Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “engineering process”

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 1,495 records · Page 83

Oxidation state and interfacial effects on oxygen vacancies in tantalum pentoxide

First-principles density-functional theory calculations are used to study the atomistic structure, structural energetics, and electron density near the O monovacancy (V{sub O}{sup n}; n = 0,1+,2+) in both bulk, amorphous tantalum pentoxide (a-Ta{sub 2}O{sub 5}), and also at vacuum and metallic Ta interfaces. We calculate multivariate vacancy formation energies to evaluate stability as a function of oxidation state, distance from interface plane, and Fermi energy. V{sub O}{sup n} of all oxidation states preferentially segregates at both Ta and vacuum interfaces, where the metallic interface exhibits global formation energy minima. In a-Ta{sub 2}O{sub 5}, V{sub O}{sup 0} is characterized by structural contraction and electron density localization, while V{sub O}{sup 2+} promotes structural expansion and is depleted of electron density. In contrast, interfacial V{sub O}{sup 0} and V{sub O}{sup 2+} show nearly indistinguishable ionic and electronic signatures indicative of a reduced V{sub O} center. Interfacial V{sub O}{sup 2+} extracts electron density from metallic Ta, indicating that V{sub O}{sup 2+} is spontaneously reduced at the expense of the metal. This oxidation/reduction behavior suggests careful selection and processing of both oxide layer and metal electrodes for engineering memristor device operation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Directional charge separation in isolated organic semiconductor crystalline nanowires

One of the fundamental design paradigms in organic photovoltaic device engineering is based on the idea that charge separation is an extrinsically driven process requiring an interface for exciton fission. This idea has driven an enormous materials science engineering effort focused on construction of domain sizes commensurate with a nominal exciton diffusion length of order 10 nm. Here, we show that polarized optical excitation of isolated pristine crystalline nanowires of a small molecule n-type organic semiconductor, 7,8,15,16-tetraazaterrylene, generates a significant population of charge-separated polaron pairs along the π-stacking direction. Charge separation was signalled by pronounced power-law photoluminescence decay polarized along the same axis. In the transverse direction, we observed exponential decay associated with excitons localized on individual monomers. We propose that this effect derives from an intrinsic directional charge-transfer interaction that can ultimately be programmed by molecular packing geometry.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Prediction of Cyclic Variability and Knock-Limited Spark Advance (KLSA) in Spark-Ignition (SI) Engine

Engine knock remains one of the major barriers to further improve thermal efficiency of Spark Ignition (SI) engines. Knock can be suppressed by lowering the compression ratio, or retarding the spark ignition timing, however, at an expense of efficiency penalty. SI engine is usually operated at knock-limited spark advance (KLSA) to achieve possibly maximum efficiency with given engine hardware and fuel properties, such as Research Octane Number (RON), Motor Octane Number (MON), and heat of vaporization, etc. Co-optimization of engine design and fuel properties is promising to improve the engine efficiency and predictive CFD models can be used to facilitate this optimization process. However, difficulties exist in predicting KLSA in CFD simulations. First, cyclic variability of SI engine demands that multi-cycle results are required to capture the extreme conditions. Secondly, Mach Courant-Friedrichs-Lewy (CFL) number of 1 is desired to accurately predict the knock intensity (KI), resulting in unaffordable computational cost, especially for multi-cycle simulations. In this study, a new approach to numerically predict KLSA using large Mach CFL number of 50 is proposed. This approach is validated against experimental data for a boosted Direct Injection Spark Ignition (DISI) engine at multiple loads and spark timings. G-equation combustion model coupled with well-mixed chemical kinetic model are used to predict the turbulent flame propagation and end-gas auto-ignition, respectively. Simulations run for 10 consecutive engine cycles at each condition. The results show good agreement between model predictions and experiments in terms of cylinder pressure, combustion phasing and cyclic variation. Engine knock is predicted with early spark ignition timing, indicated by significant pressure wave oscillation and end-gas heat release. Maximum Amplitude of Pressure Oscillation (MAPO) analysis is performed to quantify the KI, and the slope change point in KI extrema is used to indicate the KLSA accurately. Using a smaller Mach CFL number of 5 also results in the same conclusions thus demonstrating that this approach is insensitive to the Mach CFL number. The use of large Mach CFL number allows us to achieve fast turn-around time for multi-cycle engine CFD simulations.

