SEARCH · Search NASA

Results for “Process Engineering”

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.

SourceResearch connectionFrom yearThrough year

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

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗

DOE OSTI2024

Retrofitting Holcim Ste. Genevieve Cement Plant with CO2 Capture Plant Using Air Liquide Cryocap™ FG Technology

The global cement manufacturing industry is a major contributor to carbon dioxide emissions. The International Energy Agency's "Net Zero Emissions by 2050 Scenario" identifies CCS as a major strategy for meeting that goal. This project is among the first attempts to transfer capture technology developed at coal-fired power plants to the cement industry. The main objective of the project is to execute and complete a front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separates 95% of the total CO2 emissions at the Holcim (US) Ste. Genevieve cement manufacturing facility using Air Liquide’s Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology. The Holcim Ste. Genevieve cement plant in Missouri, US, boasts one of the largest single cement production lines in the world, with a capacity of approximately 12,000 t/day. The plant currently uses traditional fuels, namely coal and petcoke. The captured CO2 will be pipeline and geological storage grade. The industrial host site emits approximately 3.0 million tonne CO2/yr. Air Liquide’s Cryocap™ technology has been developed over the last 18+ years for CO2 capture applications. It has been shown to be applicable to a variety of industrial applications (e.g., steel, cement, SMR, Fluidized Catalytic Crackers (FCCs)). Cryocap™ FG consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The project team is led by the Prairie Research Institute at the University of Illinois at Urbana-Champaign. The tasks include: complete FEED study for retrofitting the industrial facility with a carbon capture system to support developing a detailed cost estimate; business case analysis outlining the anticipated revenue and credits if projects was built and operated; technoeconomic analysis (TEA) outlining how capture system achieves DOE capture goals; and life cycle (LCA) analysis demonstrating zero net carbon emissions. The FEED study was successfully completed. This includes completing the process basis of design; preliminary engineering; outside battery limits (OSBL) detailed engineering including a Zero Liquid Discharge (ZLD) wastewater treatment system; inside battery limits (ISBL) detailed engineering [1]. An overall project capital cost estimate within a -20%/+30% accuracy was developed. The major contributors to the Total Plant Cost (TPC), by system, are the costs associated with the Outside Battery Limit (OSBL) section of the plant which includes a new river water intake structure and a Zero Liquid Discharge (ZLD) system. By cost category, the major contributors to the TPC are equipment and subcontractor costs, followed closely by engineering, construction management, home office and contractor fees. The TEA has been created to reflect the findings of the project. It analyzes the economic performance of the Cryocap™ technology by reviewing the estimated capital costs, operating cost, and revenue. The Cost of Capture (COC) associated with the Cryocap™ technology for 95% CO2 capture, when considering NETL 2018 economic assumptions (42/58 debt/equity ratio, 5.15% interest on debt and 1.42% return on equity in real dollars) and 2022 economic assumptions (42/58 debt/equity ratio, 8.82% interest on debt and 4.90% return on equity in real dollars) was found to be much lower than that for the DOE-NETL’s base-line cases. The highest contributors to the COC are annualized capital expenditures (CAPEX) and electricity consumption which can be offset by using lower cost renewable sources. The LCA was conducted using OpenLCA which is an open-source software that is recommended by NETL. The database utilized for this study was a modified version of TRACI 2.1 (developed by the US. Environmental Protection Agency’s National Risk Management Research Laboratory and modified by NETL). The Cryocap™ FG technology does not consume fuels in significant quantities and does not utilize specialized chemical solvents subject to decomposition, such as those utilized in amine-based carbon capture systems. The Cryocap™ FG technology mainly utilizes electricity as its energy input; hence, its calculated emissions are mainly associated with the generation of electricity offsite and are dependent on the energy matrix of the grid at the time of project implementation. The water consumption impact of the Cryocap™ FG is mostly for makeup of the water lost by evaporation in the cooling tower; however, the carbon capture plant will be equipped with a ZLD system to avoid effluent streams and minimize water consumption. The successful construction and operation of this plant based on this study results will provide a means to demonstrate an economically attractive and transformational capture technology that can be used to retrofit existing plants and be deployed at new plants.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Revealing the Defect‐Driven Ferroelectric Mechanisms of Aluminum Nitride

