Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Manufacturing processes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Assessment of the grindability of robocast silicon carbide

The demand for high-performance lightweight optics has driven interest in silicon carbide (SiC) due to its exceptional thermal stability, hardness, and strength-to-weight ratio. This study investigates the potential of robocasting, an additive manufacturing process, as a viable method for producing lightweighted SiC components for optical applications. Four samples with varied starting powder phases (α and β) and sintering conditions were fabricated and evaluated. Post-sintering surface and form were assessed using coherence scanning interferometry (CSI) and coordinate measuring machine (CMM) techniques. A three-stage grinding process was applied to each sample, with surface roughness assessed at each stage. Results demonstrate that samples with predominantly α-phase SiC and smaller particle sizes achieved superior surface finish, particularly sample D2-α-2135 °C, which displayed the lowest post-grinding Sq value of 0.178 µm. The analysis also indicated no significant print-through effect from the lightweighting structure, or print artifacts, at this stage of grinding. However, β-phase samples showed poorer grindability, increased surface roughness, and pitting. These findings suggest that phase composition and particle size are critical for achieving the desired surface quality in robocast SiC optics. Future work will incorporate additional samples and finer grinding wheels to refine surface quality further, supporting the development of SiC for high-precision optical applications.

Barrett, Taylor [ORNL]↗
DOE OSTI2024

High-temperature lean Cu alloys with Cr-to-Nb atomic ratio of 2

Two Cu-Cr-Nb alloys, denoted as alloy 1 (comprising Cu-0.89 at% Cr-0.42 at% Nb) and alloy 2 (comprising Cu-1.84 at% Cr-0.99 at% Nb), were produced through a series of manufacturing processes including vacuum induction melting, melt spinning, consolidation, brazing, and baking, with both alloys aimed at achieving a nominal Cr-to-Nb atomic ratio of 2. Microstructural characterization using transmission electron microscopy and X-ray diffraction identified the cubic C15 Laves-phase Cr 2 Nb as the dominant precipitate in both alloys, cross-validated by thermodynamic calculations and atomistic simulation-based density functional theory (DFT). Besides cubic C15 Cr 2 Nb, hexagonal C14-phase Cr 2 Nb and α-BiF3 cubic structured Cr 3 Nb were also observed in the alloys, including a coherent interface formed between the Cr 3 Nb precipitate and the Cu matrix. The hardness of the alloys increases, and the electrical conductivity decreases with increasing alloying addition content; two practical equations described the trends. Further DFT simulations revealed that the electrical conductivity (conductance) of the Cu/Cr 2 Nb interface is an order of magnitude higher than the intrinsic Cu high-angle grain boundaries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Slug-flow synthesis of NCMA: Effect of substitution of cobalt with aluminum on the electrochemical performance of Ni-rich cathode for lithium-ion battery

Nickle-rich Li[Ni 1-x-y Co x Mn y ]O 2 (x, y≤0.1) (NCM) layered materials are known as promising cathode materials for next-generation lithium-ion batteries and electric vehicles owing to their high-reversible capacity and operating voltage of up to 3.6 vs Li/Li + . However, issues, such as irreversible phase transition, cation mixing, microcrack formation, thermal and structural stability of the material prevent its widespread adoption. Although, cation doping is a well-known technique to enhance the electrochemical performance of the NCM-based cathode material, the performance of the material is very sensitive to the doping amount. In this study, three Al-doped quaternary Ni-rich cathode materials Li[Ni 0.85 Co (0.1-x) Mn 0.05 Al x ]O 2 (where, x=0–0.04) (NCMA) are synthesized through three-phase slug-flow based continuous manufacturing process followed by high temperature calcination to study the effect of Aldoping on the performance of the cathode material while reducing Co. The slug flow-based production platform has several advantages, like particle size uniformity, high production rate, and homogeneity in elemental distribution. It is found that with an increase in Al content, the specific capacity decreases but the cyclic stability and rate capability increases. Furthermore, optimum Al-doping not only compensates for the adverse effect of low Co by decreasing the extent of cation mixing, but it also minimizes the electrode polarization and cracking of the particles.

