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DOE OSTI2024

Ion-Depleted Microenvironments During Lithium Deposition Revealed by Operando Freezing Cryogenic Electron Microscopy

Local structures and chemistry at active electrochemical interfaces are critical to determining safety, lifetime, and energy density in lithium metal batteries and other devices, but they are challenging to characterize at the nanoscale. We address this issue by developing operando freezing cryogenic electron microscopy (cryo-EM) to preserve battery interfaces in an active state for subsequent high-resolution characterization. We find that ion-depleted microenvironments form locally in the electrolyte adjacent to the lithium deposition interface in lithium metal batteries and are linked to heterogenous growth morphologies. These depleted environments arise locally even under conditions for which ion depletion is not predicted at steady state; this provides a mechanistic explanation for why dangerous lithium morphologies can still propagate in such systems and lead to thermal runaway. Operando freezing cryo-EM thus provides a method to directly visualize nanoscale heterogeneities that arise locally at electrochemical interfaces and play key roles in device failure.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,E↗

DOE OSTI2023

A study of adhesive bonding in metal–metal, metal–CFRP, and CFRP–CFRP material combinations under shear deformation: Fracture morphologies and damage mechanisms

Safe design of adhesive joining in multi-materials in engineered structures requires the accumulation of numerous experimental data on the failure behavior of various adhesively-bonded material combinations under different loading conditions. The deep understanding of mechanical performance, fracturing morphologies, and main damage mechanisms is also quintessential for accelerating the development of proper physics-based and multi-scale models for assisting the design. Towards this goal, this work presents a comprehensive characterization of the failure behavior of adhesively-bonded metal–metal, metal–CFRP, and CFRP–CFRP material combinations under global shear deformation via single lap shear testing. Thanks to a synergistic combination of measurement methods by using Digital Imaging Correlation (DIC) and 3D optical profilometry, adhesive features on the adherend after failure were quantified and the main progressive damage mechanisms were identified. The characterization performed in this work provides quantitative data that contributes to a better understanding of shear failure in adhesive bonding across different bi-material combinations. Finally, the obtained results have practical implications, including the potential to enhance adhesive bonding design, identify failure causes in adhesive joints, and develop or validate computational models capable of capturing the observed behavior in various adhesively-bonded materials under global shear deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Numerical Simulation of Container Breach and Airborne Release of Solids Due to Mechanical Insults

Throughout U.S. Department of Energy (DOE) complexes, safety engineers employ the five-factor formula to calculate the source term (ST) that includes parameters of airborne release fraction (ARF), respirable fraction (RF) and damage ratio (DR). Limited experimental data on fragmentation of solids, such as ceramic pellets (i.e., PuO2), and container breach due to mechanical insults (i.e., drop and forklift impact), can be supplemented by modeling and simulation using high fidelity computational tools to estimate these parameters. This paper presents the use of Sandia National Laboratories' SIERRA solid mechanics (SM) finite element code to investigate the behavior of the widely utilized waste container (such as 7A Drum) subject to a range of free fall impact and puncture scenarios. The resulting behavior of the container is assessed, and the estimates are presented for bounding DRs from calculated breach areas for the various accident conditions considered. This paper also describes a novel multiscale constitutive model recently implemented in SIERRA/SM that simulates the fracture of brittle materials such as PuO 2 and determines ARF during the fracture process. Furthermore, comparisons are made between model predictions and simple bench-top experiments.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2020

Self-assembling Shell Proteins PduA and PduJ have Essential and Redundant Roles in Bacterial Microcompartment Assembly