Wurtzite III-nitride compounds are CMOS-compatible with widespread industrial interest to exercise ferroelectricity, despite their polar structure being highly resistant to polarization reversal. Here, we induce and tune ferroelectric properties in w-AlN via direct-write ion-beam processing, using nanoscale patterned defect engineering as a post-growth alternative to conventional cation substitution. Nanometric piezoresponse spectroscopy of the focused He + beam patterned defect concentrations in ferroelectric Al 0.92 B 0.08 N measures a localized 10x enhancement in effective piezoresponse and 40% reduction in switching barrier. The irradiation-induced point defects convert piezoelectric AlN into a ferroelectric system with site-saturated nucleation and raise the dielectric susceptibility, switched polarization, and effective piezoelectric coefficient. Enhanced defect-lattice interactions in AlN increase carrier conduction and phonon scattering loss but preserve long-range crystallinity. Here, based on atomistic analysis of nudged elastic band density functional theory calculations and reactive force field simulations, both nitrogen vacancies and defect complexes disrupt bond ordering, facilitating a line-by-line low-barrier switching of pristine AlN.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Reactivity of net-zero carbon alcohol fuels and their corresponding aldehyde intermediates on PGM-based commercial oxidation catalysts for lean-burn emissions control

Alcohol net-zero carbon fuels will play a significant role in decarbonization of the hard-to-electrify transportation sectors. However, the combustion process in alcohol-fueled engines generate toxic aldehydes. For commercialization of net-zero carbon fuels on engines, compliance with the stringent U.S. EPA regulations is necessary. Here, this contribution focuses on reactivity of alcohols and aldehydes on commercial diesel oxidation catalysts (DOC) to inform selection of future net-zero carbon fuels. Alcohol (and aldehyde) light-off temperatures were measured on aged DOCs under full synthetic engine-exhaust conditions. Methanol was the most reactive, while ethanol completely oxidized at higher temperatures. Alcohols typically formed less reactive aldehyde intermediates. DRIFTS revealed strongly adsorbing surface formates and acetates during methanol and ethanol oxidation, respectively, resulting in inhibition effects. Preliminary alcohol oxidation mechanisms combining flow reactor and DRIFTS observations are presented. Aldehydes inhibited CO oxidation. Minimal N 2 O formation was observed for the alcohols investigated.

Alcohol oxidation↗

DOE OSTI2026

Facile synthesis of Co(OH)2 nanoneedle arrays grown on stainless steel for industrial electrochemical oxygen evolution reaction

The electrochemical oxygen evolution reaction (OER) is a critical half-reaction in a variety of energy conversion and storage applications, however, OER suffers from sluggish kinetics due to the four proton-electron transfer processes. To remedy this, interfacial engineering proves an effective strategy to design high active OER catalysts. Herein, we report a facile synthesis of Co(OH)2 nanoneedle (Co-NN) arrays grown on stainless steel (SS) via a one-step hydrothermal reaction, and the resultant impressive OER performance. Particularly, the Co-NN/SS needs 267, 307, and 576 mV overpotentials to reach 10, 100, and 1000 mA cm−2 in 1 M KOH & room temperature, and the overpotentials drop to 199, 257, and 283 mV to achieve the same current densities in 30 wt% KOH & 80 °C. Additionally, an alkaline water electrolysis (AWE) cell coupled with Co-NN/SS anode and PtRu/NiMo cathode only requires 1.65 and 1.73 V iR-free cell voltage to reach 1.0 and 2.0 A cm−2, respectively. The sterling OER performance could be attributed to four possible reasons, the Fe in SS surface tailoring the electronic properties of Co(OH)2, the mixed metal oxides on SS surface accelerating surface reconstruction of Co(OH)2 nanoneedles into CoOOH active species, a Ni-rich surface layer formation cooperatively boosting the OER activity, and a local electric field effect concentrating reactants on the tip surface and accelerating the mass transfer. This work provides a facile approach for synthesizing highly efficient OER catalysts for industrial applications by interfacial engineering.

