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At least 307 records · Page 17

Crack mitigation and wear performance of high-strength steel coatings deposited by high-speed laser cladding

This article investigates the fabrication of defect-free Rockit® 606, a high‑carbon, vanadium- and chromium-enriched precipitation-hardening martensitic steel coating, using high-speed laser cladding (HSLC). Compared to conventional laser cladding, HSLC offers higher deposition efficiency, improved coating quality, minimal thermal distortion, and a reduced heat-affected zone. Various HSLC parameters—including laser power, travel speed, powder feed rate, and overlap distance—were optimized to achieve superior coating properties. Microstructural analysis revealed solidification cracks in coatings deposited on carburized steel, regardless of processing parameters. However, preheating the substrate to 250 °C effectively eliminated cracking by reducing thermal gradients. The coatings exhibited a columnar dendritic microstructure, with coarser dendrites near the substrate and finer dendrites towards the surface. Hardness measurements confirmed that all coatings significantly exceeded the industry-specified threshold of 60 HRC, with preheating having minimal effect on overall hardness distribution. Reciprocating sliding wear tests demonstrated a substantial improvement in wear resistance for the defect-free HSLC coatings compared to baseline carburized steel. These findings underscore the potential of HSLC for producing high-performance, wear-resistant coatings suitable for industrial applications.

36 MATERIALS SCIENCE↗

Plant-wide modeling and techno-economic analysis of a direct non-oxidative methane dehydroaromatization process via conventional and microwave-assisted catalysis

Direct non-oxidative methane dehydroaromatization (DHA) process via conventional and microwave (MW)-assisted thermo-catalytic catalysis is studied. Rate models for methane DHA reactions, including the effect of catalyst deactivation, are developed by using the in-house experimental data. Model results for gas concentration profile and catalyst deactivation are in good agreement with the experimental data. This rate model is then used for the development of dynamic multi-scale, multi-physics commercial-scale reactor models. Total number of fixed bed reactors desired for a cyclic steady state process is estimated. Plant-wide models are then developed for conventional and MW-assisted processes for producing products of desired specifications. Techno-economic analysis of the methane DHA process is undertaken. Economics of these methane DHA processes are compared with the typical multi-step natural gas to aromatics production process via methanol synthesis. Sensitivity of internal rate of return (IRR) and net present value (NPV) to various economic and process parameters such as plant scale, desired rate of return, reactor cost, feedstock and utility cost, catalyst variable cost, and MW reactor cost is studied. Here, electric equivalent efficiency of the conventional methane DHA process is found to be 69.2 % and 67.3 % at 750 °C and 800 °C, respectively, while the MW-assisted methane DHA process has the electric equivalent efficiency of 48.9 % at 800 °C. IRRs of the conventional methane DHA process at 750 °C and 800 °C, and MW-assisted process are 15.2 %, 17.5 %, and 18.8 %, respectively for a methane feed flowrate of 19,782 kg/h, while the IRR of the multi-step natural gas to aromatics production process is estimated to be 0 % for the same plant scale. Impact of change in the methane price, electricity price, and catalyst cost is found to be considerable on the process economics, while the cost of the MW reactor is found to have negligible impact.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BioC2G Tool v1

The BioC2G tool provides an interface for running technoeconomic analyses and life-cycle assessments of biofuel and bioproduct production pathways. Models for the pathways are currently built into the tool: limonene, limonane, bisabolene, bisabolane, ethanol, isoprenol, DMCO, and HEFA. Additionally, a "Custom" option is available for analyzing a bioproduction pathway not included among the built-in examples. Users must supply key product properties and process parameters. Three types of model runs are available in the tool: minimum selling price (MSP), water consumption, and greenhouse gas (GHG) emissions. Running the MSP model yields a breakdown of MSP by major process stage of production, along with a a table of estimated capital expenditures (CAPEX) and annual operating expenditures (OPEX). Running the water consumption and GHG models yields a breakdown of water consumed and carbon emissions respectively, per unit of end product. A breakdown of these metrics by major process stage is also provided. Model run results can be viewed in the web interface numerically and graphically, as well as downloaded in CSV format. Detailed documentation on model methodology and assumptions is also available for download.

