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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accurate additive manufacturing of lightweight and elastic carbons using plastic precursors

Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Iodide manipulation using zinc additives for efficient perovskite solar minimodules

Abstract Interstitial iodides are the most critical type of defects in perovskite solar cells that limits efficiency and stability. They can be generated during solution, film, and device processing, further accelerating degradation. Herein, we find that introducing a small amount of a zinc salt- zinc trifluoromethane sulfonate (Zn(OOSCF 3 ) 2 ) in the perovskite solution can control the iodide defects in resultant perovskites ink and films. CF 3 SOO ̶ vigorously suppresses molecular iodine formation in the perovskites by reducing it to iodide. At the same time, zinc cations can precipitate excess iodide by forming a Zn-Amine complex so that the iodide interstitials in the resultant perovskite films can be suppressed. The perovskite films using these additives show improved photoluminescence quantum efficiency and reduce deep trap density, despite zinc cations reducing the perovskite grain size and iodide interstitials. The zinc additives facilitate the formation of more uniform perovskite films on large-area substrates (78-108 cm 2 ) in the blade-coating process. Fabricated minimodules show power conversion efficiencies of 19.60% and 19.21% with aperture areas of 84 and 108 cm 2 , respectively, as certified by National Renewable Energy Laboratory (NREL), the highest efficiency certified for minimodules of these sizes.

14 SOLAR ENERGY↗
DOE OSTI2025

Data-driven design of electrolyte additives supporting high-performance 5 V LiNi 0.5 Mn 1.5 O 4 positive electrodes

LiNi 0.5 Mn 1.5 O 4 (LNMO) is a high-capacity spinel-structured material with an average lithiation/de-lithiation potential at ca. 4.6–4.7 V vs Li + /Li, far exceeding the stability limits of electrolytes. An efficient way to enable LNMO in lithium-ion batteries is to reformulate an electrolyte composition that stabilizes both graphitic (Gr) negative electrode with solid-electrolyte-interphase and LNMO with cathode-electrolyte-interphase. In this study, we select and test a diverse collection of 28 single and dual additives for the Gr||LNMO battery system. Subsequently, we train machine learning models on this dataset and employ the trained models to suggest 6 binary compositions out of 125, based on predicted final area-specific-impedance, impedance rise, and final specific-capacity. Such machine learning-generated new additives outperform the initial dataset. This finding not only underscores the efficacy of machine learning in identifying materials in a highly complicated application space but also showcases an accelerated material discovery workflow that directly integrates data-driven methods with battery testing experiments.

batteries↗
DOE OSTI2025

Quantification and prediction of solidification textures under additive manufacturing conditions

Crystallographic textures are a major determinant of the macroscale anisotropic properties of polycrystalline metallic alloys produced in a wide range of additive manufacturing (AM) processes. Here, we introduce a statistical method that can accurately quantify the degree of orientational order of textures despite the large random fluctuations in the orientation of individual grains inherent in AM processes. The method, demonstrated for laser and resolidification of AlSi thin films, extends Z-scoring to a dynamical regime to assess the statistical significance of observed textures compared to randomly generated ones at different stages of solidification. We further show that, combined with phase-field modeling, this method can be used to infer fundamental anisotropic properties of the solid-liquid interface that are essential for texture prediction, and are compared here to the results of atomistic simulations. In addition, phase-field modeling reveals that, even at rapid AM solidification rates, the observed 〈110〉-dominated textures in the AlSi thin films are controlled predominantly by the anisotropy of the interface free-energy and sheds light on the physical mechanism of grain competition. These results significantly enhance both the existing tools for the quantification and prediction of AM crystallographic textures and our basic understanding of their formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Additive manufacturing of LiNi 1/3 Mn 1/3 Co 1/3 O 2 battery electrode material via vat photopolymerization precursor approach

Additive manufacturing, also called 3D printing, has the potential to enable the development of flexible, wearable and customizable batteries of any shape, maximizing energy storage while also reducing dead-weight and volume. In this work, for the first time, three-dimensional complex electrode structures of high-energy density LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC 111) material are developed by means of a vat photopolymerization (VPP) process combined with an innovative precursor approach. This innovative approach involves the solubilization of metal precursor salts into a UV-photopolymerizable resin, so that detrimental light scattering and increased viscosity are minimized, followed by the in-situ synthesis of NMC 111 during thermal post-processing of the printed item. The absence of solid particles within the initial resin allows the production of smaller printed features that are crucial for 3D battery design. The formulation of the UV-photopolymerizable composite resin and 3D printing of complex structures, followed by an optimization of the thermal post-processing yielding NMC 111 is thoroughly described in this study. Based on these results, this work addresses one of the key aspects for 3D printed batteries via a precursor approach: the need for a compromise between electrochemical and mechanical performance in order to obtain fully functional 3D printed electrodes. In addition, it discusses the gaps that limit the multi-material 3D printing of batteries via the VPP process.

