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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 1,603 records · Page 89
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DOE OSTI2021

Construction of Lattice Strain in Bimetallic Nanostructures and Its Effectiveness in Electrochemical Applications

Bimetallic nanocrystals (NCs), associated with various surface functions such as ligand effect, ensemble effect, and strain effect, exhibit superior electrocatalytic properties. The stress-induced surface strain effect can alter binding strength between the surface active sites and reactants as well as their intermediates, and the electrochemical performance of bimetallic NCs can be significantly facilitated by the lattice-strain modification via their morphologies, sizes, shell-thickness, surface defectiveness as well as compositions. Here in this review, an overview of fundamental principles, characterization techniques, and quantitative determination of the surface lattice strain is provided. Various strategies and synthesis efforts on creating lattice-strain-engineered bimetallic NCs, including the de-alloying process, atomic layer-by-layer deposition, thermal treatment evolution, one-pot synthesis, and other efforts are also discussed. It is further outlined how the lattice strain effect promotes electrochemical catalysis through the selected case studies. The reactions on oxygen reduction reaction, small molecular oxidation, water splitting reaction, and electrochemical carbon dioxide reduction reactions are focused. In particular, studies of lattice strain arisen from core–shell nanostructure and defectiveness are highlighted. Lastly, the potential challenges are summarized and the prospects of lattice-strain-based engineering on bimetallic nanocatalysts with suggestion and guidance of the future electrocatalyst design are envisioned.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Modeling nuclear processes by Simulink

Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Industrial Assessment Centers - Small Manufacturers Reduce Energy & Increase Productivity

Since 1976, the Industrial Assessment Centers (IACs), administered by the US Department of Energy, have supported small and medium-sized American manufacturers to reduce energy use and increase their productivity and competitiveness. The 24 IACs, located at premier engineering universities around the country (see below), send faculty and engineering students to local small and medium-sized manufacturers to provide no-cost assessments of energy use, process performance and waste and water flows. Under the direction of experienced professors, IAC engineering students analyze the manufacturer’s facilities, energy bills and energy, waste and water systems, including compressed air, motors/pumps, lighting, process heat and steam. The IACs then follow up with written energy-saving and productivity improvement recommendations, with estimates of related costs and payback periods.

Success, Alumni, Sign Up, Industrial, Assessment, ↗
DOE OSTI2015

Are X-rays the key to integrated computational materials engineering?

The ultimate dream of materials science is to predict materials behavior from composition and processing history. Owing to the growing power of computers, this long-time dream has recently found expression through worldwide excitement in a number of computation-based thrusts: integrated computational materials engineering, materials by design, computational materials design, three-dimensional materials physics and mesoscale physics. However, real materials have important crystallographic structures at multiple length scales, which evolve during processing and in service. Moreover, real materials properties can depend on the extreme tails in their structural and chemical distributions. This makes it critical to map structural distributions with sufficient resolution to resolve small structures and with sufficient statistics to capture the tails of distributions. For two-dimensional materials, there are high-resolution nondestructive probes of surface and near-surface structures with atomic or near-atomic resolution that can provide detailed structural, chemical and functional distributions over important length scales. Furthermore, there are no nondestructive three-dimensional probes with atomic resolution over the multiple length scales needed to understand most materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Pilot-Scale Silicone Process for Low-Cost Carbon Dioxide Capture. Final Scientific/Technical Report

