a practical pathway to optimize the K-Se battery performance through structure engineering and manipulation of selenium chemistry for the formation of selective species and reveal its internal reaction mechanism in the carbonate electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2025

Designing Moderately‐Solvating Electrolytes for High‐Performance Lithium–Sulfur Batteries

New electrolytes are critical for high‐energy lithium (Li)–sulfur (S) batteries (LSBs) to ensure their stability against Li metal anode and polysulfides (PSs) shuttling which hinder the large‐scale application of LSBs. In this study, the design principle of moderately solvating electrolytes (MSEs) for LSBs is demonstrated by using a multiple‐solvent system comprising of a highly solvating solvent, a weakly solvating solvent, and a non‐solvating solvent to create a well‐balanced electrolyte system. This resulting electrolyte significantly improves the cycle life of LSBs, achieving 300 cycles, which is twice as long as that of similar cells with the conventional electrolyte and it also ensures stable calendar life for at least seven months. The optimal MSE forms robust passivation layers enhancing the structural integrity of both S and Li metal electrodes after cycling. These virtues effectively hinder parasitic side reactions and self‐discharge behavior of LSBs. This electrolyte design principle is versatile and can be applied to other battery chemistries, providing a potential path toward the development of a more efficient and stable battery system. By addressing key challenges such as the instability of electrodes and shuttling of polysulfides, this electrolyte approach offers promising solutions for advancing LSB technology.

25 ENERGY STORAGE↗
DOE OSTI2025

Understanding Structural and Compositional Evolution during NMC Cathode Direct Recycling via Solid-State NMR

Recycling end-of-life lithium-ion batteries (LIBs) to recover high-value cathode materials such as LiNixMnyCozO2 (NMC) is driven by economical, geopolitical, and sustainability needs. There has been recent interest in direct recycling methods to improve efficiency and recovery of materials, including ionothermal, hydothermal, solid-state, or redox mediator methods. In conjunction with recycling process development, detailed structural characterization is necessary in order to understand the mechanisms and efficacy of cathode recycling steps. Solid-state nuclear magnetic resonance (NMR) spectroscopy is a unique tool that can probe Li coordination, bulk and surface environments, and transition metal ordering in recycled and upcycled NMC cathodes. Here, 6,7Li, 1H, and 19F NMR spectroscopy to probe structural and compositional changes as well as surface impurities that may form during each step in NMC direct recycling is utilized. During relithiation, Li reinsertion into the NMC lattice is observed. During upcycling, where the goal is to increase the Ni content in the NMC, incorporation of Ni-rich phases into the bulk Li environment is observed. Surface impurities formed during processing were also identified. These studies provide valuable information for optimizing recycling processes to reach targeted cathode composition and structure that can enable electrochemical performance comparable to or better than pristine materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hypersonic Jets of Detonation Products in the Hydrodynamic Collapse of Macroscopic Voids

Localizing the energetic output from detonation waves has been a long-standing challenge in applied detonation physics. Here, energy localization is achieved via machined millimeter scale voids in pressed samples of PBX 9501, an HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane)-based plastic bonded explosive. A main mechanism of energy localization in these systems, the formation of hydrodynamic jets of dense product gases, is characterized experimentally using a semicylindrical geometry in witness plate impact experiments and streak imaging of the jet propagating into the air. The distance at which the jet is optimally developed is identified and the supersonic flow structure in the vicinity of this feature is explored using hydrocode simulations. This analysis found that most of the kinetic energy of the hydrodynamic jet arises from pressure gradients induced by geometrically mediated squeeze flow lateral to the direction of detonation propagation. This work presents a new development in the control of energetic output from detonation waves and applications to detonation wave shaping are discussed.

42 ENGINEERING↗
DOE OSTI2022

Design space exploration and decision‐making for a segmented ultralight morphing 50‐MW wind turbine

Abstract Wind turbine design encompasses many different aspects including aerodynamic, structural, electrical, and control system design. To achieve optimal plant performance, a system design approach is utilized in which the performance of the whole wind turbine is evaluated and quantified during operational scenarios with subsystem interactions. In this paper, the design for a Segmented Ultralight Morphing Rotor (SUMR) 50‐MW wind turbine is presented utilizing levelized cost of energy (LCOE) for design choices, with additional quantification of simulated performance shortcomings at the 50‐MW scale. The multi‐disciplinary design process results in a final ultra‐scale turbine configuration that outperforms other existing offshore wind farms regarding the LCOE.