Protein self-assembly is a common and essential biological phenomenon, and bacterial microcompartments present a promising model system to study this process. Bacterial microcompartments are large, protein-based organelles which natively carry out processes important for carbon fixation in cyanobacteria and the survival of enteric bacteria. These structures are increasingly popular with biological engineers due to their potential utility as nanobioreactors or drug delivery vehicles. However, the limited understanding of the assembly mechanism of these bacterial microcompartments hinders efforts to repurpose them for non-native functions. Here, we comprehensively investigate proteins involved in the assembly of the 1,2-propanediol utilization bacterial microcompartment from Salmonella enterica serovar Typhimurium LT2, one of the most widely studied microcompartment systems. We first demonstrate that two shell proteins, PduA and PduJ, have a high propensity for self-assembly upon overexpression, and we provide a novel method for self-assembly quantification. Using genomic knock-outs and knock-ins, we systematically show that these two proteins play an essential and redundant role in bacterial microcompartment assembly that cannot be compensated by other shell proteins. At least one of the two proteins PduA and PduJ must be present for the bacterial microcompartment shell to assemble. We also demonstrate that assembly-deficient variants of these proteins are unable to rescue microcompartment formation, highlighting the importance of this assembly property. Our work provides insight into the assembly mechanism of these bacterial organelles and will aid downstream engineering efforts.

1,2-propanediol utilization MCP↗

DOE OSTI2020

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗

DOE OSTI2025

Nuclear Materials Packaging, Transportation, and Systems Analysis Group Software Quality Assurance Plan: ANSYS Mechanical Finite Element Analysis Software Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic, and electromagnetic simulation capabilities. ANSYS has two main programs, which use the same solvers: (1) Mechanical APDL (ANSYS Design Parametric Language), a Fortran-based coding platform, and (2) ANSYS Workbench, which uses a graphical user interface to aid in finite element analysis implementation. This plan covers both APDL and Workbench. The ANSYS computer program is a large-scale, multipurpose finite element program that can be used to solve several classes of engineering analyses. The analysis capabilities of ANSYS include the ability to solve static and dynamic structural analyses, steady-state and transient heat transfer problems, mode-frequency and buckling eigenvalue problems, static or time-varying magnetic analyses, and various types of field and coupled-field applications. The program contains many special features that allow nonlinearities or secondary effects such as plasticity, large strain, hyperelasticity, creep, swelling, large deflections, contact, stress stiffening, temperature dependency, material anisotropy, and radiation to be included in the solution. As ANSYS has been developed, other special capabilities such as substructuring, submodeling, random vibration, kinetostatics, kinetodynamics, free convection fluid analysis, acoustics, magnetics, piezoelectrics, coupled-field analysis, and design optimization have been added to the program. These capabilities contribute further to making ANSYS a multipurpose analysis tool for varied engineering disciplines. The ANSYS program has been in commercial use for over 50 years and has been used extensively in the aerospace, automotive, construction, electronic, energy services, manufacturing, nuclear, plastics, oil, and steel industries. Additionally, many consulting firms and hundreds of universities have used ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. Ansys design analysis software is the first created within a quality system with ISO 9001 certification, the internationally accepted quality standard. Product development, testing, maintenance and support processes also meet the United States Nuclear Regulatory Commission's quality requirements, as they have for nearly four decades. The Quality Assurance Service Agreement is suitable for the customers working in the nuclear industry who need to meet specific federal regulations including 10CRF50 Appendix B and provisions of 10CFR21. ANSYS has retained its original International Organization for Standardization (ISO) 9001 accreditation certificate since1995-05-04, It’s current certificate is valid until 2027-05-29.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Atmospheric Pressure Plasma Deposition of TiO2: A Review

Atmospheric pressure plasma (APP) deposition techniques are useful today because of their simplicity and their time and cost savings, particularly for growth of oxide films. Among the oxide materials, titanium dioxide (TiO2) has a wide range of applications in electronics, solar cells, and photocatalysis, which has made it an extremely popular research topic for decades. Here, we provide an overview of non-thermal APP deposition techniques for TiO2 thin film, some historical background, and some very recent findings and developments. First, we define non-thermal plasma, and then we describe the advantages of APP deposition. In addition, we explain the importance of TiO2 and then describe briefly the three deposition techniques used to date. We also compare the structural, electronic, and optical properties of TiO2 films deposited by different APP methods. Lastly, we examine the status of current research related to the effects of such deposition parameters as plasma power, feed gas, bias voltage, gas flow rate, and substrate temperature on the deposition rate, crystal phase, and other film properties. The examples given cover the most common APP deposition techniques for TiO2 growth to understand their advantages for specific applications. In addition, we discuss the important challenges that APP deposition is facing in this rapidly growing field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A Review on Metallic Alloys Fabrication Using Elemental Powder Blends by Laser Powder Directed Energy Deposition Process