GE Global Research has developed, over the last 8 years, a platform of cost effective CO 2 capture technologies based on a non-aqueous aminosilicone solvent (GAP-1m). As demonstrated in a previous funded DOE project (DE-FE0007502), the GAP-1m solvent has increased CO 2 working capacity, lower volatility and corrosivity than the benchmark aqueous amine technology. The current report describes the cooperative program between GE Global Research (GE GRC), and the National Carbon Capture Center (NCCC) to design, construct, and operate a pilot-scale process using GAP-1m solvent to demonstrate its performance at 0.5 MWe. (i) Performance of the GAP-1m solvent was demonstrated in a 0.5 MWe pilot with real flue gas for over 900 hrs. of operation using two alternative desorption designs: a Continuous Stirred Tank Reactor (CSTR), and a Steam Stripper Column (SSC). The CSTR is a one-stage separation unit with reduced space requirements, and capital cost. The alternative is a multi-stage separation column, with improved desorption efficiency. Testing the two desorber options allowed us to identify the most cost effective, and space efficient desorber solution. (ii) CSTR Campaign: The CSTR desorber unit was designed, fabricated and integrated with the pilot solvent test unit (PSTU), replacing the PSTU Steam Stripper Column at NCCC. Solvent management and waste water special procedures were implemented to accommodate operation of the non-aqueous solvent in the PSTU. Performance of the GAP-1m solvent with the CSTR was demonstrated for over 500 hrs. while varying temperature of the desorption (230 – 265 oF), solvent circulation rate (GAP-1m : CO 2 (molar) = 1.5 – 4), and flue gas flow rates (0.2 – 0.5 MWe). Solvent carry-over in the CO 2 product was minimized by maintaining water content below 5 wt.%, and desorption pressure at 7 psig. CO 2 capture efficiency achieved was 95% at 0.25 MWe (GAP-1m : CO 2 = 4 (molar), 230 oF desorption), and 65% at 0.5 MWe (GAP-1m : CO 2 (molar) = 1.5, 248 oF). Solvent loss was dominated by thermal degradation of the rich solvent. (iii) Steam Stripper Column Campaign: Higher expected cost of the solvent vs. aqueous amines makes solvent management a top priority to maintain the low cost for the process. During the testing of the GAP-1m solvent with the CSTR, thermal degradation of the rich solvent was found to be the main mechanism in solvent loss. Small amounts of water in the working solution were found to be an effective way to enable steam stripping, thereby lowering desorption temperature, and hence reducing thermal degradation. Steam stripping also increased working capacity by 30% due to a more efficient desorption. The concept was first tested in a glass stripping column (lab scale, GE GRC), optimized in a continuous bench scale system (2 kWe, GE GRC), and demonstrated in a 0.5 MWe PSTU at NCCC. No special system modifications were required to the PSTU to accommodate the testing of the non-aqueous GAP-1 solvent with the regenerator column. SSC was found to be more robust towards solvent entrainment (H 2 O < 35 wt.%). 90 – 95% CO 2 capture efficiency was achieved under stoichiometric conditions at 0.5 MWe (235 oF desorption, 2 psig and 19 wt. % H 2 O). Both CO 2 capture efficiency and specific duty reached optimum conditions at 18 wt.% H 2 O. Low amine degradation (< 0.05 wt.%/day) was recorded over 350 hrs. of operation. Controlled water addition to GAP-1m solvent decreased the desorption temperature, thermal degradation, and improved the CO 2 working capacity due to more efficient absorption and desorption processes. Under these conditions, the GAP-1m solvent exhibited a 25% increased working capacity, and 10% reduction in specific steam duty vs. MEA, at 10 oF lower desorption temperature. (iv) Techno-economic Analysis: The pilot-scale PSTU engineering data were used to update the capture system process models, and the techno-economic analysis was performed for a 550 MW coal fired power plant. The 1st year CO 2 removal cost for the aminosilicone-based carbon-capture process was evaluated at $48/ton CO 2 using the steam stripper column. This is a 20% reduction compared to MEA, primarily due to lower overall capital cost. CO 2 cost using the CSTR desorber is dominated by the economics of the solvent make-up. The steam stripper desorber is the preferred unit operation due to a more efficient desorption, and reduced solvent make-up rate. Further reduction in CO 2 capture cost is expected by lowering the manufacturing cost of the solvent, implementing flowsheet optimization and/or implementing the next generation aminosilicone solvent with improved stability and increased CO 2 working capacity.

