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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Toward Multiscale, Multimaterial 3D Printing

Biological materials and organisms possess the fundamental ability to self-organize, through which different components are assembled from the molecular level up to hierarchical structures with superior mechanical properties and multifunctionalities. These complex composites inspire material scientists to design new engineered materials by integrating multiple ingredients and structures over a wide range. Additive manufacturing, also known as 3D printing, has advantages with respect to fabricating multiscale and multi-material structures. The need for multifunctional materials is driving 3D printing techniques toward arbitrary 3D architectures with the next level of complexity. In this paper, the aim is to highlight key features of those 3D printing techniques that can produce either multiscale or multimaterial structures, including innovations in printing methods, materials processing approaches, and hardware improvements. Several issues and challenges related to current methods are discussed. Ultimately, the authors also provide their perspective on how to realize the combination of multiscale and multimaterial capabilities in 3D printing processes and future directions based on emerging research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

High‐Speed Slot‐Die Coating with Donor‐Priority Rapid Aggregation Kinetics for Improved Morphology and Efficiency in Ecofriendly Organic Solar Cells

Abstract Solution‐processable organic solar cells (OSCs) represent a promising renewable photovoltaic technology with significant potential for eco‐compatible production. While high power conversion efficiencies (PCEs) have been achieved in OSCs, scaling this technology for high‐throughput manufacturing remains challenging. Key reason lies in the lack of efficient control strategies for the complex and long‐duration morphology evolution during high‐speed coating process with ecofriendly solvents. Here, a donor‐priority rapid aggregation process (DP‐RAP) scheme is proposed to solve this issue by adjusting the aggregation kinetics of donor and acceptor components. DP‐RAP enables blends with a nanoscale fiber network structure and favorable crystallinity, which contributes to balanced carrier transport and reduced recombination losses. As a result, the PCE is improved from 14.3% (reference) to 17.4% (DP‐RAP) for ultra‐high speed coated PM6:BTP‐eC9 devices in atmosphere, which is one of the highest values for non‐halogenated solvent‐processed solar cells at coating speeds of 500 mm s −1 . Moreover, the DP‐RAP based devices remain a stable PCE of approximately 17.4% across a broad range of coating speeds (20–500 mm s −1 ), illustrating its tolerance to the varied manufacturing conditions. This work highlights a promising avenue for the high‐speed, ecofriendly production of efficient OSCs, pushing the boundaries of practical manufacturing in renewable energy technologies.

Chemistry↗
DOE OSTI2020

A Discrete Dendrite Dynamics Model for Epitaxial Columnar Grain Growth in Metal Additive Manufacturing with Application to Inconel

Epitaxial columnar grain growth is a prevalent microstructural feature in the additive manufacturing (AM) of metal components such as Inconel, with cubic unit cell crystal lattice structure (face centered cubic (FCC) or body centered cubic (BCC)). These columnar grains evolve from the partly molten grains in the substrate or the solidified metal. This work proposes an efficient model to simulate the competitive growth of epitaxial columnar dendritic grains. The proposed model tracks the dynamic changes in the dendrites emanating from discrete points along the solid/liquid interface of a quasi-steady melt pool (MP). These dynamic changes include convergence and divergence of growing dendrites. The model is extended to predict the microstructure of large 3D parts and experimentally validated by comparing the simulation results for laser powder bed fusion (L-PBF) and wire-arc additive manufacturing (WAAM) processes. The microstructure and pole figures are predicted for Inconel 718 samples produced by L-PBF and Inconel 740H samples produced by WAAM processes. Finally, the model predictions compare well with the observed microstructure and pole figures results for both the L-PBF and WAAM processes.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗
DOE OSTI2024

Cluster expansion by transfer learning for phase stability predictions

Recent progress towards universal machine-learned interatomic potentials holds considerable promise for materials discovery. Yet the accuracy of these potentials for predicting phase stability may still be limited. In contrast, cluster expansions provide accurate phase stability predictions but are computationally demanding to parameterize from first principles, especially for structures of low dimension or with a large number of components, such as interfaces or multimetal catalysts. We overcome this trade-off via transfer learning. Using Bayesian inference, we incorporate prior statistical knowledge from machine-learned and physics-based potentials, enabling us to sample the most informative configurations and to efficiently fit first-principles cluster expansions. Furthermore, this algorithm is tested on Pt:Ni, showing robust convergence of the mixing energies as a function of sample size with reduced statistical fluctuations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermohydraulic experiments on a supercritical carbon dioxide–air microtube heat exchanger