25 ENERGY STORAGE↗
DOE OSTI2020

Ultra-efficient polymer binder for silicon anode in high-capacity lithium-ion batteries

As a highly promising anode material for high-capacity lithium-ion batteries (LIBs), the low electronic conductivity and large volume variation of silicon (Si) make the slurry-coating Si based electrode requiring high content of “inert” materials and suffering rapid capacity fading. In this work, a polyimine, synthesized via one-step condensation reaction, has been demonstrated as an ultra-efficient polymer binder that can resolve the above issues. The polyimine binder containing Si electrode delivers superior electrochemical performance: a delithiation specific capacity of 804.4 mAh g –1 with capacity retention of 82.4% after 1000 cycles at the current density of 2 A g –1 . The high efficiency of polyimine binder for Si electrode has also been demonstrated with ultrahigh weight ratio of “active” material to “inert” material (R A/I ). The electrode with 95 wt% of Si (95Si/Polyimine, R A/I = 19) reveals a reversible delithiation capacity of 2114 mAh g –1 (capacity retention ~ 80.4%) over 200 cycles at the current density of 400 mA g –1 . Even at the high current density of 2 A g –1 , a delithiation capacity of 1087.8 mAh g –1 after 500 cycles can be obtained. Molecular simulations and atomic force microscopy (AFM) indentation are utilized to investigate the ultra-efficiency of polyimine binder. With simple manufacturing process and ultra-efficient binder performance, the designed polyimine binder will be definitely meaningful in achieving low-cost and high-capacity LIBs with prolonged cycle life.

25 ENERGY STORAGE↗
DOE OSTI2023

TRISO fuel performance analysis: Uncertainty quantification toward optimization

Tri-structural isotropic (TRISO) fuel particles are a fuel form being considered for potential use in next-generation nuclear reactors (i.e., high-temperature gas-cooled reactors). Though the TRISO fuel manufacturing process has continually advanced in recent years, particle comparisons still reveal statistical variations and uncertainties in terms of geometric configurations and material properties. Given that the physical processes ongoing in TRISO fuel particles during reactor operation are highly correlated with each other, a small degree of uncertainty in one model may lead to significant uncertainty in another. This makes appropriate uncertainty quantification of TRISO fuel particles essential. However, one may wonder about the extent to which the current version of TRISO particles has been optimized, and whether any room remains for further improvements. This paper quantifies TRISO fuel performance model uncertainties that stem from geometric and material data. For this analysis, the BISON code was used, and the Advanced Gas Reactor (AGR)-2 experiment served as a reference case. A total of 10 5 calculations was performed for the uncertainty and optimization analysis, altering the geometric and material data within their uncertainty range. Lastly, the optimization potential of TRISO particles is evaluated from a fuel performance perspective.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A visco-plastic constitutive model for accurate densification and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near net shape parts with high material utilization and uniform microstructures. Despite being used frequently to produce small-scale components, the application of PM-HIP to large-scale components is limited due to inadequate understanding of its complex mechanisms that cause unpredictable post-HIP shape distortions. A computational model can provide necessary information about the intermediate and final stages of the HIP process that can help understand it better and make accurate predictions. Generally, two types of computational models are employed for PM-HIP of metal powders, namely, plastic and visco-plastic models. Between these, the plastic model is preferred due to its cheaper calibration approach requiring less experimental data. However, the plastic model sometimes produces incorrect predictions when slight variations of the HIP conditions are encountered in practical situations. Therefore, this work presents a visco-plastic model that addresses these limitations of the plastic model. A novel modified calibration approach is employed for the visco-plastic model that utilizes less experimental data than existing approaches. With the new approach, the data requirement is same for both plastic and visco-plastic models. This also enables a quantitative comparison of plastic and visco-plastic models, which have been only qualitatively compared in the past. When calibrated with the same experimental data, both the models are found to produce similar results. In conclusion, the calibrated visco-plastic model is applied to several complex geometries, and the predictions are found to be in good agreement with experimental observations.