0.5 MW Pilot↗
DOE OSTI2026

PERFORMANCE ANALYSIS OF AN ENGINEERING SCALE HYDROTHERMAL LIQUEFACTION SYSTEM

This work evaluates the Modular Hydrothermal Liquefaction System (MHTLS), an engineering-scale, integrated continuous HTL plant operated at the Pacific Northwest National Laboratory (PNNL), for converting realistic wet wastes into energy-dense biocrudes. The production campaigns discussed here processed algae, sewage sludges, lignocellulosic blends, Industrial food waste, and engineered food-waste slurries at 350?°C and around 200?bar, with nominal feed rates of ~12?L?h?¹. We report biocrude yields and composition, establish mass and elemental (C, N) balances, and quantify energy performance via heater duties, heat-exchanger behavior, and system-level efficiencies. Biocrudes contained 76–80?wt?% C (dry, ash-free) with HHVs of 38-41?MJ?kg?¹, substantially higher than feed materials HHVs of 16.6–26.1?MJ?kg?¹ and approaching petroleum fuels. Dry, ash-free biocrude yields of 32–53?wt?% corresponded to 43–71?wt?% carbon yields, with 18–40?wt?% of feed carbon routed to the aqueous phase. Thermal efficiencies were 50-65%, and total energy efficiencies, including reactor heat input, were 35-55%. A counter-current tube-in-tube heat exchanger delivered U values of 200–450?W?m?²?K?¹, with fouling-induced declines impacting heat recovery and heater duty. The analysis highlights three priorities for the process intensification of HTL: robust, fouling-resistant heat recovery, hydrodynamically suitable reactor and heat-exchanger designs, simplified and predictable solids management, and biocrude-water separation.

Biocrude production↗
DOE OSTI2017

PARALLEL PERTURBATION MODEL FOR CYCLE TO CYCLE VARIABILITY PPM4CCV

This code consists of a Fortran 90 implementation of the parallel perturbation model to compute cyclic variability in spark ignition (SI) engines. Cycle-to-cycle variability (CCV) is known to be detrimental to SI engine operation resulting in partial burn and knock, and result in an overall reduction in the reliability of the engine. Numerical prediction of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are required to accurately capture the in-cylinder turbulent flow field, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In the new technique, the strategy is to perform multiple parallel simulations, each of which encompasses 2-3 cycles, by effectively perturbing the simulation parameters such as the initial and boundary conditions. The PPM4CCV code is a pre-processing code and can be coupled with any engine CFD code. PPM4CCV was coupled with Converge CFD code and a 10-time speedup was demonstrated over the conventional multi-cycle LES in predicting the CCV for a motored engine. Recently, the model is also being applied to fired engines including port fuel injected (PFI) and direct injection spark ignition engines and the preliminary results are very encouraging.

Ameen, Muhsin Mohammed↗
DOE OSTI2025

Linear Quantum Coupler for Clean Bosonic Control

Quantum computing with superconducting circuits relies on high-fidelity driven nonlinear processes. An ideal quantum nonlinearity would selectively activate desired coherent processes at high strength, without activating parasitic mixing products or introducing additional decoherence. The wide bandwidth of the Josephson nonlinearity makes this difficult, with undesired drive-induced transitions and decoherence limiting qubit readout, gates, couplers, and amplifiers. Significant strides have recently been made into building better “quantum mixers,” with promise being shown by Kerr-free three-wave mixers that suppress driven frequency shifts, and balanced quantum mixers that explicitly forbid a significant fraction of parasitic processes. We propose a novel mixer that combines both these strengths, with engineered selection rules that make it essentially linear (not just Kerr-free) when idle, and activate clean parametric processes even when driven at high strength. Furthermore, its ideal Hamiltonian is simple to analyze analytically, and we show that this ideal behavior is first-order insensitive to dominant experimental imperfections. We expect this mixer to allow significant advances in high-𝑄 control, readout, and amplification.