The laser powder directed energy deposition process is a metal additive manufacturing technique, which can fabricate metal parts with high geometric and material flexibility. The unique feature of in-situ powder feeding makes it possible to customize the elemental composition using elemental powder mixture during the fabrication process. Thus, it can be potentially applied to synthesize industrial alloys with low cost, modify alloys with different powder mixtures, and design novel alloys with location-dependent properties using elemental powder blends as feedstocks. This paper provides an overview of using a laser powder directed energy deposition method to fabricate various types of alloys by feeding elemental powder blends. At first, the advantage of laser powder directed energy deposition in manufacturing metal alloys is described in detail. Then, the state-of-the-art research and development in alloys fabricated by laser powder directed energy deposition through a mix of elemental powders in multiple categories is reviewed. Finally, critical technical challenges, mainly in composition control are discussed for future development.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Calcium Carbonate Cement: A Carbon Capture, Utilization, and Storage (CCUS) Technique

A novel calcium carbonate cement system that mimics the naturally occurring mineralization process of carbon dioxide to biogenic or geologic calcium carbonate deposits was developed utilizing carbon dioxide-containing flue gas and high-calcium industrial solid waste as raw materials. The calcium carbonate cement reaction is based on the polymorphic transformation from metastable vaterite to aragonite and can achieve >40 MPa compressive strength. Due to its unique properties, the calcium carbonate cement is well suited for building materials applications with controlled factory manufacturing processes that can take advantage of its rapid curing at elevated temperatures and lower density for competitive advantages. Examples of suitable applications are lightweight fiber cement board and aerated concrete. The new cement system described is an environmentally sustainable alternative cement that can be carbon negative, meaning more carbon dioxide is captured during its manufacture than is emitted.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Impact of Humidity and Temperature on the Stability of the Optical Properties and Structure of MAPbI3, MA0.7FA0.3PbI3 and (FAPbI3)0.95(MAPbBr3)0.05 Perovskite Thin Films

In situ real-time spectroscopic ellipsometry (RTSE) measurements have been conducted on MAPbI3, MA0.7FA0.3PbI3, and (FAPbI3)0.95(MAPbBr3)0.05 perovskite thin films when exposed to different levels of relative humidity at given temperatures over time. Analysis of RTSE measurements track changes in the complex dielectric function spectra and structure, which indicate variations in stability influenced by the underlying material, preparation method, and perovskite composition. MAPbI3 and MA0.7FA0.3PbI3 films deposited on commercial fluorine-doped tin oxide coated glass are more stable than corresponding films deposited on soda lime glass directly. (FAPbI3)0.95(MAPbBr3)0.05 films on soda lime glass showed improved stability over the other compositions regardless of the substrate, and this is attributed to the preparation method as well as the final composition.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

The objective of this project is to improve the prediction of engine knock by developing a new combustion modeling framework. Engine knock is a limiting factor to constrain the increase of fuel efficiency for spark ignition (SI) engines in most passenger cars. Efforts to increase fuel efficiency, increasing the compression ratio or downsizing, lead to the increase in the tendency of the knock occurrence. The knock is an undesired ignition of the end-gas, unburned fuel/air mixture ahead of the spark-ignited premixed flame, resulting in rapid in-cylinder pressure rises and engine damages. The combustion modeling framework developed in this project can consider turbulence-chemistry interactions during end-gas ignition, while using a reasonably detailed chemical mechanism developed for ignition and combustion reactions under engine relevant conditions, and the subtle characteristics of spark-ignited flame propagation. It is developed in the context of large eddy simulation (LES), which can capture stochastic in-cylinder processes. The developed model is incorporated into a commercial software for engine simulation, CONVERGE CFD, as a user defined function, and validated. Engine knock and knock-free experiments as well as direct numerical simulation (DNS) of end-gas ignition in homogeneous turbulence are performed to help model development and provide data sets for model validation. With further validation, the developed model is expected to advance the predictive capability for engine knock simulations and thus contribute to improving the fuel efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