Heat exchangers are critical components in supercritical CO 2 Brayton cycles and provide necessary heat input, recovery, and dissipation. Tubular heat exchangers with unconventionally small tube sizes (tube diameters less than 5 mm) are promising components for supercritical CO 2 cycles and potentially provide excellent structural stability with wide scope of application. This paper provides essential design and fabrication guidelines for a compact shell-and-tube heat exchanger with microtubes (with an inner diameter equal to 1.75 mm). A heat exchanger test rig is used to evaluate the thermohydraulic performance of this heat exchanger with supercritical CO 2 and air as working fluids. Thermohydraulic data are reported for more than forty sets of experiments with varying Reynolds numbers for shell and tube flows. Critical performance metrics are calculated from the data and compared with predictions from a previously described numerical model. The average deviations between the experimental and model results fall within 10% for all critical metrics. This excellent agreement validates the numerical model for supercritical CO 2 heat exchanger optimization and scale-up.

42 ENGINEERING↗
DOE OSTI2025

Substituent size versus metal binding of inhibitors with variants of influenza endonuclease

The influenza virus causes a significant burden of illness each year. Although vaccination is the most effective method to prevent seasonal influenza infection, viral escape mechanisms make vaccine composition difficult to predict. Antivirals are crucial for decreasing rates of morbidity and mortality from influenza viral infection. The newest anti-influenza drugs target the RNA-dependent RNA polymerase acidic N-terminal (PA N ) endonuclease, a critical component of influenza viral replication machinery. This study examines the structure of inhibitors of PAN that utilize a hydroxypyridinone-based metal-binding pharmacophore (MBP). Specifically, this report explores how the size of substituent groups impacts the binding conformation and affinity of a series of compounds against both wild-type (WT) and resistance mutant strains, I38T and E23K. Co-crystal structures revealed that the distance between compounds and enzyme residue 38 was conserved to maintain strong interactions, resulting in deviations from ideal coordination geometries at the active site metal centers. This suggests the interactions with residue 38 with each compound is important and can impact inhibitor potency as a consequence of distortions in the metal binding geometry of the compounds.

Endonuclease↗
DOE OSTI2025

Suppression of irradiation hardening in tungsten-coated ferritic steel for fusion reactor blanket applications

W-coated reduced activation ferritic steels have been developed for use as plasma facing components in fusion reactor blankets, offering excellent sputtering resistance and structural strength. Previous high-temperature coating methods, such as diffusion bonding and brazing, caused interfacial deterioration due to thermal stress from mismatched thermal expansion between W and reduced activation ferritic steel. To address this, underwater explosive welding was introduced as a high-velocity cold process that joins dissimilar materials while maintaining a strong, thin interface without the thermal issues associated with traditional methods. In this study, the effects of neutron irradiation on the hardness and microstructure in W-coated F82H reduced activation ferritic steel (W/F82H) joined by underwater explosive welding are investigated. Following neutron irradiation at 290 °C, irradiation hardening is suppressed in W, F82H, and their interface within the W/F82H material. Furthermore, microstructural observations indicate that the recovery of work hardening and relaxation of elastic strain introduced during coating significantly contribute to the suppression of irradiation hardening in W/F82H. In conclusion, W/F82H exhibits significantly suppressed irradiation hardening compared with those in stand-alone materials. This suppression is explained by residual stress from thermal expansion mismatch and the unique microstructure at the interface. These results provide valuable insights for the development of more durable materials in nuclear fusion applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The forward physics facility: Physics opportunities and conceptual design

The Forward Physics Facility (FPF) is a proposed extension of the HL-LHC program designed to exploit the unique scientific opportunities offered by the intense flux of high energy neutrinos, and possibly new particles, in the far-forward direction. Located in a well-shielded cavern 627 m downstream of one of the LHC interaction points, the facility will support a broad and ambitious physics program that significantly expands the discovery potential of the HL-LHC. Equipped with four complementary detectors -- FLArE, FASER$ν$2, FASER2, and FORMOSA -- the FPF will enable breakthrough measurements that will advance our understanding of neutrino physics, quantum chromodynamics, and astroparticle physics, and will search for dark matter and other new particles. With this Letter of Intent, we propose the construction of the FPF cavern and the construction, integration, and installation of its experiments. We summarize the physics case, the facility design, the layout and components of the detectors, as well as the envisioned collaboration structure, cost estimate, and implementation timeline.