Hot isostatic pressing↗
DOE OSTI2026

A fast and robust computational modeling approach for density and shape predictions in powder metallurgy hot isostatic pressing

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near-net-shape parts with high material utilization and uniform microstructures. PM-HIP is frequently used for producing small-scale parts with complicated geometries and is potentially economical for producing large-scale parts. However, excessive post-HIP shape distortions can reduce its effectiveness and economic advantage, especially for larger parts. A PM-HIP computational model can predict and help mitigate these distortions. However, due to complex deformation mechanisms and thermo-mechanical coupling present in PM-HIP processes, these non-linear computational models sometimes become numerically unstable. The numerical instabilities in these models can lead to very slow convergence or no convergence at all, which often translates to slow and unreliable models. These limitations are more pronounced in large models with complicated geometries. Hence, in this work, an alternative modeling approach is presented that improves numerical stability and computational performance. The presented approach achieves these improvements through approximating the fully coupled thermo-mechanical PM-HIP model as a decoupled model and adding inertial damping to the model’s mechanical part. In conclusion, a comparison with the fully coupled model indicated a slight dip in prediction accuracy (<5% error) but significant improvements in numerical stability (>20 times larger time step size) and computational performance (5-10 times speed-up with less computational resource usage) when using the presented approach.

Hot isostatic pressing↗
DOE OSTI2021

Autonomous nondestructive evaluation of resistance spot welded joints

The application of non-destructive evaluation approaches has attracted strong interests in modern automotive industries. Here, we present an autonomous deep-computing framework to analyze raw videos from infrared systems and to predict weld nugget shape and size with unprecedented accuracy and speed. In a comprehensive training and testing experiment with 90 videos (seven sets of welding material stack-ups), a new method was developed to assemble sufficient datasets for neural network training. Our framework successfully predicts all the nugget shapes with F1 scores that range from 0.84 to 0.92. The total training time on Nvidia DGX station takes less than 10 min for each set of welding material stack-up. The real inference time of an individual dataset (with 30 video frames) takes about 0.005 s. The procedure and methods developed in the study can be applied to other image-based weld property prediction, as well as other manufacturing processes. Furthermore, our well-trained neural networks take limited memory resources (2.3 MB) and are suitable for embedded microprocessors for in-situ welding quality control as edge computing within an intelligent welding framework.

42 ENGINEERING↗
DOE OSTI2023

California's harvested wood products: A time-dependent assessment of life cycle greenhouse gas emissions

Following life-cycle assessment (LCA) methodology, this study presents a state-level estimation of embodied carbon of wood products harvested in 2019 from California and subsequently processed, manufactured, transported, used, and disposed at the end-of-life (EoL). In a conventional static approach to LCA, all GHG emissions were aggregated and considered to occur at year 0 of the given time horizon (500 years in this study) and used a static characterization factor (CF). In dynamic LCA, GHG emissions occurring in different years were considered, and their global warming impact (GWI) was determined using a time-dependent CF over the selected time horizon of 500 years. Four scenarios were developed to examine the impact of EoL choices on GWI. It was found that dynamic GWI for all scenarios ranged from 0.27 to 0.93 million tonne CO₂e, which were 45–73 % lower than those estimated with static LCA approach, indicating that the static LCA approach could lead to an underestimation of the benefits of substituting wood for non-wood products, compared to those based on dynamic LCA approach. This analysis also demonstrated that the choice of EoL treatment option is a key factor affecting the estimated GWI as it directly determines the annual emission of GHGs released into atmosphere and subsequently their warming effect depending on the time harvested wood products (HWPs) spend in the horizon of assessment. Altogether, the dynamic LCA performed in this study enabled more robust interpretations of embodied carbon by including temporal boundaries associated with the HWPs life cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sustainable recycling of cathode scraps via Cyrene-based separation