Huntington, Tyler↗

Process Intensification for Nanostructure Aluminum Extrusions

A new technology called Shear Assisted Processing and Extrusion (ShAPE™), pioneered at the Pacific Northwest National Laboratory (PNNL), has the potential to revolutionize the US extrusion industry. Maturation of the ShAPE™ process would create a new cross cutting US manufacturing technology that advances three key the objectives within AMO; namely, nanomaterials processing, process intensification, and materials for extreme and harsh environments. PNNL and SCM Metals Products, Inc. (SCM), a division of Kymera International, will collaborate to mature the ShAPE™ extrusion process beyond TRL 3 to increase the likelihood of its adoption by industry. PNNL’s custom (one-of-a-kind in the world) ShAPE™ machine will be used to extrude round rods of high strength aluminum alloy feedstock powder provided by SCM. As proof-of-concept, PNNL has previously extruded 5 mm diameter rods with SCM aluminum alloy powder AL-12.4TM. This project aims to scale up the process to a diameter of 25 mm while retaining the excellent mechanical properties achieved for the 5 mm diameter rods. The degree of process intensification with ShAPE™ will also be estimated. The primary objectives of this project are as follows. 1) Fabricate 25 mm diameter nanostructured extrusions in bulk, directly from AL-12.4TM aluminum alloy powder without the need for canning, degassing, compaction, and other intermediate steps typical of powder metallurgy extrusion. 2) Achieve a microstructure with an ultrafine grained (UFG <1 µm) aluminum matrix having refined and homogenously distributed nanoscale second phases. 3) Show that the ram force can be significantly reduced compared to conventional powder metallurgy extrusion of the same material and estimate the extent of process intensification that may be possible with ShAPE™. 4) Demonstrate improved high-temperature mechanical properties compared to conventional extrusion of the same material. The following tasks will be undertaken to achieve these objectives. PNNL will develop the die set and process parameters necessary to fabricate Al-12.4TM extrusions with a 25 mm diameter. Microstructural analysis will be performed by PNNL while mechanical testing will be conducted by SCM. With information learned from the process development and characterization, PNNL will perform an estimate of the degree of process intensification that may be possible with ShAPE™.

42 ENGINEERING↗

Enhanced Catalyst Durability for the Oxidative Production of Biobased Chemicals (Cooperative Research and Development Final Report)

This CRADA will facilitate technology maturation for NREL-developed atomic layer deposition (ALD) coated catalyst materials that are tailored for durability during the oxidative production of biobased chemicals. This project will address optimizing process parameters for scaling aluminum oxide (Al 2 O 3 ) ALD coated catalysts, demonstrating ALD coated catalyst performance for biomass oxidation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗

Hydrothermal liquefaction of Cyanidioschyzon merolae and Salicornia bigelovii Torr.: The interaction effect on product distribution and chemistry

Hydrothermal liquefaction (HTL) has proven to be a promising technology for processing wet biomass into valuable biofuel intermediates. We investigated the influence of HTL process parameters on the individual and co-liquefaction of Salicornia bigelovii Torr. (SL) and Cyanidioschyzon merolae (CM) biomass and their respective product properties and characteristics. SL and CM biomasses were subjected to HTL conditions of process temperatures (250–350 °C), 10 wt% solid loading, 30 min reaction time, and co-liquefaction ratios (80–20, 50–50, 20–80, CM-SL, respectively). The individual maximum HTL biocrude yields for CM (34.63 wt%) and SL (7.63 wt%) were obtained at 300 °C. In both cases, biocrude oils had a higher carbon and hydrogen content relative to those of the original biomass. The HHV (higher heating value) values for the biocrude samples ranged from 24.2 to 33.12 MJ/kg, which were significantly higher than those of the original biomasses. A positive synergistic effect was observed during the co-liquefaction of two biomasses, where the experimental yield of biocrude oil was higher than the theoretical value. During the co-liquefaction experiments, a maximum biocrude yield of 32.95 wt% was obtained at 300 °C and 80–20 CM-SL biomass mix ratio. Co-liquefaction led to an increase in the energy content of the co-liquefied biocrude oil and a higher energy recovery rate. Finally, the properties of HTL products and biomasses were determined with TGA, CHN elemental analyzer, GC/MS, bomb calorimeter, HACH Spectrophotometer, and ICP OES.

09 BIOMASS FUELS↗

Unveiling the influence of selective-area-regrowth interfaces on local electronic properties of GaN p-n junctions for efficient power devices