Quantum circuits↗
DOE OSTI2018

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyber infrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyber infrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate, maintain, and distribute MRML based resource descriptions. Once all of the resource topologies are absorbed by the RCE, a connected graph of the full distributed system topology is constructed, which forms the basis for computation and workflow processing. The RCE includes a Modular Computation Element (MCE) framework which allows for tailoring of the computation process to the specific set of resources under control, and the services desired. The input and output of an MCE are both model data based on MRS/MRML ontology and schema. Some of the RAINS project accomplishments include: Development of general and extensible multi-resource modeling framework; Design of a Resource Computation Engine (RCE) system which includes the following key capabilities; Absorb a variety of multi-resource model types and build integrated models; Novel architecture which uses model based communications across the full stack for all Flexible provision of abstract or intent based user facing interfaces; Workflow processing based on model descriptions; Release of the RCE as an open source software; Deployment of RCE in the University of Maryland/Mid-Atlantic Crossroad ScienceDMZ in prototype mode with a plan under way to transition to production; Deployment at the Argonne National Laboratory DTN Facility in prototype mode; Selection of RCE by the DOE SENSE (SDN for End-to-end Networked Science at the Exascale) project as the basis for their orchestration service.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Feature Based Qualification (FBQ) of Wire Arc Additively Manufactured (WAAM) 17-4PH Martensitic Stainless Steels

The Department of Defense (DOD) programs of records desire to reduce the time and cost of the development and delivery loop in metal additive manufacturing (AM), including establishing forwarded AM capabilities. The success of these efforts relies on a robust and qualified process. To achieve this, the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center Materials Engineering (GVME) needs to be able to quickly evaluate, test, and develop feedstocks, processes, and parts. This report is directed towards demonstrating the need for a framework for metal AM processes, defining and exploring geometries for metal AM process qualification, testing resultant deposition, and delivering actionable data.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Low Temperature Waste Form for Supplemental Immobilization of Hanford Low Activity Waste - 17485

The Hanford site has approximately 56 million gallons of radioactive waste stored in 177 underground storage tanks. The Hanford Waste Treatment and Immobilization Plant (WTP) is being constructed to treat the waste but will only have sufficient capacity to treat about one-third of the Low Activity Waste (LAW) portion within the anticipated time-frame for completing the waste treatment mission. The LAW vitrification facility will need to be supplemented with additional LAW vitrification capacity or an alternate LAW immobilization technology. The LAW immobilization technologies considered must be capable of treating approximately 65% of Hanford's LAW and will be evaluated with respect to facilities required, quantity of final waste forms and secondary wastes produced, waste form performance data, technical viability, and life cycle cost and schedule estimates. A low temperature (i.e. non-thermal) waste form and treatment process is being evaluated to provide the additional LAW immobilization capacity. Low temperature, cementitious waste forms have been evaluated previously for immobilizing Hanford tank waste but were not further developed for various reasons. Over the past few years the Hanford Tank Operations Contractor has conducted a technology development program to evaluate a low temperature waste form for immobilization of Hanford LAW including formulation development and testing with a range of simulant compositions spiked with radioactive and hazardous contaminants of concern (COCs). The objectives of this program include; developing a low temperature waste form formulation that is robust with respect to both waste form performance and processing properties over a range of LAW compositions, demonstrating waste form performance with real waste, and conducting Engineering Scale testing to advance the technical maturity of the low temperature immobilization process. The purpose of this paper is to report progress toward these objectives, in particular testing with real waste including additives to enhance technetium and iodine retention. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Strain engineered pyrochlore at high pressure

Strain engineering is a promising method for next-generation materials processing techniques. Here, we use mechanical milling and annealing followed by compression in diamond anvil cell to tailor the intrinsic and extrinsic strain in pyrochlore, Dy 2 Ti 2 O 7 and Dy 2 Zr 2 O 7 . Raman spectroscopy, X-ray pair distribution function analysis, and X-ray diffraction were used to characterize atomic order over short-, medium-, and long-range spatial scales, respectively, under ambient conditions. Raman spectroscopy and X-ray diffraction were further employed to interrogate the material in situ at high pressure. High-pressure behavior is found to depend on the species and concentration of defects in the sample at ambient conditions. Overall, we show that defects can be engineered to lower the phase transformation onset pressure by ~50% in the ordered pyrochlore Dy 2 Zr 2 O 7 , and lower the phase transformation completion pressure by ~20% in the disordered pyrochlore Dy 2 Zr 2 O 7 . These improvements are achieved without significantly sacrificing mechanical integrity, as characterized by bulk modulus.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Distillation-based Droplet Modeling of Non-Ideal Oxygenated Gasoline Blends: Investigating the Role of Droplet Evaporation on PM Emissions