Separation of cathode materials from the current collector remains a challenging task for the recycling of both spent lithium-ion batteries and cathode scraps. Dissolving the organic binder polyvinylidene difluoride (PVDF) with an organic solvent to recover both cathode materials and Al foils is an efficient and promising method. However, the use of toxic solvents limits their practical application in recycling large amounts of cathode scraps generated during the manufacturing process. Cyrene, a bioderived green solvent, is proposed here for a solvent-based separation process. This study investigated a closed-loop recovery process to reclaim cathode materials, Al foils, and PVDF binder from cathode scraps. Furthermore, the reuse of the Cyrene solvent led to a circular recycling process. Additionally, the Cyrene-based separation process embraces a sustainable electrode recovery and reuse platform and paves the way for battery recycling.

25 ENERGY STORAGE↗
DOE OSTI2021

Biological upgrading of pyrolysis-derived wastewater: Engineering Pseudomonas putida for alkylphenol, furfural, and acetone catabolism and (methyl)muconic acid production

While biomass-derived carbohydrates have been predominant substrates for biological production of renewable fuels, chemicals, and materials, organic waste streams are growing in prominence as potential alternative feedstocks to improve the sustainability of manufacturing processes. Catalytic fast pyrolysis (CFP) is a promising approach to generate biofuels from lignocellulosic biomass, but it generates a complex, carbon-rich, and toxic wastewater stream that is challenging to process catalytically but could be biologically upgraded to valuable co-products. Here, we implemented modular, heterologous catabolic pathways in the Pseudomonas putida KT2440-derived EM42 strain along with the overexpression of native toxicity tolerance machinery to enable utilization of 89% (w/w) of carbon in CFP wastewater. The dmp monooxygenase and meta-cleavage pathway from Pseudomonas putida CF600 were constitutively expressed to enable utilization of phenol, cresols, 2- and 3-ethyl phenol, and methyl catechols, and the native chaperones clpB, groES, and groEL were overexpressed to improve toxicity tolerance to diverse aromatic substrates. Next, heterologous furfural and acetone utilization pathways were incorporated, and a native alcohol dehydrogenase was overexpressed to improve methanol utilization, generating reducing equivalents. All pathways (encoded by genes totaling ~30 kilobases of DNA) were combined into a single strain that can catabolize a mock CFP wastewater stream as a sole carbon source. Further engineering enabled conversion of all aromatic compounds in the mock wastewater stream to (methyl)muconates with a ~90% (mol/mol) yield. Biological upgrading of CFP wastewater as outlined in this work provides a roadmap for future applications in valorizing other heterogeneous waste streams.

(methyl)muconates↗
DOE OSTI2020

Preparation and Characterization of Various Kraft Lignins and Impact on Their Pyrolysis Behaviors

Lignin-derived chemicals and fuel products have received much attention in the context of bio-refinery. In this study we prepared and characterized various lignin samples from black liquor (BL), a major byproduct from the pulp and paper manufacturing processes, and studied the pyrolysis behaviors of these isolated lignin samples at 600 °C under a N2 atmosphere. Three lignin samples were isolated from the Kraft pulping BL of Loblolly pine linerboard grade process (KL, obtained by direct evaporation; L10, obtained by precipitation at pH 10; L3, obtained by precipitation at pH 3), while another three were from the Kraft pulping BL of Loblolly pine bleach grade process (KB, B10, B3). The inorganic elements present in lignin samples were analyzed using an inductively coupled plasma (ICP) analyzer. The KL and KB samples contained a larger amount of inorganic elements, especially Na and S, than did the other lignin samples. Owing to large quantities of inorganic elements, the ash contents in KL and KB were higher than in the precipitated lignin samples (L10, B10, L3, and B3). These inorganic elements have a significant effect on the subsequent pyrolysis process, as a result, more extensive depolymerization of lignin occurred in KL and KB samples, leading to the formation of fewer pyrolysis oils, with lower molecular weights. NMR analyses of pyrolysis oils show that more methoxyl groups and ether bonds were cleaved, resulting in fewer methoxyl groups and aromatic C–O bonds for the KL and KB heavy oil than for the precipitated lignin heavy oil.