Astroparticle physics↗
DOE OSTI2025

Ligand-Driven Electrochemical Tuning of Co 6 Se 8 Chevrel Clusters

Molecular “Chevrel-type” clusters of the formula Co 6 Se 8 L 6 (L = neutral ligand) are a well-studied class of clusters due to their utility as molecular analogues to the Chevrel extended solid phase and their application as subunits in hierarchical materials. However, their solution and optical properties remain relatively underexplored. Aiming to develop the fundamental relationships between the molecular and electronic structures of these clusters and their electrochemical and photophysical properties, this work reports the preparation of a series of Co 6 Se 8 (P­(C 6 H 4 R) 3 ) 6 -type clusters with R = Cl (1), F (2), H (3), CH 3 (4), and OCH 3 (5) via a stepwise synthetic approach. Solution and solid-state experimental characterization and density functional theory calculations reveal that the Co 6 Se 8 cores of 1–5 maintain consistent electronic and structural properties despite the variation of the triarylphosphine ligand para-substituent Hammett parameters (σ p ). However, cyclic voltammetry measurements indicate that the electron transfer energetics of 1–5 are strongly influenced by ligand substitution, with the E 1/2 of a given redox event spanning ∼0.5 V depending on the triarylphosphine ligand’s σ p . In conclusion, these findings support the characterization of Co 6 Se 8 clusters as atomically precise nanoclusters with both the structural robustness and the electrochemical tunability needed to act as components in larger charge transfer assemblies.

Wheaton, Amelia M. [Argonne National Laboratory (A↗
DOE OSTI2020

Anisotropic Motions of Fibrils Dictated by Their Orientations in the Lamella: A Coarse-Grained Model of a Plant Cell Wall

Plant cell walls are complex systems that exhibit the characteristics of both rigid and soft material depending on their external perturbations. The three main polymeric components in a plant primary cell wall are cellulose fibrils, hemicellulose, and pectins. These components interact in a hierarchical fashion giving rise to mesoscale structural features such as cellulose bundles, lamella stacking, and so on. Although several studies have focused on understanding these unique structural features, a clear picture linking them to cell wall mechanics is still lacking. As a first step toward this goal, a phenomenological model of plant cell wall has been developed in this work by using available experimental data to investigate the underlying connections between mesoscale structural features and the motions of fibrils during deformation. In this model cellulose fibrils exhibit motions such as angular reorientations and kinking upon forced stretching. Furthermore, these motions are dependent on the orientation of fibrils with respect to the stretch direction, i.e., fibrils that are at an angle to the stretch direction exhibit predominant angular reorientations, while fibrils transverse to the stretch direction undergo kinking as a result of transverse compression. Varying the chain length of pectin had negligible effects on these motions. One of the main contributions from this work is the development of a simple model that can be easily fine-tuned to test other hypotheses and extended to include additional experimental knowledge about the structural aspects of cell walls in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Detecting lithium plating dynamics in a solid-state battery with operando X-ray computed tomography using machine learning

Operando X-ray micro-computed tomography (µCT) provides an opportunity to observe the evolution of Li structures inside pouch cells. Segmentation is an essential step to quantitatively analyzing µCT datasets but is challenging to achieve on operando Li-metal battery datasets due to the low X-ray attenuation of the Li metal and the sheer size of the datasets. Herein, we report a computational approach, batteryNET, to train an Iterative Residual U-Net-based network to detect Li structures. The resulting semantic segmentation shows singular Li-related component changes, addressing diverse morphologies in the dataset. In addition, visualizations of the dead Li are provided, including calculations about the volume and effective thickness of electrodes, deposited Li, and redeposited Li. We also report discoveries about the spatial relationships between these components. The approach focuses on a method for analyzing battery performance, which brings insight that significantly benefits future Li-metal battery design and a semantic segmentation transferrable to other datasets.

25 ENERGY STORAGE↗
DOE OSTI2025

Magnetically dependent photovoltages in permalloy films and gratings

Significant photoinduced voltages observed in permalloy structures consist of two contributions with different origins, which depend on illumination conditions, structure geometry and magnetic field in distinct ways. The first component is the plasmon drag effect voltage closely associated with plasmon propagation. The second contribution is magnetically dependent and can be related to photoinduced gradients in the sample temperature and spin polarization. Possible mechanisms of the effect are discussed