In some studies, a relationship has been observed between increasing ethanol content in gasoline and increased particulate matter (PM) emissions from vehicles equipped with spark ignition engines. The fundamental cause of the PM increase seen for moderate ethanol concentrations is not well understood. Ethanol features a greater heat of vaporization (HOV) than gasoline and also influences vaporization by altering the liquid and vapor composition throughout the distillation process. A droplet vaporization model was developed to explore ethanol's effect on the evaporation of aromatic compounds known to be PM precursors. The evolving droplet composition is modeled as a distillation process, with non-ideal interactions between oxygenates and hydrocarbons accounted for using UNIFAC group contribution theory. Predicted composition and distillation curves were validated by experiments. Detailed hydrocarbon analysis was applied to fuel samples and to distillate fractions, and used as input for the initial droplet composition. With composition calculated throughout the distillation, the changing HOV and other physical properties can be found using reference data. The droplet can thus be modeled in terms of energy transfer, which in turn provides the transient mass transfer, droplet temperature, and droplet diameter. Model predictions suggest that non-ideal vapor-liquid equilibrium along with an increase in HOV can alter the droplet composition evolution. Results predict that the presence of ethanol causes enrichment of the higher boiling fractions (T90+) in the aromatic components as well as lengthens the droplet lifetime. A simulation of the evaporation process in a transient environment as experienced within an engine cylinder predicts a decrease in mixing time of the heaviest fractions of the fuel prior to spark initiation, possibly explaining observations linking ethanol to PM.

02 PETROLEUM↗
DOE OSTI2018

Gene stacking of multiple traits for high yield of fermentable sugars in plant biomass

Second-generation biofuels produced from biomass can help to decrease dependency on fossil fuels, bringing about many economic and environmental benefits. To make biomass more suitable for biorefinery use, we need a better understanding of plant cell wall biosynthesis. Increasing the ratio of C6 to C5 sugars in the cell wall and decreasing the lignin content are two important targets in engineering of plants that are more suitable for downstream processing for second-generation biofuel production. Here, we have studied the basic mechanisms of cell wall biosynthesis and identified genes involved in biosynthesis of pectic galactan, including the GALS1 galactan synthase and the UDP-galactose/UDP-rhamnose transporter URGT1. We have engineered plants with a more suitable biomass composition by applying these findings, in conjunction with synthetic biology and gene stacking tools. Plants were engineered to have up to fourfold more pectic galactan in stems by overexpressing GALS1, URGT1, and UGE2, a UDP-glucose epimerase. Furthermore, the increased galactan trait was engineered into plants that were already engineered to have low xylan content by restricting xylan biosynthesis to vessels where this polysaccharide is essential. Finally, the high galactan and low xylan traits were stacked with the low lignin trait obtained by expressing the QsuB gene encoding dehydroshikimate dehydratase in lignifying cells. In conclusion, the results show that approaches to increasing C6 sugar content, decreasing xylan, and reducing lignin content can be combined in an additive manner. Thus, the engineered lines obtained by this trait-stacking approach have substantially improved properties from the perspective of biofuel production, and they do not show any obvious negative growth effects. The approach used in this study can be readily transferred to bioenergy crop plants.

09 BIOMASS FUELS↗
DOE OSTI2013

Efficiency bounds for nonequilibrium heat engines

We analyze the efficiency of thermal engines (either quantum or classical) working with a single heat reservoir like an atmosphere. The engine first gets an energy intake, which can be done in an arbitrary nonequilibrium way e.g. combustion of fuel. Then the engine performs the work and returns to the initial state. We distinguish two general classes of engines where the working body first equilibrates within itself and then performs the work (ergodic engine) or when it performs the work before equilibrating (non-ergodic engine). We show that in both cases the second law of thermodynamics limits their efficiency. For ergodic engines we find a rigorous upper bound for the efficiency, which is strictly smaller than the equivalent Carnot efficiency. I.e. the Carnot efficiency can be never achieved in single reservoir heat engines. For non-ergodic engines the efficiency can be higher and can exceed the equilibrium Carnot bound. By extending the fundamental thermodynamic relation to nonequilibrium processes, we find a rigorous thermodynamic bound for the efficiency of both ergodic and non-ergodic engines and show that it is given by the relative entropy of the nonequilibrium and initial equilibrium distributions. These results suggest a new general strategy for designing more efficient engines. We illustrate our ideas by using simple examples. -- Highlights: ► Derived efficiency bounds for heat engines working with a single reservoir. ► Analyzed both ergodic and non-ergodic engines. ► Showed that non-ergodic engines can be more efficient. ► Extended fundamental thermodynamic relation to arbitrary nonequilibrium processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Additive Manufacturing of Fuel Injectors

