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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 19 records

Comprehensive Efficiency Analysis of Current Source Inverter Based SPM Machine Drive System for Traction Applications

A current-source inverter (CSI) has the natural capability of boosting the output voltage which is a notable advantage over voltage source inverter (VSI) in traction drive applications. This paper investigates the voltage boosting feature of the CSI to improve the overall efficiency of the CSI-based surface permanent magnet (SPM) machine drive system in the constant power region. The effects of the boost function on the total system losses, including the machine copper loss, core loss, and magnet loss, as well as the device conduction and switching loss in the CSI and dc/dc converter, are described using analytical models. The operating characteristics of the machine and CSI are validated by 2-D finite-element analysis (FEA) and simulations. Based on the loss model, the effects of the modulation index on the overall drive system losses and power factor have been analyzed. A genetic algorithm has been used to optimize the CSI's boost ratio, demonstrating that the drive system efficiency can be increased by 1% to 2.5% along the constant-power regime envelope by using the boost function.

current source inverter, genetic algorithm, SPM ma↗

The Radical Atom: Mechanosynthetic 3D Printing of an Atomically Precise SPM Tip

This research effort sought to overcome current limitations in scanning probe-based atomic manipulation to enable atomically precise manufacturing (APM). Previous theoretical and experimental works on atom by atom and molecule by molecule fabrication of precise structures are limited to essentially to two-dimensions. APM will enable a paradigm shift in 21st century manufacturing practices in which every single atom in a electronic chip, device or machine can be placed in an exact and predefined position in three-dimensions. By providing a general method for generating reproducible SPM tip structure, this project will drive forward the entire field of atomically precise scanning probe microscopy, opening the door to positional control of nearly arbitrary covalent chemistry. Such control could, for example, be used in applications such as novel 2.5 or 3D microchip fabrication. The creation of a unique manufacturing method through APM has the potential to impact technologies at the theoretical limits of performance, weight, and utility including: solid-state quantum and spintronic computing systems, high efficiency optical antenna, solar power systems, defect engineered materials and extremely efficient catalysts. Although this experiment focused on pick-and-place non-scalable APM, the better understanding of the chemistry is crucial to the eventual goal of scalable APM. To place individual atoms into a specified location is a seminal aspiration of researchers and engineers in the many fields and may have early premium applications in medical devices and microelectronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Simultaneous mapping of nanoscale dielectric, electrochemical, and ferroelectric surface properties of van der Waals layered ferroelectric via advanced SPM

Ferroelectric surfaces involve a complex interplay between polarization and dielectric properties, internal and external surface charge screening, and ionic and electrochemical effects. There is currently no good way to simultaneously capture all the required information at appropriate length scales. To this end, we present an advanced scanning probe microscopy approach for simultaneously mapping surface potential, dielectric, and piezoelectric properties on the nanoscale. For quantitatively mapping electromechancial properties, we utilize interferometric displacement sensing piezoresponse force microscopy, which measures the effective piezoelectric coefficient free of background artifacts such as the cantilever body electrostatics. The dielectric and surface electrochemical properties are captured during G-mode electrostatic force microscopy/Kelvin probe force microscopy operated in the lift mode. We show the capabilities of this approach on the chemically phase separated composite sample consisting of a van der Waals layered ferroelectric CuInP 2 S 6 phase and a non-polar In 4/3 P 2 S 6 phase. Finally, we demonstrate domain structure evolution during thermally stimulated phase transition.

36 MATERIALS SCIENCE↗

Mechanical Analysis of Carbon Fiber Retaining Sleeve for A High-speed Outer Rotor SPM Electric Motor Design

Outer rotor motors can be designed with a larger airgap diameter than inner rotor motors for the same overall diameter and therefore provide higher torque which makes them ideal for high torque space constrained applications. This advantage fits well with the increasing demand of high-speed electric machines in many applications due to their inherent high-power density. However, increasing the motor speed results in significant centrifugal loads for the outer rotor motor design. Layers of carbon fiber sleeve winding on the rotor outer surface is necessary to guarantee its structural integrity without introducing too much weight on the motor itself. In this paper, we studied the mechanical stress of a carbon fiber retaining sleeve in a surface permanent magnet outer rotor motor that spins up to 20,000 RPM. Analytical results from finite element method (FEM) confirmed that the maximum stress experienced by the carbon fiber sleeve was under the material’s yield strength. The proposed sleeve will allow this outer rotor motor to operate at high speeds.