25 ENERGY STORAGE↗
DOE OSTI2022

Photoinduced chemomimetic biocatalysis for enantioselective intermolecular radical conjugate addition

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical con- jugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Here, mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

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

Laser-metal interaction dynamics during additive manufacturing resolved by detection of thermally-induced electron emission

In situ monitoring is required to improve the understanding and increase the reliability of additive manufacturing methods such as laser powder bed fusion (LPBF). Current diagnostic methods for LPBF capture optical images, X-ray radiographs, or measure the emission of thermal or acoustic signals from the component. Herein, a methodology based on the thermal emission of electrons - thermionic emission - from the metal surface during LPBF is proposed which can resolve laser-material interaction dynamics. The high sensitivity of thermionic emission to surface temperature and surface morphology is revealed to enable precise determination of the transition between conduction and keyhole mode melting regimes. Increases in thermionic emission are correlated to laser scanning conditions that give rise to pore formation and regions where surface defects are pronounced. The information presented here is a critical step in furthering our understanding and validation of laser-based metal additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dendritic deformation modes in additive manufacturing revealed by operando x-ray diffraction

Abstract Dynamic solidification behavior during metal additive manufacturing directly influences the as-built microstructure, defects, and mechanical properties of printed parts. How the formation of these features is driven by temperature variation (e.g., thermal gradient magnitude and solidification front velocity) has been studied extensively in metal additive manufacturing, with synchrotron x-ray imaging becoming a critical tool to monitor these processes. Here, we extend these efforts to monitoring full thermomechanical deformation during solidification through the use of operando x-ray diffraction during laser melting. With operando diffraction, we analyze thermomechanical deformation modes such as torsion, bending, fragmentation, assimilation, oscillation, and interdendritic growth. Understanding such phenomena can aid the optimization of printing strategies to obtain specific microstructural features, including localized misorientations, dislocation substructure, and grain boundary character. The interpretation of operando diffraction results is supported by post-mortem electron backscatter diffraction analyses.

Dass, Adrita (ORCID:000000019100635X)↗
DOE OSTI2024

Additive manufacturing of defect-free TiZrNbTa refractory high-entropy alloy with enhanced elastic isotropy via in-situ alloying of elemental powders

Laser powder-bed fusion (L-PBF) additive manufacturing presents ample opportunities to produce net-shape parts. The complex laser-powder interactions result in high cooling rates that often lead to unique microstructures and excellent mechanical properties. Refractory high-entropy alloys show great potential for high-temperature applications but are notoriously difficult to process by additive processes due to their sensitivity to cracking and defects, such as un-melted powders and keyholes. Here, we present a method based on a normalized model-based processing diagram to achieve a nearly defect-free TiZrNbTa alloy via in-situ alloying of elemental powders during L-PBF. Compared to its as-cast counterpart, the as-printed TiZrNbTa exhibits comparable mechanical properties but with enhanced elastic isotropy. This method has good potential for other refractory alloy systems based on in-situ alloying of elemental powders, thereby creating new opportunities to rapidly expand the collection of processable refractory materials via L-PBF.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗
DOE OSTI2021

Design, synthesis, and characterization of vinyl-addition polynorbornenes with tunable thermal properties

Unfunctionalized vinyl-addition polynorbornene (VAPNB) possesses many outstanding properties such as high thermal, chemical, and oxidative stability. These features make VAPNB a promising candidate for many engineering applications. However, VAPNB has a small service window between its glass transition temperature (T g ) and decomposition temperature (T d ), and it cannot be readily processed in a melt state. In this work, we demonstrate that the service window of VAPNBs can be tailored through the use of norbornene monomers bearing alkyl, aryl, and aryl ether substituents. The vinyl addition homopolymerization and copolymerization of these functionalized norbornyl-based monomers yielded VAPNBs with high T' g s (>150 °C) and large service windows (T d –T g > 100 °C), which are comparable to other commercial engineering thermoplastics. To further establish the feasibility of melt processing, a functionalized VAPNB material with T g = 209 °C and a service window of 170 °C was successfully extruded and molded into bars. Subsequent characterization of the bars by dynamic mechanical analysis (DMA), nuclear magnetic resonance spectroscopy (NMR), and gel permeation chromatography (GPC) revealed only minor signs of polymer degradation. Furthermore, these studies suggest that substituted VAPNBs could be developed into a new class of engineering thermoplastics that is compatible with workhorse melt processing techniques such as extrusion and injection molding, as well as emerging techniques such as extrusion-based 3D printing.

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

Light controlled reversible Michael addition of cysteine: a new tool for dynamic site-specific labeling of proteins

Cysteine-based Michael addition is a widely employed strategy for covalent conjugation of proteins, peptides, and drugs. The covalent reaction is irreversible in most cases, leading to a lack of control over the process. Utilizing spectroscopic analyses along with X-ray crystallographic studies, we demonstrate Michael addition of an engineered cysteine residue in human Cellular Retinol Binding Protein II (hCRBPII) with a coumarin analog that creates a non-fluorescent complex. UV-illumination reverses the conjugation, yielding a fluorescent species, presumably through a retro-Michael process. Furthermore, this series of events can be repeated between a bound and non-bound form of the cysteine reversibly, resulting in the ON–OFF control of fluorescence. The details of the mechanism of photoswitching was illuminated by recapitulation of the process in light irradiated single crystals, confirming the mechanism at atomic resolution.