Kianbakht, Sepideh↗
DOE OSTI2018

Quantitative Pointwise Estimate of the Solution of the Linearized Boltzmann Equation

We study the quantitative pointwise behavior of the solutions of the linearized Boltzmann equation for hard potentials, Maxwellian molecules and soft potentials, with Grad’s angular cutoff assumption. More precisely, for solutions inside the finite Mach number region (time like region), we obtain the pointwise fluid structure for hard potentials and Maxwellian molecules, and optimal time decay in the fluid part and sub-exponential time decay in the non-fluid part for soft potentials. For solutions outside the finite Mach number region (space like region), we obtain sub-exponential decay in the space variable. The singular wave estimate, regularization estimate and refined weighted energy estimate play important roles in this paper. Our results extend the classical results of Liu and Yu (Commun Pure Appl Math 57:1543–1608, 2004), (Bull Inst Math Acad Sin 1:1–78, 2006), (Bull Inst Math Acad Sin 6:151–243, 2011) and Lee et al. (Commun Math Phys 269:17–37, 2007) to hard and soft potentials by imposing suitable exponential velocity weight on the initial condition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Enhanced sensitivity of hemoglobin sensor using dual-core photonic crystal fiber

A Hemoglobin (Hb) biosensor based on dual-core photonic crystal fiber is proposed and analyzed. In this paper, the effective refractive index dependency on the Hb concentration within a blood sample is utilized in obtaining the transmission spectrum variation. The results are calculated using full vectorial finite element method. Through this study, the effect of the structure geometrical parameters on the sensor performance is optimized to maximize the sensor sensitivity. The numerical results show a sensitivity of 8.013 nm/g/dL for the X-polarized mode at 3.7 cm fiber length and 7.68 nm/g/dL for the Y-polarized mode at 3.2 cm fiber length of the proposed sensor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Strategies for design and synthesis of porous liquids toward carbon capture and separation

Porous liquids (PLs) represent a promising category of sorbents in carbon capture and separation capable of integrating the advantages of flowing liquid and porous solid systems. Well-defined pores were engineered into liquid sorbents via liquifying molecules with stiff interior voids, dissolving rigid porous hosts in flowing liquids, or dispersing porous frameworks in high steric hindrance solvents, producing type I, II, or III PLs, respectively. Unique features of PLs have triggered broad interest in exploring their applications in carbon capture and separation, in which diverse design strategies, synthesis approaches, and enhanced performance have been reported. Here, in this minireview, recent progress in the design, synthesis, and structural engineering of PLs and efforts towards the optimization of their carbon capture and separation behavior will be summarized, including the comparison between PLs with varied types. Porosity engineering into liquid sorbents provides opportunities to resolve challenging issues in conventional sorption and separation systems.

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

QRCODE: Massively parallelized real-time time-dependent density functional theory for periodic systems

We present a new software module, QRCODE (Quantum Research for Calculating Optically Driven Excitations), for massively parallelized real-time time-dependent density functional theory (RT-TDDFT) calculations of periodic systems in the open-source Qbox software package. Our approach utilizes a custom implementation of a fast Fourier transformation scheme that significantly reduces inter-node message passing interface (MPI) communication of the major computational kernel and shows impressive scaling up to 16,344 CPU cores. In addition to improving computational performance, QRCODE contains a suite of various time propagators for accurate RT-TDDFT calculations. As benchmark applications of QRCODE, we calculate the current density and optical absorption spectra of hexagonal boron nitride (h-BN) and photo-driven reaction dynamics of the ozone-oxygen reaction. We also calculate the second and higher harmonic generation of monolayer and multi-layer boron nitride structures as examples of large material systems. Our optimized implementation of RT-TDDFT in QRCODE enables large-scale calculations of real-time electron dynamics of chemical and material systems with enhanced computational performance and impressive scaling across several thousand CPU cores.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Towards automated and real-time multi-object detection of anguilliform fishes from sonar data using YOLOv8 deep learning algorithm

Eels (Anguilla spp.), including American eels (Anguilla rostrata), European eels (Anguilla anguilla), and Japanese eels (Anguilla japonica), are species of critical management and regulatory concern due to their vulnerability to various stressors during downstream migrations. Accurate and efficient detection of migrating eels can improve our understanding of fish behaviors and fish-hydraulic structure interactions, thereby facilitating the design, operation, and optimization of more effective downstream passage facilities from both biological and economic perspectives. However, a real-time, automated framework for detecting migrating eels in real-world applications is currently lacking. Leveraging imaging sonar as a reliable technology for fish passage monitoring, field data are acquired using imaging sonar and then converted to single sonar frames/images for subsequent analysis. In this study, a framework based on the You Only Look Once Version 8 (YOLOv8)-based convolutional neural network is proposed for multi-object detection of eels and non-eel fish using the sonar images after image subtraction and additional wavelet denoising. The results from both training and testing phases demonstrate that the framework's ability can successfully detect both eels and non-eel fish in preprocessed sonar images, achieving F1-scores and mAP@0.50 exceeding 0.84. Additionally, the incorporation of wavelet denoising during preprocessing slightly improve detection performance. Furthermore, the transferability of this framework from eel to lamprey detection is demonstrated to be feasible given the similar morphological characteristics of these two species. Overall, the proposed framework achieves accurate and efficient detection of migrating eels, providing reliable and real-time information that can help conserve vulnerable eel and eel-like populations.