Additive manufacturing (AM), also known as 3D-printing, has been shifting from a novelty prototyping paradigm to a legitimate manufacturing tool capable of creating components for highly complex engineered products. An emerging AM technology for producing metal parts is the laser powder bed fusion (L-PBF) process; however, industry manufacturing specifications and component design practices for L-PBF have not yet been established. Solar Turbines Incorporated (Solar), an industrial gas turbine manufacturer, has been evaluating AM technology for development and production applications with the desire to enable accelerated product development cycle times, overall turbine efficiency improvements, and supply chain flexibility relative to conventional manufacturing processes (casting, brazing, welding). Accordingly, Solar teamed with EWI on a joint two-and-a-half-year project with the goal of developing a production L-PBF AM process capable of consistently producing high-nickel alloy material suitable for high temperature gas turbine engine fuel injector components. The project plan tasks were designed to understand the interaction of the process variables and their combined impact on the resultant AM material quality. The composition of the high-nickel alloy powders selected for this program met the conventional cast Hastelloy X compositional limits and were commercially available in different particle size distributions (PSD) from two suppliers. Solar produced all the test articles and both EWI and Solar shared responsibility for analyzing them. The effects of powder metal input stock, laser parameters, heat treatments, and post-finishing methods were evaluated. This process knowledge was then used to generate tensile, fatigue, and creep material properties data curves suitable for component design activities. The key process controls for ensuring consistent material properties were documented in AM powder and process specifications. The basic components of the project were: • Powder metal input stock: Powder characterization, dimensional accuracy, metallurgical characterization, and mechanical properties evaluation. • Process parameters: Laser parameter effects, post-printing heat-treatment development, mechanical properties evaluation, and post-finishing technique. • Material design curves: Room and elevated temperature tensiles, low cycle fatigue, and creep rupture properties curves generated. • AM specifications: Key metal powder characteristics, laser parameters, and heat-treatment controls identified.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DME-to-Propane Mixture Effects on a Light Duty Compression Ignition Engine

Fuels that can be produced in a sustainable manner are of high interest because they can provide an essential step toward net zero emissions vehicles. This study examines the combustion of two such fuels, Dimethyl Ether (DME) and propane, in a compression ignition, 4-cylinder, 2.2L engine running with mixtures of DME-to-Propane ranging of 100%-0%, 85%-15%, 75%-25%, and 65%-35% by weight. Testing was conducted at 2000rpm - 100Nm, an important representative point in the FTP certification cycle. For each fuel mixture, conditions tested include sweeps of boost, EGR and injection pressure. Here, tests are mainly conducted at a constant combustion timing with CA10 of -1 deg with respect to TDC, with an engine controller combustion feedback system based on in-cylinder sampling of pressure. Trends of NOx, HC, and CO are similar for the range of DME-to-propane, from 100%-0% to 75%-25%. Boost and injection pressures had the most notable impact on the heat release traces. Higher boost, from stoichiometric to lean resulted in approximately a 3-5% increase on cycle efficiency. Fuel injection pressures resulted in about 1% gain per 200bar. Results also illustrated that EGR is effective in reducing NOx but causes notable degradation of cycle efficiency. The emissions for DME-propane mixtures with 65%-35% had a different trend, with CO and HC exceeding the runs with lower propane content by 2 to 3-fold. As propane content increases, the pressure rise rates become higher, and with 65%-35% mixtures, rates easily exceed 12bar/deg. The increased rise rates correlate with early injection timings but the rates can be reduced, with higher boost and lower injection pressures. The result of the approach, however, leads to lower thermal efficiencies, decreasing efficiency by over 5% between neat DME and the highest propane ratios.

Combustion and combustion processes↗