36 MATERIALS SCIENCE↗
DOE OSTI2020

What we know and what we don’t know about the proton spin after 30 years

More than three decades ago, the European Muon Collaboration published a surprising result on the spin structure of the proton: the spins of its three quark components account for only a small part of the spin of the proton. Furthermore, ever since, theoretical and experimental progress has been made in understanding the origins of the proton spin. In this review, we discuss what has been learned so far, what is still missing and what could be learned from the upcoming experiments, including the Jefferson Lab 12GeV upgrade and the proposed Electron-Ion Collider. In particular, we focus on first-principles calculations and experimental measurements of the total gluon helicity ΔG, and the quark and gluon orbital angular momenta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Electrostatically driven pattern formation in mixed charged–neutral multicomponent elastic membranes

Multicomponent crystalline and amorphous elastic shells exhibit heterogeneous surface patterns that provide distinctive functionalities in cellular environments. Such patterning typically arises from the competition between short-range attractive and long-range repulsive interactions in membranes. Here, we demonstrate that the intrinsic competition between electrostatic repulsion and elastic deformation is sufficient to drive spontaneous surface patterning in elastic shells, requiring no additional attractive interactions. Using numerical simulations, we demonstrate pattern formation in mechanically homogeneous membranes with heterogeneous surface charge composition across different topologies, including spheres, discs, and flat periodic membranes. We also examine patterns in crystalline and amorphous shells of coassembled charged and neutral components with different bending rigidities. At low charge fraction, discrete charged surface domains form. At intermediate charge fraction, the competition between electrostatics and elasticity leads to elongated domains (rods) of the charged component, which results in lamellar patterns at nearly equal fraction of the charged and neutral components. At high charge fraction, nanodomains of the neutral component form. Amorphous shells exhibit similar progressions but with disordered structures rather than ordered lamellar patterns. These pattern morphologies are observed in both the closed shells and flat membranes. As salt concentration increases, all patterns coarsen due to the screening of electrostatic interactions.

charge heterogeneity↗
DOE OSTI2023

New Structure in the Deuteron

Here, we demonstrate that a paradigm shift from considering the deuteron as a system of a bound proton and neutron to that of a pseudovector system in which we observe a proton and neutron results in the possibility of probing a new “incomplete” P-statelike structure on the light front (LF). This occurs at extremely large internal momenta, which can be achieved in a high energy transfer electrodisintegration of the deuteron. Investigating the deuteron on the light front, where the vacuum fluctuations are suppressed, we found that this new structure, together with the conventional S and D states, is leading order in transferred energy of the reaction and thus not suppressed on the light front. The incompleteness of the observed P state results in a violation of the angular condition that can happen only if the deuteron contains non-nucleonic structures, such as Δ Δ, N*⁢N or hidden color components. We demonstrate that experimentally verifiable signatures of incomplete P states are angular anisotropy of the light front momentum distribution of the nucleon in the deuteron, as well as an enhancement of the tensor polarization strength beyond the S- and D-wave predictions at large internal momenta in the deuteron.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Structure and electronic tunability of acene alkylamine based layered hybrid organic-inorganic perovskites from first principles

Twelve layered hybrid organic-inorganic perovskites combining oligoacene derivatives [phenylmethylammonium (PMA), naphthylmethylammonium (NMA), anthrylmethylammonium (AMA), and tetrylmethylammonium (TMA)] and lead halides (Cl - , Br - , and I - anions) are investigated by first-principles density functional theory (DFT), showing broad, rational tunability of band gap, quantum well type, and spin-dependent energy band properties. Six compounds are known from previous syntheses and are used to devise a computational search space for likely low-energy structures. Among the six known compounds, a refined structure is identified for (NMA) 2 ⁢ PbCl 4 and a new, lower-energy structure is suggested for (AMA) 2 ⁢PbCl 4 . The DFT based search methodology is next applied to predict the likely structures for the six unknown compounds. Computationally predicted energy levels for all 12 compounds from spin-orbit coupled hybrid DFT reveal tunable type I quantum well alignments, with frontier orbitals located on the inorganic component, on the organic component, or on both, as controlled by cation and anion selection. In conclusion, several structures spontaneously break local and global inversion symmetry, causing strong spin splitting of the conduction bands [up to 0.12 eV for (PMA) 2 ⁢PbCl 4 ] and showing potential for spin-dependent transport properties and future spintronic and tunable chiroptical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Water Network Tool for Resilience (WNTR)

The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework. The software includes capability to: • Generate water network models • Modify network structure and operations • Assign fragility and survival curves to network components • Model disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents • Model response and repair strategies • Simulate hydraulics and water quality • Evaluate resilience using a wide range of metrics • Integrate dependency with other critical infrastructure and supply chains • Analyze results and generate graphics SAND2019-450 M

Villa, Daniel↗