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

Assessment of Molten Eutectic LiF-NaF-KF Density through Experimental Determination and Semiempirical Modeling

Molten salts have favorable material properties for use in high-temperature energy systems, including thermal energy storage systems, concentrating solar power plants, nuclear reactors, and various industrial manufacturing processes. Knowledge of chemical and thermophysical property data is essential for the design and optimization of these systems, yet data are often limited or uncertain for many candidate salts due to the difficulty of thermophysical property measurements at relevant temperatures (e.g., 500–900 °C). Here, the density of molten LiF-NaF-KF eutectic is reassessed through review of previous experimental data, new density measurements from 470 to 800 °C, and semiempirical modeling. Additionally, the density was measured using the displacement technique. Compositional and temperature-dependent density estimates were calculated with a multidimensional Redlich–Kister model. The results of the new experimental measurements agree within 2% of the modeled density of molten eutectic LiF-NaF-KF. The Redlich–Kister model’s prediction shows a near-ideal density behavior for the LiF-NaF-KF system and is promising for the estimation of off-eutectic LiF-NaK-KF densities. Finally, through review of the existing literature and comparison to new measurements, recommendations are made for the density of LiF-NaF-KF.

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

Renewable and Biodegradable Polyurethane Foams with Aliphatic Diisocyanates

The transition to renewable plastics will require the development of substitutes with existing industrial standards and manufacturing processes. Polyurethanes (PU), versatile plastics, are traditionally dominated by aromatic diisocyanates, which are challenging to derive from renewable sources. However, for higher biocontent, it is crucial to utilize aliphatic diisocyanates, which can be sourced from renewable plant or algae waste streams. Historically, PU foams relied on aromatic diisocyanates for essential hard segments, resulting in desired physical properties. Here, we report the generation of high-performance renewable and biodegradable PU foams utilizing aliphatic diisocyanates and aromatic polyols, translating hard segments into the polyester polyol component using biosourced furan dicarboxylic acid (FDCA) monomers. We demonstrate that an FDCA-based PU is suitable for foams with performance characteristics that meet commercial tolerances and can biodegrade under backyard compost conditions. Here, this demonstrates steps toward redesigning traditional petrochemical-based polymers to accommodate new biological monomers.

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

SAN-Based Block Polymers as a Platform for Manufacturing Strong Isoporous Membranes

Ultrafiltration (UF) membranes are ubiquitous in water purification and bioprocessing. However, co-designing their mechanical and transport properties remains challenging because of the broad pore size distributions at the surface and within the bulk that result from nonsolvent-induced phase separation (NIPS) – their typical manufacturing process. These distributions influence the hydrodynamic resistance to water flow and the stress concentrations around the pores. Developing advanced UF membranes requires innovative molecular designs that offer control over the surface and bulk pores, as well as the mechanical properties of the load-bearing, polymer. Here, we introduce a platform for designing UF membranes by leveraging solution self-assembly of block polymers and chain architectures with pendant polar groups. The block polymers consist of a poly(styrene-co-acrylonitrile) hydrophobic block, which is known for its strength, and a poly(4-vinyl pyridine) hydrophilic block, which drives solution self-assembly. We focus on a series of block polymers with constant molecular weight, M n ≈ 115 kDa, SAN fraction, 75 wt.%, and varying acrylonitrile content, 0 to 40 mol%, to demonstrate that: (i) RAFT dispersion copolymerization of acrylonitrile and styrene provides a facile route to synthesize strong block polymers, (ii) incorporation of acrylonitrile into the hydrophobic block enhances membrane strength by facilitating chain entanglements and dipole-dipole interactions, and (iii) acrylonitrile alters the balance between membrane permeance and rejection, even when the membranes feature similar surface and bulk pores. Overall, our results provide insights into the molecular design of UF membranes with enhanced mechanical and separation properties, contributing to the development of materials for water and energy technologies.