Yue, Zongyu↗

Decomposition Analysis of Neodymium Loaded Resin

In an effort to understand and quantify the carbon and sulfur contents of a curium oxide production process performed in the hot cells at Oak Ridge National Laboratory’s Radiochemical Engineering Development Center, a non-radioactive surrogate was used in a similar oxide formation process. Neodymium (Nd), which was chosen as a substitute for curium, was loaded onto a Dowex 50W-X8 resin by use of ion exchange column techniques and then treated under a variety of processing conditions. The surrogate product was analyzed for carbon and sulfur impurities, using inductively coupled plasma–mass spectrometry for sulfur assessment, a LECO combustion furnace/analyzer for carbon quantification, and X-ray diffraction for compound identification. The results indicate that the carbon and sulfur contents in the Nd oxide were similar to current estimations for curium oxide using the reference hot cell process. It was also seen that the major surrogate product of the hot cell process contained sulfur in a Nd oxysulfate (Nd2O2SO4) compound. Parametric analysis of the resin decomposition process revealed that increasing the temperature to 1400°C yielded considerably better removal of carbon and sulfur.

Curium Targets↗

Interparticle Characterization of Mechanical Biomass Particle-Particle and Particle-Wall Interactions

The biomass materials industry faces significant challenges in managing material variability and its impact on storage and handling systems. Physical properties such as moisture content, particle size, and density fluctuate considerably, leading to operational issues like bridging and ratholing that disrupt material flow. These variations create a complex cascade effect throughout the process chain, affecting transportation, storage, and conversion processes. The economic consequences of this variability manifest in increased operational costs, maintenance requirements, and system downtime. Environmental factors further complicate the situation, as weather conditions and seasonal availability influence material properties and system performance. Engineers employ specialized equipment design, material characterization protocols, and pre-processing steps like size reduction and homogenization to address these challenges. A critical knowledge gap exists between continuous-level constitutive models and particle-scale behavior. This project developed a novel device to quantify interparticle mechanics between biomass particles, measuring friction and adhesion forces between particles and wall materials. The research focused on corn stover and southern pine forest residue, creating a comprehensive database of particle interactions. This breakthrough enables direct application in particle-based computational modeling, advancing the field's understanding of biomass handling characteristics and supporting the development of more reliable and efficient storage and handling systems. The project's outcomes contribute significantly to understanding biomass's mechanical and flow characteristics, particularly how variability at the particle level affects larger-scale handling operations. This knowledge is crucial for engineering feedstock supply systems that consistently meet quality and cost specifications for various conversion processes. The innovative experimental setup developed through this research represents a significant advancement in biomass characterization methodology. Providing precise measurements of particle-level interactions establishes a foundation for more accurate predictive modeling of bulk material behavior. This enhanced understanding of fundamental particle mechanics enables engineers to anticipate better and address handling challenges before they manifest in full-scale operations. This research opens new avenues for optimizing biomass handling systems through data-driven design approaches. The comprehensive database of particle interactions serves as a valuable resource for future research and development efforts, potentially leading to more efficient and cost-effective biomass processing solutions. This advancement in particle-level mechanics could revolutionize how biomass handling systems are designed and operated, contributing to more sustainable and reliable renewable energy production.

09 BIOMASS FUELS↗

Electron Linear Accelerator Additive Manufacturing

Superconducting electron linear accelerators open up new opportunities for advanced materials processing. High energy electrons penetrate deeper within materials, increase the processing depth and rate and enables production of far-from-equilibrium materials and selective processing within a material surface and subsurface. With support from the Office of Naval Research, NASA, and DoE, Mainstream Engineering commissioned a superconducting linear electron accelerator to investigate advanced materials processing and additive manufacturing. The goal of Mainstream's Electron Beam Enabled Advanced Manufacturing (EBEAM) center is to develop unique, far-from-equilibrium materials and alleviate significant technological deficiencies. We will present results of irradiating various metals and their unique material properties. Monte Carlo simulations electron beam and sample interaction were used to optimize the processing parameters and study far-from-equilibrium processing conditions. Applications include stainless steel additive manufacturing for small modular nuclear reactors and dissimilar metal bonding of corrosion-resistant cladding for next-generation molten salt reactors.