Here, we report correlated nanoscale mapping of the structure, composition, and properties of regrown GaN p-n junctions to identify how etching and non-planar regrowth processes limit diode performance via the introduction of unintentional dopants and defect states. p-GaN was selectively regrown in n-GaN trenches with SiO 2 masks of variable mask-to-trench-width ratio. Dilute Al layers were periodically introduced during regrowth as markers of the growth interface. Correlated nanoscale mapping of doping, conductivity, and dopant complexes was achieved with atom probe tomography (APT), scanning spreading resistance microscopy (SSRM), and cathodoluminescence (CL) spectroscopy, respectively. The Al marker layers, detected by APT, enabled reconstruction of the faceted growth interface and correlation of the dopant concentration with position and time. The p-GaN growth rate is proportional to the mask-to-trench width ratio while the dopant incorporation rate is invariant. At trench edges, magnesium incorporation is suppressed, and oxygen incorporation enhanced, due to preferential incorporation on the semi-polar growth surface, leading to compensation and less abrupt p-n junctions; the SiO 2 mask is a source of oxygen. Residual etch damage below the regrowth interface induces n-type and p-type conductivity, creating leakage pathways. The non-uniform Mg incorporation is driven by crystal anisotropy and is thus inherent to non-planar regrowth, but can be mitigated by engineering the regrowth interface and process parameters. The unprecedented integration of spatially resolved mapping of dopants, impurities, conductivity, and carrier type is a powerful approach to discriminating distinct factors that limit the performance of regrown diodes, enabling the rational optimization of process and device design.

36 MATERIALS SCIENCE↗

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

Failure Modes and Effects Analysis of Biorefinery Pathways

This talk provides an overview of failure modes and effects analysis (FMEA) development and implementation as a systematic criticality and risk assessment tool for biorefinery pathways within the FCIC. This supports a quality by design (QbD) approach, and this talk provides a high-level overview of the results for the FMEA evaluation focused on the generation of pine residue materials for high-temperature pyrolysis conversion. the FMEA interviews included two approaches. The first approach was based around the entire system of unit operations giving a wholistic system level view. The second approach used detailed interviews from individual unit operation within the system allowing for specific failures for individual system components. These two approaches provide different resolutions of information about the reliability and risk. The FMEA results focused on failures associated with meeting critical quality attributes (CQAs) identified for the high temperature conversion of loblolly pine residues and were supplemented with experimental data supporting process upsets and reliability also collected within the consortium. Estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score were gathered through the FMEA interviews, and were combined to understand the overall process risk metrics and where technology, process, and knowledge improvements are needed in order to de-risk emerging biorefineries.

09 BIOMASS FUELS↗

Correlation of SWIR imaging with LPBF 304L stainless steel part properties

In the Laser Powder Bed Fusion (LPBF) process, the local thermal history can vary significantly over a part as the heat transfer characteristics and the laser scan path are geometry dependent. The variations introduce the potential for defects that lead to part failure, some of which are difficult to identify non-destructively with common ex-situ evaluation techniques. These defects include significant microstructural and mechanical property differences in the part interiors. In this paper, thermal features are extracted from in-situ Short-Wave Infrared (SWIR) imaging measurements to compile voxel based part representations and understand how the complexities in the thermal history affect part performance. The deviations in thermal features due to different laser processing parameters and complex scan pathing are explored. Empirical correlations are developed to map thermal features with the engineering properties (bulk yield strength, area percentage porosity, and local state) of 304L stainless steel parts manufactured by LPBF. Processing modes (insufficient melting and keyholing) are determined by mapping part property measurements with multiple thermal features. Generating the relationships between thermographic measurements and resulting SLM part properties lays the foundation for in-situ part qualification.

36 MATERIALS SCIENCE↗

Long-Term Static and Dynamic Corrosion Stability of Nonwetting Surfaces

Superhydrophobic surfaces (SHSs) and lubricant-infused surfaces (LISs) are two classes of nonwetting surfaces that have drawn attention due to their advanced functional properties including corrosion inhibition. Yet there is a conspicuous lack of corrosion study of SHSs and LISs with respect to their fabrication and material parameters, especially at high temperatures and under dynamic flow conditions over long durations, which is sought to be addressed in this article. Considering copper SHSs and LISs, a full factorial combinatorial study of two facile texturing processes, electrodeposition and etching, two different functionalization agents, stearic acid and mercaptan, and two types of infused lubricants, Krytox 104 and DOWSIL 510, is presented, encompassing over 650 measurements on 90 tested surfaces. All fabricated surfaces demonstrated water repellency with a contact angle above 150° and a sliding angle below 7°. For the first time, the study examines high-temperature corrosion stability and long-term corrosion durability of the nonwetting surfaces in both static fluid and dynamic turbulent flow conditions over a period of 30 days. Here, LISs and SHSs are shown to provide excellent corrosion inhibition over all tested corrosion conditions, with negligible presence of corrosion species on the surfaces and no deterioration of the texturing. The surfaces are also shown to rejuvenate easily to the initial wettability and corrosion resistance values. This study provides valuable insights into the selection of materials and processing parameters for the fabrication of nonwetting surfaces for the application of interest.