Lin, Lianshan↗

Shielded and Low-Damping SPM Probes for Quantitative Electrical and Electrochemical Characterization (Phase IIA)

The purpose of this DOE SBIR award was to develop new scanning probe microscopy tools for the elucidation of electrical and electrochemical properties at the nanoscale. High performance probes are important for energy materials research. In both solar cells and batteries, the essential physics and chemistry occur at the nanoscale and nanoscale characterization tools are required for their elucidation. Two products were developed: an electrically shielded probe and an electrically conductive probe with low leakage currents. Our processes were based on post processing of existing probes and fabrication methods were tested, leading to a laser micromachining based approach that led to the first minimal viable product. We invented a method to make a reliable electrical contact that attaches a flexible printed circuit board to the chip. enable leak-free operation crucial when used in conductive liquids and electrolytes. This proprietary solution improves chip handling, reduces contamination, and maintains effective electrical contact. The probes fabricated in this Phase IIa are a minimal viable product which attracted attention from various tip manufacturers and instrument manufacturers alike.

36 MATERIALS SCIENCE↗

Shielded and Low-Damping SPM Probes For Quantitative Electrical and Electrochemical Characterization (Phase IIB)

The purpose of this DOE SBIR award was to develop new scanning probe microscopy tools for the elucidation of electrical and electrochemical properties at the nanoscale. High performance probes are important for energy materials research. In both solar cells and batteries, the essential physics and chemistry occur at the nanoscale and nanoscale characterization tools are required for their elucidation. The introduced new models are a shielded probe and an electrically insulated probe where only less than one micron of a conductive tip is exposed. In Phases I and IIa, we explored the development of cost-effective methods to insulate cantilevers from aqueous solutions and patented a technology that provides an insulated electrical contact to the tip. Also, our technology was adapted to be compatible with all popular commercial AFM systems. In Phase IIb, we improved reproducibility and batch size to drive down costs while maintaining quality control with testing. We transformed our product into a convenient turnkey solution to make electrochemical characterization approachable to a wide range of researchers. In January 2021, the technology was well received by the AFM community and Nanosurf Inc. (Woburn, MA) acquired Scuba Probe Technologies. The technology and expertise of Scuba Probe Technologies complements Nanosurf’s development of the full range of nano-electrical characterization tools.