36 MATERIALS SCIENCE↗

Crystal Structure of the Ergothioneine Sulfoxide Synthase from Candidatus Chloracidobacterium thermophilum and Structure-Guided Engineering To Modulate Its Substrate Selectivity

Ergothioneine is a thiohistidine derivative with potential benefits on many aging-related diseases. The central step of aerobic ergothioneine biosynthesis is the oxidative C–S bond formation reaction catalyzed by mononuclear nonheme iron sulfoxide synthases (EgtB and Egt1). Thus far, only the Mycobacterium thermoresistibile EgtB (EgtB Mth ) crystal structure is available, while the structural information for the more industrially attractive Egt1 enzyme is not. In this paper, we reported the crystal structure of the ergothioneine sulfoxide synthase (EgtB Cth ) from Candidatus Chloracidobacterium thermophilum . EgtB Cth has both EgtB- and Egt1-type of activities. Guided by the structural information, we conducted Rosetta Enzyme Design calculations, and we biochemically demonstrated that EgtB Cth can be engineered more toward Egt1-type of activity. This study provides information regarding the factors governing the substrate selectivity in Egt1- and EgtB-catalysis and lays the groundwork for future sulfoxide synthase engineering toward the development of an effective ergothioneine process through a synthetic biology approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monitoring Radiochemical Processing Streams for the 238 Pu Supply Program with Process Pulse II

Oak Ridge National Laboratory (ORNL) is developing advanced spectroscopic and real-time monitoring capabilities to improve the timeliness of analytical measurements and process decisions for the 238Pu Supply Program. Reducing the time, resources, and costs associated with each production campaign is critical because overlapping campaigns will be required to meet the production goals of the National Aeronautics and Space Administration. Real-time, in situ analytical measurements in the heavily shielded hot cells at the Radiochemical Engineering Development Center (REDC) will allow for rapid process information feedback and operational benefits that help the 238Pu supply program scale-up production efforts. Noteworthy steps were taken during Campaign 5 to establish the ability to monitor processing streams in real time with spectrophotometry and a commercially available online monitoring software called The Unscrambler X Process Pulse II (PP) multivariate statistical process monitoring system by Camo Analytics (version 5.60). PP automates univariate-type calculations within the software itself and executes multivariate models built using The Unscrambler X (version 10.4 or newer). The Unscrambler is a commercially available data analysis software made by the same company. PP is composed of easy-to-use-tools for all personnel, including data scientists and technicians. The software can be used to plot analyte concentration profiles, spectral data, and other process variables in real time. All process data are represented in a single view with interactive charts useful for viewing how a process evolves over time.

07 ISOTOPE AND RADIATION SOURCES↗

Standard High Solids Vessel Design De-inventory Simulant Qualification

The Hanford Tank Waste Treatment and Immobilization Plant (WTP) is working to develop a Standard High Solids Vessel Design (SHSVD) process vessel. To support testing of this new design, WTP engineering staff requested that a Newtonian simulant be developed that would represent the de-inventory (residual high-density tank solids cleanout) process. Its basis and target characteristics are defined in 24590-WTP-ES-ENG-16-021 and implemented through PNNL Test Plan TP-WTPSP-132 Rev. 1.0. This document describes the de-inventory Newtonian carrier fluid (DNCF) simulant composition that will satisfy the basis requirement to mimic the density (1.18 g/mL ± 0.1 g/mL) and viscosity (2.8 cP ± 0.5 cP) of 5 M NaOH at 25 °C.1 The simulant viscosity changes significantly with temperature. Therefore, various solution compositions may be required, dependent on the test stand process temperature range, to meet these requirements. Table ES.1 provides DNCF compositions at selected temperatures that will meet the density and viscosity specifications as well as the temperature range at which the solution will meet the acceptable viscosity tolerance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗

Scalable Two–Step Production of High–Efficiency Perovskite Solar Cells and Modules

Perovskite solar cells (PSCs) fabricated in laboratories have already achieved power conversion efficiency (PCE) comparable to market-dominant crystalline silicon solar cells. However, this promising photovoltaic technology suffers from severe loss of PCE during scaling up, limiting its progress toward commercialization. One critical question is to develop scalable, low-cost, high throughput, and well-controlled production methods to deposit high-quality perovskite films. Among various approaches, two-step sequential deposition methods have their unique advantages but have been long overlooked. This review provides an overview of two-step methods for fabricating efficient and stable perovskite solar modules (PSMs). We first discuss the mechanisms of two-step perovskite conversion and advanced engineering approaches to modulate the perovskite formation process. We survey the progress of efficient PSCs prepared by different two-step methods and compare the advantages and disadvantages of each method for scalable production of PSMs. Particularly, we highlight that the vapor-based two-step methods are promising for high-throughput in-line production of PSMs. Finally, we provide insights into the challenges and outlook of the industrialization of two-step processes for producing PSMs.