Lyu, Xiang [ORNL] (ORCID:0000000208673248)↗

DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗

DOE OSTI2025

Engineered Barrier System Research Activities at SNL: FY25 Report

This report describes research and development (R&D) activities conducted at Sandia National Laboratories (SNL) during Fiscal Year 2025 (FY25) specifically related to the Engineered Barrier System (EBS) Properties & Processes Work Package in the Spent Fuel and High-Level Waste Disposition (SFHLWD) Campaign supported by the United States (U.S.) Department of Energy (DOE). SNL activities focus on understanding EBS component evolution and interactions within the EBS, as well as interactions between the host media and the EBS. The team represented in this report consists of individuals from SNL, Argonne National Laboratory (Advanced Photon Source), and Vanderbilt University. The activities represented in this report include development of anion sorbent materials for buffer formulations, properties of pure bentonite and bentonite mixtures, and characterization of cement interfaces relevant to the EBS. The SNL EBS activities also leverage interactions with EBS teams from other national laboratories, and international collaborations to ensure that the DOE program is active and abreast of the latest advances in nuclear waste disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Ambipolar Transport in Polycrystalline GeSn Transistors for Complementary Metal-Oxide-Semiconductor Applications

Group-IV alloy GeSn is a promising material for electronic and optoelectronic applications due to its compatibility with both Si substrates and established Si fabrication processes. This study focuses on polycrystalline GeSn (10% Sn), which offers a cost-effective, large-area, and versatile alternative to epitaxial GeSn. We demonstrate ambipolar transport behavior in polycrystalline GeSn thin film transistors, achieving electron and hole field-effect mobilities reaching up to 0.05 cm 2 /Vs and 2.05 cm 2 /Vs, respectively. Through temperature-dependent analysis, we elucidate the underlying mechanism of this phenomenon, which we attribute to quantum tunneling between the Schottky barrier contact and the channel, as well as potential barriers between the grain boundaries of this polycrystalline film, thereby advancing the understanding of polycrystalline GeSn's electrical properties. Furthermore, this work highlights the potential of ambipolar transport as a technique to employ towards the development of GeSn complementary metal-oxide-semiconductor field-effect transistors, promising to simplify and reduce the cost of GeSn manufacturing processes for edge computing and sensing applications.

42 ENGINEERING↗

DOE OSTI2025

Emergent properties of magnons coupled to microwave photons (Final Technical Report)

Studying the emergent properties of hybrid quantum material platforms holds great promise for advancing quantum technologies and transforming our ability to control quantum mechanical interactions. A key development in recent years is the recognition that magnons – the elementary quanta of spin waves – can serve as fundamental building blocks in quantum systems. Understanding the mechanisms behind the generation and control of hybrid quasiparticles based on magnons could pave the way for engineering new materials for quantum coherent processing and quantum computing. This research project focused on the precise control of light-matter interactions in magnetic hybrid systems and nanostructures, where light is carried by microwave photons and matter by magnons in engineered magnetic metamaterials. Furthermore, we investigated hybridized magnon interactions in magnetic nanostructures and devices. To this end, the project has developed new measurement techniques and systematically studied novel material systems for efficient magnon-photon coupling. A key focus was uncovering the fundamental mechanisms governing magnon-photon and magnon-phonon interactions – critical for utilizing magnons as coherent information transducers between carriers. Specifically, this research addressed: 1. Investigate the dispersion and collective properties of magnon hybrid systems in new material systems. 2. Develop magnonic hybrids with non-zero wavevectors and achieve effective control of magnon-polariton properties through engineered magnonic behaviors. 3. Determine how spin-orbit torques interact with electromagnetic fields in the strong coupling regime. This work generated new insights into the physics of magnonic hybrid systems and their emergent properties by broadening the range of material platforms and measurement techniques used to study magnon-photon and magnon-magnon coupling. The findings deepen our understanding of magnon-polaritons and lay the groundwork for novel spintronic devices with potential applications in quantum information science.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