Deep learning↗
DOE OSTI2021

Core-shell and egg-shell zeolite catalysts for enhanced hydrocarbon processing

Developing structure-performance relationships with the underlying goal of optimizing known zeolite catalysts involves the manipulation of their physicochemical properties. Here, we systematically assessed the impact of mesoscopic gradients in acid site concentration, which has generally received little attention in the design of zeolite catalysts for hydrocarbon upgrading. A series of core–shell MEL-type zeolites were synthesized with catalytically active ZSM-11 cores and passivated silicalite-2 shells of varying thickness. Our findings revealed that ZSM-11@silicalite-2 particles with ultrathin shells (<10 nm) have enhanced mass transport, characteristic of relatively smaller particles, compared to the corresponding ZSM-11 core. Additionally, catalytic testing using the methanol-to-hydrocarbon (MTH) reaction showed that core–shell zeolites exhibit longer lifetimes, higher total turnovers, and an unexpected promotion of the aromatic cycle in the hydrocarbon pool mechanism. Time-resolved acid titration of core and core–shell catalysts confirmed that the siliceous shell introduces a hydrophobic exterior that impacts molecular diffusion. In comparison, prepared MFI core-shells (ZSM-5@silicalite-1) showed similar enhancement in catalyst performance. Moreover, we prepared egg-shell configurations of each zeolite, silicalite-2@ZSM-11 and silicalite-1@ZSM-5, comprised of an inert core and catalytically active shell. This inverse design of the egg-shell created pseudo nanosheets with total turnovers that were markedly higher than their homogeneous counterparts. Collectively, this study demonstrated that mesoscopic gradients in acid concentration via the design of core–shell and egg-shell zeolites significantly improve catalyst performance over conventional analogues for hydrocarbon upgrading.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Trends and limits of CO 2 capture in solid and liquid sorbents at standard conditions

Carbon capture and storage (CCS) plays a critical role in achieving climate change mitigation targets, offering a pathway to decarbonize power generation, industrial processes, and heat production while addressing atmospheric CO 2 removal. While CCS technologies are technically advanced, the widespread adoption of 100 % CO 2 capture capacities such as 1 mol of CO 2 /mol of material and 1 g CO 2 /g storage (targeted by the DARPA, Defense Sciences Office, USA Govt.) has raised questions about the feasibility of achieving higher capture capacities. In the context of limiting global warming to 1.5°C, reaching 100 % CO 2 capture capacity is increasingly necessary, with residual emissions requiring complementary carbon dioxide removal (CDR) technologies. This review exclusively focuses on the CO 2 capture capacities of various sorbents under standard conditions, using different evaluation metrics. This study explores the performance of solid and liquid sorbents under standard conditions, analyzing factors including surface area, pore structure, solvent type, and functionalization to identify materials optimized for industrial-scale CCS applications. Emerging sorbents, including ILs, MOFs, COFs, POPs, DES, RCC, hybrid materials, and reactive sorbents, offer significant potential for enhanced selectivity and energy-efficient regeneration. Through a systematic assessment of gravimetric, volumetric, and molar capacities, the study provides insights into material efficiencies and trade-offs, offering guidance on optimizing sorbent selection for specific applications. The research advances understanding of scalable CCS technologies, contributing to global efforts to achieve net-zero emissions and address the pressing challenge of climate change.

Absorption↗
DOE OSTI2024

Convergence of variational Monte Carlo simulation and scale-invariant pre-training

We provide theoretical convergence bounds for the variational Monte Carlo (VMC) method as applied to optimize neural network wave functions for the electronic structure problem. Here, we study both the energy minimization phase and the supervised pre-training phase that is commonly used prior to energy minimization. For the energy minimization phase, the standard algorithm is scale-invariant by design, and we provide a proof of convergence for this algorithm without modifications. The pre-training stage typically does not feature such scale-invariance. We propose using a scale-invariant loss for the pretraining phase and demonstrate empirically that it leads to faster pre-training.

97 MATHEMATICS AND COMPUTING↗