14 SOLAR ENERGY↗

PanDA: Production and Distributed Analysis System

The Production and Distributed Analysis (PanDA) system is a data-driven workload management system engineered to operate at the LHC data processing scale. The PanDA system provides a solution for scientific experiments to fully leverage their distributed heterogeneous resources, showcasing scalability, usability, flexibility, and robustness. The system has successfully proven itself through nearly two decades of steady operation in the ATLAS experiment, addressing the intricate requirements such as diverse resources distributed worldwide at about 200 sites, thousands of scientists analyzing the data remotely, the volume of processed data beyond the exabyte scale, dozens of scientific applications to support, and data processing over several billion hours of computing usage per year. PanDA’s flexibility and scalability make it suitable for the High Energy Physics community and wider science domains at the Exascale. Beyond High Energy Physics, PanDA’s relevance extends to other big data sciences, as evidenced by its adoption in the Vera C. Rubin Observatory and the sPHENIX experiment. As the significance of advanced workflows continues to grow, PanDA has transformed into a comprehensive ecosystem, effectively tackling challenges associated with emerging workflows and evolving computing technologies. The paper discusses PanDA’s prominent role in the scientific landscape, detailing its architecture, functionality, deployment strategies, project management approaches, results, and evolution into an ecosystem.

97 MATHEMATICS AND COMPUTING↗

Tetravalent anti-CD20/CD3 bispecific antibody for the treatment of B cell lymphoma

Bispecific antibodies (bsAbs) are second generation antibodies for therapeutic application in immunotherapy. One of the major strategies of the bsAb platform is the recruitment of immune effector T cells by incorporating an anti-CD3 domain. A bispecific T-cell engager (BiTE), with one end having an affinity for CD3 and the other end with affinity for CD19, has been approved in the US and Europe for the treatment of acute lymphoblastic leukemia. However, due to their small size and lack of Fc region, these single-chain variable fragment (scFv) bsAbs have short half-lives in vivo. Additionally, poor solubility, structural instability, and low production yields have also become major challenges in the bulk production process. To overcome these challenges, we have engineered a tetravalent bsAb with bivalent binding specificity for the CD20 and CD3 antigen in an immunoglobulin G (IgG) format. The fusion of the anti-CD3 scFvs to the CD20 antibody via a linker-hinge domain (LHD) results in improved antibody stabilization and properties. Here we demonstrate this antibody's highly efficient cancer cell elimination in a dose-dependent manner in a CD20-expressing B lymphoblastoid cell line in vitro. Our data suggest the potential clinical application of this bsAb for the treatment of CD20-expressing B cell malignancies. - Highlights: • A bispecific antibody (bsAb) can increase immunotherapeutic efficacy. • A tetravalent bsAb with binding specificity for the CD20 and CD3 antigens is proposed. • A linker-hinge domain (LHD) within the bsAb results in improved antibody properties.

60 APPLIED LIFE SCIENCES↗

Microbial valorization of lignin to malic acid by Aspergillus niger

Lignin is the largest renewable source of aromatic carbon, yet its heterogeneity and recalcitrance limit its use in higher-value bioconversion processes. In this study, Aspergillus niger was engineered to enable the bioconversion of lignin-derived aromatics and base-catalyzed depolymerized (BCD) lignin streams into malic acid, a value-added C4 dicarboxylic acid with broad industrial relevance. Overexpression of the C4 dicarboxylate transporter C4T318 from Aspergillus oryzae enhanced malic acid secretion, while medium optimization under buffered conditions further improved the production. The engineered strain efficiently assimilated representative lignin-derived aromatics, including 4-hydroxybenzoic acid and p-coumaric acid, producing up to 3.9 g/L malic acid. Conversion of BCD lignin liquors from poplar and sorghum demonstrated effective utilization of heterogeneous aromatic mixtures, generating up to 0.82 g/L malic acid. This work demonstrates direct fungal conversion of real lignin streams into malic acid and establishes A. niger as a promising platform for sustainable lignin valorization.