NUMERICAL INVESTIGATION OF FUEL PROPERTY EFFECTS ON MIXED-MODE COMBUSTION IN A SPARK-IGNITION ENGINE

In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.

detailed chemical kinetics↗

DOE OSTI2021

Quantum Otto engines at relativistic energies

Not Available

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Leveraging a Neural Network-Enhanced Reproducing Kernel Particle Method for Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation has been developed to analyze this system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. Here, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RKPM is additionally used to inform how crack opening and closure in turn affect the coupled chemical equations and material microstructure. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

degradation↗

DOE OSTI2024

A Perspective on Scalable AI on High-Performance Computing and Leadership Class Supercomputing Facilities [Industrial and Governmental Activities]

Many scientific applications that support the mission of the US Department of Energy (US-DoE) require modeling complex engineering and/or physical systems. Here, examples of such complex systems arise from: (a) materials science to develop new compounds with exceptional mechanical and thermodynamical properties (e.g., resistance to mechanical stresses and high temperatures), (b) structural and nuclear engineering to model the temporal evolution of the structural damage of concrete shields exposed to continuous neutron and gamma radiations emitted by the nuclear reactor core, (c) urban sciences (e.g., transportation and smart buildings), and (d) power grid systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Chemoautotrophic cells comprising an engineered carbon fixation pathway

The present disclosure identifies pathways, mechanisms, systems and methods to confer chemoautotrophic production of carbon-based products of interest, such as sugars, alcohols, chemicals, amino acids, polymers, fatty acids and their derivatives, hydrocarbons, isoprenoids, and intermediates thereof, in organisms such that these organisms efficiently convert inorganic carbon to organic carbon-based products of interest using inorganic energy, such as formate, and in particular the use of organisms for the commercial production of various carbon-based products of interest.

Fischer, Curt R.↗

DOE OSTI2024

A chemical kinetic analysis of knock propensity of methanol-to-gasoline fuel

Production of low carbon gasoline-like fuels such as methanol-to-gasoline (MTG) is a promising approach to achieve rapid greenhouse gas emission reduction of the transportation sector. Despite the fact that gasoline that meets the ASTM D4814 standard for automotive spark-ignition engine fuel can be readily produced from these processes, it is unclear how the composition of MTG may affect engine performance and emissions. Here, in this paper, a surrogate for an MTG is used to numerically study the effects of gasoline composition on knock propensity and on the sensitivity of knock to thermal and fuel stratification, to oxygen dilution and to nitric oxide from exhaust gas recirculation of residual gases. Simulations were performed in ANSYS CHEMKIN-PRO using a comprehensive chemical kinetic mechanism for gasoline surrogates, and results of the MTG surrogate were compared against those of a petroleum-based regular E10 gasoline, termed PACE-20. A premium-grade MTG fuel was also formulated by adding ethanol to the MTG surrogate, and results were compared against those of four premium-grade, gasoline-like fuels representative of future alternative gasoline formulations. Surrogates and mechanism were evaluated by comparison against experimental engine data, and the model showed high accuracy at stoichiometric conditions (mean absolute error of ignition timing equal to 1.46 crank angle degrees) but larger deviations at lean conditions (mean absolute error of ignition timing equal to 5.52 crank angle degrees). Despite the fact that the MTG surrogate has a RON 1.1 units higher than that of PACE-20, it may show higher knock propensity at medium temperature conditions due to a less intense NTC behavior. MTG autoignition was more temperature- and equivalence ratio-sensitive than that of PACE20, suggesting that MTG can benefit more from naturally-occurring thermal stratification or from induced fuel stratification of the end gas to mitigate knock intensity. The sensitivity of autoignition reactivity to oxygen dilution and to NO concentration was higher for MTG than for regular gasoline at medium loads, but the opposite trend was observed at high loads due to the effect of pressure on the low-temperature chemistry of regular gasoline. Approximately 14 % vol ethanol content was required to upgrade the octane rating of MTG from regular grade to premium grade. Adding 13.6 % vol ethanol made the fuel autoignition less sensitive to both oxygen dilution and NO content (ignition time varies approx. 17 % and 50 % less with oxygen dilution and NO addition, respectively, when adding ethanol at high engine loads).

02 PETROLEUM↗