Copper↗

Formation of functionally graded steel by laser powder bed fusion via in-situ carbon doping

Additive Manufacturing (AM) enables functional integration by combining multiple components into a single part to shorten assembly time, reduce weight, and improve performance. Laser Powder Bed Fusion (LPBF) is an important AM method due to excellent spatial resolution, surface finish, and material properties without the need for extensive post-processing. Functional integration could be enhanced by spatial tuning of properties, but LPBF cannot readily vary material composition. Here, this paper addresses a method to add spatial composition control by printing small quantities of dopants via liquid carrier prior to laser fusion. The impact of carbon black suspension added to select regions of a Stainless Steel 316 L powder bed on melt pool dimension, hardness, and porosity is reported. The distribution of the carbon between the doped and plain layers and the resulting spatial variation in hardness is measured. Optical microscopy and composition analysis show that the carbon dispersed uniformly within the layer of deposition and diffused as little as 50 μm in the build direction. Keyhole conditions dramatically increase the inter-layer transport of the dopant. The added carbon increased hardness by >50 %. Porosity increased in doped regions but remained below 1.5 % for the best processing parameters. These results demonstrate that the composition of LPBF parts could be controlled in 3-dimensions using a dopant that is soluble in the melt pool. Additional work will be required to evaluate different dopant materials and optimize processing conditions for full density, but microalloying with soluble dopants appears to be a plausible solution to enhance functional integration with LPBF.

36 MATERIALS SCIENCE↗

Aggregation Dynamics of Colloidal Particles in Tin Perovskite Crystalline Film Formation

We present an approach to understanding the crystallization of tin-based perovskite films for photovoltaic applications, starting from precursor suspensions processed via spin-coating. By integrating colloidal theory with the fluid dynamics of suspensions, this approach elucidates the influence of both chemical variables and process parameters on the crystallization pathways of perovskite suspensions and the resulting microstructural features of the solid films. Specifically, the incorporation of SnCl 2 as an additive was found to accelerate crystallization, whereas tBP induces a slowdown of the process leading, however, to a marked improvement in film uniformity and microstructural quality.

Crystallization↗

Nanocrystalline Materials: Synthesis, Characterization, Properties, and Applications

Nanostructuring is a commonly employed method of obtaining superior mechanical properties in metals and alloys. Compared to conventional polycrystalline counterparts, nanostructuring can provide remarkable improvements in yield strength, toughness, fatigue life, corrosion resistance, and hardness, which is attributed to the nano grain size. In this review paper, the current state-of-the-art of synthesis methods of nanocrystalline (NC) materials such as rapid solidification, chemical precipitation, chemical vapor deposition, and mechanical alloying, including high-energy ball milling (HEBM) and cryomilling was elucidated. More specifically, the effect of various process parameters on mechanical properties and microstructural features were explained for a broad range of engineering materials. This study also explains the mechanism of grain strengthening using the Hall-Petch relation and illustrates the effects of post-processing on the grain size and subsequently their properties. This review also reports the applications, challenges, and future scope for the NC materials.

36 MATERIALS SCIENCE↗

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel–Bronze Composites

In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors’ level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors’ level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating.

36 MATERIALS SCIENCE↗

Data-Driven Approaches for Bead Geometry Prediction Via Melt Pool Monitoring

In the realm of additive manufacturing, the selection of process parameters to avoid over and under deposition entails a time-consuming and resource-intensive trial-and-error approach. Given the distinct characteristics of each part geometry, there is a pressing need for advancing real-time process monitoring and control to ensure consistent and reliable part dimensional accuracy. Here, this research shows that support vector regression (SVR) and convolutional neural network (CNN) models offer a promising solution for real-time process control due to the models’ abilities to recognize complex, non-linear patterns with high accuracy. A novel experiment was designed to compare the performance of SVR and CNN models to indirectly detect bead height from a coaxial image of a melt pool from a single-layer, single bead build. The study showed that both SVR and CNN models trained on melt pool data collected from a coaxial optical camera can accurately predict the bead height with a mean absolute percentage error of 3.67% and 3.68%, respectively.

36 MATERIALS SCIENCE↗

Coupling of Spark Plasma Sintering with Advanced Modeling to Enable Process Scale-Up: LDRD Final Project Poster

Electric-field assisted sintering (EFAS) manufacturing techniques reduce energy usage requirements, fabricate near-net-shape parts, and produce bulk nanostructured materials through rapid heating and cooling rates achievable through Joule heating. Process parameters of pulsed DC voltage and constant pressure are applied through stainless steel rams and graphite tooling to the ceramic yttrium oxide powder to be sintered. Our high-fidelity modeling code application advances manufacturing for extreme environments by enabling process-informed design and improving microstructure consistency through multiphysics multiscale process-structure-property-performance correlation simulations.

36 MATERIALS SCIENCE↗