Aromatic bioconversion↗

Lignin-based jet fuel and its blending effect with conventional jet fuel

Sustainable aviation fuels (SAFs) must demonstrate specific physical and chemical properties as well as material compatibility (i.e., seal swell) to be used as an aviation turbine fuel. Several alternative jet fuels incorporated in ASTM D7566 are comprised mainly of n/iso-alkanes and can only be blended up to 50 vol% due to material compatibility and density issues. Prior work illustrated the ability of cycloalkanes to replace aromatics’s role in material compatibility. Here, we report the first archival documentation of a feedstock and chemical process to yield a product composition able to complement existing SAF ASTM D7566 annexes. A lignin-based jet fuel (LJF) blend components is generated and composed of mostly C7-C18 mono, di, and tri-cycloalkanes. The neat LJF was blended with conventional jet fuel at 10 vol% (LJF blend) to simulate an ASTM “Fast Track” evaluation process. Fuel properties that are critical to engine operability (ATSM D4054 Tier 3 & 4) were either predicted or experimental tested based on the volume availability. All LJF blend’s critical properties fall within the experience range of conventional jet fuel, with o-ring swelling exceeding the typical range of conventional fuels. Here, these results in total support the potential use of this LJF pathway to complement other SAF pathways and achieve 100% drop-in SAF.

09 BIOMASS FUELS↗

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗

Mechanistic Insights into Copper(I) and Copper(II) Cation Exchange Reactions in CdSe Nanoplatelets

In this study, we investigated the synthesis of copper selenide nanoplatelets (NPLs) through a cation exchange reaction (CER) in 5-monolayer-thick CdSe NPLs using Cu(I) and Cu(II) precursors. We discovered that the exposure of CdSe NPLs to a Cu(I) precursor led to the transformation of NPLs into Cu 2-x Se while maintaining their nanoplatelet morphology. The replacement of Cd(II) with Cu(I) prevailed over the formation of doped structures. In the case of the Cu(II) precursor, we observed that Cu(II) was first reduced to Cu(I) before being intercalated into the host lattice, resulting in the synthesis of Cu 2-x Se, similar to CER with Cu(I) precursors but without preservation of the initial morphology of NPLs. Interestingly, the presence of oxygen was found to facilitate the cation exchange processes in CdSe NPLs, whereas a nitrogen atmosphere suppressed the CER. Further, despite the similar ionic sizes of Cu(I) and Cu(II), the substitution of Cd(II) with Cu(II) was found to be challenging, possibly due to the involvement of redox processes resulting in the significant deterioration of initial CdSe NPLs. We demonstrate that CER can achieve near-complete substitution of cadmium atoms with monovalent copper at room temperature. Understanding the processes involved in CERs is crucial for engineering more complex structures, such as high-entropy nanoparticles involving cation exchange with different oxidation states and development of material synthesis using machine learning and artificial intelligence approaches.

2D nanoplatelets↗

Bound Exciton Complexes in Near-Infrared Emitting Quantum Shells

Near-infrared (NIR) light sources based on colloidal semiconductor nanocrystals (NCs) represent a scalable, low-cost alternative to epitaxial semiconductor platforms. However, their performance remains hindered by rapid Auger recombination, a problem that is particularly pronounced in narrow-bandgap materials. Here, we report on CdS/HgS/CdS and CdS/HgCdSe/ ZnS quantum shells (QSs), a class of spherical quantum wells specifically engineered for a suppression of nonradiative Auger processes. Fabricated QSs exhibit tunable NIR emission with photoluminescence quantum yields reaching ∼60% below 1000 nm and up to 30% near 1300 nm. Optical gain and stimulated emission were observed in CdS/HgS/CdS QSs. In contrast, CdS/HgCdSe/ZnS QSs displayed a photoinduced absorption in lieu of optical gain despite demonstrating a comparatively stronger Auger suppression. Transient absorption spectroscopy revealed that this phenomenon arises from the formation of bound multiexciton complexes that induce long-lived sub-bandgap multiexciton states. The observation of such bound excitonic clusters at room temperature offers a pathway toward nonlinear NIR photonic phenomena, including biexciton−exciton cascade emission, optical modulation, and singleexciton gain.

Auger recombination↗