High-Energy and High-Power NMP-Free, Designer NMC 811 Cathodes with Ultra-Thick Architectures Processed by Electrophoretic Deposition

This project focused on electrode engineering and reducing the weight of inactive components in the battery cells. Additionally, the project focused on optimizing the ‘electrophoretic deposition’ technique developed by PPG industries for aqueous processing of electrodes. During this project team has screened several binders suitable for electrophoretic deposition of electrodes. Additionally, we developed a nice strategy to deposit a low cost and scalable oxide coating on the surface of cathode materials. ORNL team performed the research under this CRADA at DOE’s Battery Manufacturing Facility (BMF) at ORNL.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

High-Energy and High-Power NMP-Free, Designer NMC 811 Cathodes with Ultra-Thick Architectures Processed by Electrophoretic Deposition

25 ENERGY STORAGE↗

DOE OSTI2025

Process and environmental safety of thermochemical conversion of biomass

Biomass presents a promising opportunity for converting waste into valuable energy, fuels, and chemicals through various thermochemical processes, including hydrothermal carbonization, hydrothermal liquefaction, pyrolysis, gasification, and combustion. However, these processes operate under extreme conditions, introducing significant safety hazards that necessitate meticulous management to prevent accidents. This review discusses potential hazards, risk mitigation strategies, and safety management practices, emphasizing the importance of integrated safety measures into the design and operation of these processes. It also highlights the critical need for robust safety engineering and environmental management strategies tailored to each thermo-chemical process. As these processes transition from laboratory to industrial scale, there is an imperative to develop a clear and concise pathway for emerging industries to achieve regulatory compliance, achieve safety certification, and enable effective stewardship of potential fugitive emissions. By addressing safety and environmental concerns, stakeholders can optimize economic benefits, rural development, and achieve sustained domestic energy generation benefits offered by biomass conversion technologies. Further research on plant design optimization, operational safety, environmental evaluation standardization, and innovative waste management solutions will support the safe and effective scaling of these technologies, ultimately contributing to sustainable management and resource recovery.

09 - BIOMASS FUELS↗

DOE OSTI2025

Requirements Framework for Cyber-Informed Engineering

The existing requirements frameworks or models cater to the existing practices. However, they fall short in directly using them for Cyber informed engineering. Therefore, this paper develops and presents a comprehensive framework that can be used for Cyber informed Engineering during the requirements phase. We describe the existing requirements process and models, then develop a requirements framework for cyber informed engineering.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Thermo-hydraulic steam pipe models for district heating simulations: Simplifications to balance accuracy and simulation speed

Steam piping networks are essential for optimizing performance in industrial processes and district heating systems. However, dynamic models that balance thermo-hydraulic accuracy with computational efficiency remain limited. In response, this paper presents a new discretized steam pipe model based on the plug flow approach, capturing key thermo-hydraulic behaviors while simplifying steam phase change processes. Implemented in Modelica, the model accurately calculates temperature and pressure distributions along steam pipelines. To improve computational efficiency for district-scale simulations, five model simplifications are introduced: lumped thermo-hydraulic functions, empirical correlations, fluid state approximations, steady-state dynamics and inclusion of flow derivatives. These simplified models achieve 85%-98% accuracy in predicting pressure drop and condensation losses, including dynamic condensate behavior during pipe warm-up—a factor often overlooked in existing models. The models support diverse network configurations, scaling effectively to systems with multiple distribution pipes and connected building loads. Discrete models provide detailed insights but exhibit a cubic increase in simulation time as the network scales by N connected building O(N 2.42 ). In contrast, lumped models simulate 10–28 times faster than discrete, offering quadratic scaling of simulation time O(N 1.73 ). However, they still require 6 times more computation time than a lossless network, highlighting the inherent computational challenges of modeling compressible fluid flow. In conclusion, the steady-state lumped variant, with its near-linear scalability in computational time O(N 1.01 ), emerges as an efficient solution for preliminary design evaluations and extensive parametric studies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