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

High-speed x-ray phase contrast imaging and digital image correlation analysis of microscale shock response of an additively manufactured energetic material simulant

The performance of energetic materials subjected to dynamic loading significantly depends on their micro- and meso-scale structural morphology. The geometric versatility offered by additive manufacturing opens new pathways to tailor the performance of these materials. Additively manufactured energetic materials (AMEMs) have a wide range of structural characteristics with a hierarchy of length scales and process-inherent heterogeneities, which are hitherto difficult to precisely control. It is important to understand how these features affect AMEMs’ response under dynamic/shock loading. Therefore, temporally and spatially resolved measurements of both macroscopic behavior and micro- and meso-level processes influencing macroscopic behavior are required. In this paper, we analyze the shock compression response of an AMEM simulant loaded under several impact conditions and orientations. Furthermore, x-ray phase contrast imaging (PCI) is used to track features across the observed shock front and determine the linear shock velocity vs particle velocity equation of state, as well as to quantify the interior deformation fields via digital image correlation (DIC) analyses. Photon Doppler velocimetry is simultaneously used to measure the particle velocities of the specimens, which are consistent with those obtained from x-ray PCI. The DIC analyses provide an assessment of the average strain fields inside the material, showing that the average axial strain depends on the loading intensity and reaches as high as 0.23 for impact velocities up to 1.5 km/s. The overall results demonstrate the utility of x-ray PCI for probing “in-material” equation of state and interior strains associated with dynamic shock compression behavior of the AMEM simulant.

3D printing↗
DOE OSTI2020

Self-radiography of imploded shells on OMEGA based on additive-free multi-monochromatic continuum spectral analysis

Radiographs of pure-DT cryogenic imploding shells provide critical validation of progress toward ignition-scalable performance of inertial confinement fusion implosions. Cryogenic implosions on the OMEGA Laser System can be self-radiographed by their own core spectral emission near ≈2 keV. Utilizing the distinct spectral dependences of continuum emissivity and opacity, the projected optical-thickness distribution of imploded shells, i.e., the shell radiograph, can be distinguished from the structure of the core emission distribution in images.Importantly, this can be done without relying on spectral additives (shell dopants), as in previous applications of implosion self-radiography. Furthermore, demonstrations with simulated data show that this technique is remarkably well-suited to cryogenic implosions and can also be applied to self-radiography of imploded room-temperature CH shells at higher spectral energy (hv ≈ 3–5 keV) based on the very similar continuum spectrum of carbon. Experimental demonstration of additive-free self-radiography with warm CH shell implosions on OMEGA will provide an important proof of principle for future applications to cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Treating random sequential addition via the replica method

While many physical processes are non-equilibrium in nature, the theory and modeling of such phenomena lag behind theoretical treatments of equilibrium systems. The diversity of powerful theoretical tools available to describe equilibrium systems has inspired strategies that map non-equilibrium systems onto equivalent equilibrium analogs so that interrogation with standard statistical mechanical approaches is possible. In this work, we revisit the mapping from the non-equilibrium random sequential addition process onto an equilibrium multi-component mixture via the replica method, allowing for theoretical predictions of non-equilibrium structural quantities. We validate the above approach by comparing the theoretical predictions to numerical simulations of random sequential addition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Molecular-orbital-based machine learning for open-shell and multi-reference systems with kernel addition Gaussian process regression

We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correlation energies of general electronic structure theories for closed- and open-shell systems by introducing a machine learning strategy. The learning efficiency of MOB-ML(KA-GPR) is the same as the original MOB-ML method for the smallest criegee molecule, which is a closed-shell molecule with multi-reference characters. In addition, the prediction accuracies of different small free radicals could reach the chemical accuracy of 1 kcal/mol by training on one example structure. Accurate potential energy surfaces for the H10 chain (closed-shell) and water OH bond dissociation (open-shell) could also be generated by MOB-ML(KA-GPR). To explore the breadth of chemical systems that KA-GPR can describe, we further apply MOB-ML to accurately predict the large benchmark datasets for closed- (QM9, QM7b-T, and GDB-13-T) and open-shell (QMSpin) molecules.

Chemistry↗
DOE OSTI2021

Sensitivity of grassland carbon pools to plant diversity, elevated CO 2 , and soil nitrogen addition over 19 years

Significance The long-term effects of rising atmospheric carbon dioxide (CO 2 ), high rates of nitrogen deposition, and declining plant biodiversity on ecosystem carbon pools are uncertain and rarely assessed in concert yet represent key feedbacks to global climate change. In a 19-y study in an open-air grassland experiment, increasing planted species richness substantially enhanced ecosystem carbon storage, while elevated CO 2 and nitrogen addition treatments had only modest effects. Effects of the three global changes were largely additive, and stronger effects of species richness compared with CO 2 or nitrogen resulted from large enhancements in plant productivity relative to ecosystem losses. Our results suggest that biodiversity losses may influence carbon storage as much as or more than rising CO 2 or high nitrogen deposition rates.

54 ENVIRONMENTAL SCIENCES↗