deformation↗
DOE OSTI2021

Bifunctional Janus Particles as Multivalent Synthetic Nanoparticle Antibodies (SNAbs) for Selective Depletion of Target Cells

Monoclonal antibodies (mAb) have had a transformative impact on treating cancers and immune disorders. SNAbs However, their use is limited by high development time and monetary cost, manufacturing complexities, suboptimal pharmacokinetics, and availability of disease-specific targets. To address some of these challenges, we developed an entirely synthetic, multivalent, Janus nanotherapeutic platform, called Synthetic Nanoparticle Antibodies (SNAbs). SNAbs, with phage-display-identified cell-targeting ligands on one "face" and Fc-mimicking ligands on the opposite "face", were synthesized using a custom, multistep, solid-phase chemistry method. SNAbs efficiently targeted and depleted myeloid-derived immune-suppressor cells (MDSCs) from mouse-tumor and rat-trauma models, ex vivo. Systemic injection of MDSC-targeting SNAbs efficiently depleted circulating MDSCs in a mouse triple-negative breast cancer model, enabling enhanced T cell and Natural Killer cell infiltration into tumors. Finally, our results demonstrate that SNAbs are a versatile and effective functional alternative to mAbs, with advantages of a plug- and-play, cell-free manufacturing process, and high-throughput screening (HTS)-enabled library of potential targeting ligands.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Controlled Formation of Stacked Si Quantum Dots in Vertical SiGe Nanowires

In this work, we demonstrate the ability to fabricate vertically stacked Si quantum dots (QDs) within SiGe nanowires with QD diameters down to 2 nm. These QDs are formed during high-temperature dry oxidation of Si/SiGe heterostructure pillars, during which Ge diffuses along the pillars’ sidewalls and encapsulates the Si layers. Continued oxidation results in QDs with sizes dependent on oxidation time. The formation of a Ge-rich shell that encapsulates the Si QDs is observed, a configuration which is confirmed to be thermodynamically favorable with molecular dynamics and density functional theory. The type-II band alignment of the Si dot/SiGe pillar suggests that charge trapping on the Si QDs is possible, and electron energy loss spectra show that a conduction band offset of at least 200 meV is maintained for even the smallest Si QDs. Our approach is compatible with current Si-based manufacturing processes, offering a new avenue for realizing Si QD devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Design and Fabrication of Polyisocyanurate Foams toward Significantly Enhanced Thermal Resistivity

Developing high-performance thermal insulation is vital for addressing the ongoing global demand for reduced energy costs. Polyisocyanurate (PIR) foams are commonly used in residential and commercial buildings and in various industrial applications owing to their relatively high thermal insulation properties and fire resistivity. Here, this study aims to further improve the thermal resistivity of PIR foams by (1) incorporating low thermal conductivity blowing agents; (2) tailoring the anisotropy of their cells; (3) tuning polymeric isocyanate quantities; and (4) incorporating a facer barrier, while using steps that easily integrate into current manufacturing processes for PIR foams. The resulting PIR foams exhibit a significant enhancement in thermal resistivity, achieving initial values as high as 8.3 h·ft 2 ·°F/Btu/in., commonly abbreviated as R-8.3/in., which is a 20% improvement compared with that of commercially used PIR foams that achieve approximately R-7/in. The detailed analysis of thermal conductivity measurements, mechanical testing, and morphological characterization elucidates the structure–property relationships. The developed high-performance PIR foams provide a critical pillar for next-generation high-performance insulation, offering promising thermal insulation for buildings and many other applications that have a significant effect on global energy costs.

Anisotropic pores↗