AI-Driven Crack Detection for Remanufacturing Cylinder Heads Using Deep Learning and Engineering-Informed Data Augmentation

Detecting cracks in cylinder heads traditionally relies on manual inspection, which is time-consuming and susceptible to human error. As an alternative, automated object detection utilizing computer vision and machine learning models has been explored. However, these methods often face challenges due to a lack of sufficiently annotated training data, limited image diversity, and the inherently small size of cracks. Addressing these constraints, this paper introduces a novel automated crack-detection method that enhances data availability through a synthetic data generation technique. Unlike general data augmentation practices, our method involves copying cracks from one location to another, guided by both random and informed engineering decisions about likely crack formations due to cyclic thermomechanical loads. The innovative aspect of our approach lies in the integration of domain-specific engineering knowledge into the synthetic generation process, which substantially improves detection accuracy. We evaluate our method’s effectiveness using two metrics: the F2 score, which emphasizes recall to prioritize detecting all potential cracks, and mean average precision (MAP), a standard measure in object detection. Experimental results demonstrate that, without engineering insights, our method increases the F2 score from 0.40 to 0.65, while maintaining a stable MAP. Incorporating detailed engineering knowledge further enhances the F2 score to 0.70 and improves MAP to 0.57, representing increases of 63% and 43%, respectively. These results confirm that our approach not only mitigates the limitations of traditional data augmentation but also significantly advances the reliability and precision of crack detection in industrial settings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Strategies for Superconducting Transmon Qubits with Millisecond T1 Relaxation Time

Enhancing coherence in superconducting transmon qubits requires suppressing dielectric loss and quasiparticle-mediated dissipation at metal–substrate, metal–vacuum, and substrate–vacuum interfaces. We recently demonstrated a five-fold enhancement of the energy relaxation time (T₁) by encapsulating Nb thin films with a low-loss passivation layer that inhibits NbOₓ formation, thereby reducing two-level system (TLS) participation at the metal surface. To extend T₁ into the millisecond regime, we are implementing a comprehensive materials- and process-level optimization strategy. This includes engineered substrate surface treatments, evaluation of alternative low-loss superconducting and dielectric material stacks, development of ultra-low-loss capping layers, and redesigns of transmon geometries to suppress electric-field participation ratio in lossy regions. Additionally, we are pioneering novel etching processes to further lower surface participation ratios. We are also exploring novel Josephson-junction materials and device layouts to enhance coherence further. We report T₁ measurements from these efforts, with the leading devices achieving relaxation times>1 ms.

Crisa, Francesco↗

DOE OSTI2026

Strategies for Superconducting Transmon Qubits with Millisecond T1 Relaxation Time

Crisa, Francesco↗

DOE OSTI2025

Large‐Scale 2D Perovskite Nanocrystals Photodetector Array via Ultrasonic Spray Synthesis

Abstract 2D perovskite (PVSK) single crystals have received significant attention due to their unique optical and optoelectronic properties. However, current synthesis methods face limitations, particularly in large‐area fabrication, which remain critical barriers to practical applications. In this study, the synthesis of red/green/purple‐blue‐colored 2D PVSK nanocrystals over a large area (4‐inch wafer) and the fabrication of high‐performance photodetector arrays are presented via a facile yet efficient spray‐coating approach with a liquid‐bridge transport effect. The photodetector array achieves 100% working yield, high photo‐responsivity (1.5 × 10 6 A W −1 ) and specific‐detectivity (1.1 × 10 16 Jones) with competitive photomapping characteristics. An intelligent vision system for automatic shape recognition is further demonstrated with a recognition rate exceeding 90%. This study provides significant advances in the scalable synthesis of nanoscale 2D PVSK crystals, their integration into large‐area optoelectronic devices, and their potential use in artificial‐intelligence systems.

Lee, Yoon Ho [Davidson School of Chemical Engineer↗