36 MATERIALS SCIENCE↗

Analysis of HolosGen Sub-Scale Simulator with Plant Dynamics Code

The Subcritical Power Module Sub-scale Simulator (SPM-SS) has been designed and constructed by HolosGen LLC under the ARPA-E MEITNER program to simulate the thermal-hydraulic and heat transfer behavior of the full-scale Holos-Quad Subcritical Power Modules (SPMs). Four coupled SPMs, each rated at 5.5MW, form the Holos-Quad gas-cooled microreactor design. The SPM-SS represents a substantially scaled-down system with a power rating less than 40 kW, equipped with an electrically heated fuel cartridge heat exchanger, an electrically heated compressor heat exchanger, and a valve actuated turbine heat exchanger, in addition to a recuperator and a cooler heat exchanger. The fuel cartridge represents a portion of the full-scale SPM core, the compressor heat exchanger mimics the temperature changes resulting from the compressor’s turbomachinery inefficiencies, the turbine heat exchanger mimics the expansion process normally occurring through the turbine, while the recuperator and cooler heat exchangers complete the subscale simulator loop. The heaters equipping the fuel cartridge and the compressor heat exchangers are electronically controlled to simulate normal and off-normal SPM operating conditions. The full-scale Holos-Quad SPM design eliminates the traditional balance of plant and executes thermal-to-electric energy conversion by means of an intercooled Brayton cycle with decoupled compressor-turbine turbomachinery. The Holos-Quad full-scale design is equipped with a multi-stage axial Low- and High-Pressure compressor, and a multistage axial turbine. The SPM-SS is designed for testing and validation of selected components which are instead coupled by a traditional balance of plant. The SPMSS is not equipped with turbo-machinery (compressor and turbine) as the development of these components were excluded from the scope of work under the ARPA-E MEITNER funding program. The SPM-SS balance of plant enables modifications, replacement and testing of individual components with different working fluids and is designed to include the turbo-machinery components that will be developed in future research . The SPM-SS can be operated with different gases, variable mass-flow-rates, pressures, and temperatures to obtain test data for selected components, whose performance can be scaled to validate the computer model of the full-scale SPM at various conditions (e.g., start-up, transients conditions). The SPM-SS can operate at the maximum Holos-Quad design pressure of 7 MPa, and a maximum temperature limited to 650 °C by the electrical heaters. Several SPM-SS tests have been conducted and analyzed with the Plant Dynamics Code (PDC) developed at the Argonne National Laboratory (ANL). These tests aimed at validating the PDC modeled predictions of the full-scale Holos-Quad design with data from selected SPM-SS components. In order to address SPM-SS specific characteristics, such as components heat losses and absence of turbomachinery components, some modifications to the PDC have been implemented to factor the design differences from the full-scale Holos-Quad SPM to the SPM-SS. As the PDC offers capabilities to analyze systems with different working fluids, air, nitrogen, and helium were utilized as the SPM-SS working fluids. Air was utilized to fine-tune the SPM-SS Systems Structures and Components (SSCs), nitrogen was utilized to pressure test the SPM-SS loop at the SPMs design maximum pressure of 7MPa. Helium was utilized as the working fluid circulating through the SPM-SS SSCs for specific tests to validate the PDC predictions of the fuel cartridge heat exchanger. SPM-SS tests data were also analyzed with both the steady-state and transient analysis capabilities offered by the PDC. This report describes the PDC analysis of the SPM-SS tests data, including the necessary code modifications and comparison of the code results with the experimental data. Based on the results, a discussion is presented on how the analysis supports design and transient calculations of the full-scale Holos-Quad microreactor. Also based on the results of this work, recommendations are made for future optimizations of the SPM-SS components and PDC model development needs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Specific iron binding to natural sphingomyelin membrane induced by non-specific co-solutes

Sphingomyelin (SPM), a crucial phospholipid in the myelin sheath, plays a vital role in insulating nerve fibers. We hypothesize that iron ions selectively bind to the phosphatidylcholine (PC) template within the SPM membrane under near-physiological conditions, resulting in disruptions to membrane organization. These interactions could potentially contribute to the degradation of the myelin sheath, thereby playing a role in the development of neurodegenerative diseases. We utilized synchrotron-based X-ray spectroscopy and diffraction techniques to study the interaction of iron ions with a bovine spinal-cord SPM monolayer (ML) at the liquid-vapor interface under physiological conditions. The SPM ML serves as a model system, representing localized patches of lipids within a more complex membrane structure. The experiments assessed iron binding to the SPM membrane both in the presence of salts and with additional evaluation of the effects of various ion species on membrane behavior. Grazing incidence X-ray diffraction was employed to analyze the impact of iron binding on the structural integrity of the SPM membrane. Furthermore, our results demonstrate that iron ions in dilute solution selectively bind to the PC template of the SPM membrane exclusively at near-physiological salt concentrations (e.g., NaCl, KCl, KI, or CaCl 2 ) and are pH-dependent. In-significant binding was detected in the absence of these salts or at near-neutral pH with salts. The surface adsorption of iron ions is correlated with salt concentration, reaching saturation at physiological levels. In contrast, multivalent ions such as La 3+ and Ca 2+ do not bind to SPM under similar conditions. Notably, iron binding to the SPM membrane disrupts its in-plane organization, suggesting that these interactions may compromise membrane integrity and contribute to myelin sheath damage associated with neurological disorders.

59 BASIC BIOLOGICAL SCIENCES↗

Imaging Electrons in Two Dimensional Materials (Final report)

Two-dimensional (2D) materials have extraordinary characteristics that offer promising new approaches for science and technology. Electrons in graphene can move ballistically through a sheet, even though it is only a single atom thick. And transition metal dichalcogenide materials can be cleaved into 2D flakes of all types – metals, semiconductors, insulators, magnetic materials, and superconductors. To benefit from these discoveries, the science needs to be understood to transform 2D materials into useful new devices and systems. The evolution in time of atomic scale graphene structures has been studied in time with a transmission electron microscope (TEM), and ballistic transport of electrons in graphene was been imaged using a cooled scanning probe microscope (SPM), as well as electron motion in MoS 2 . Graphene is only one atom thick but is extremely strong, creating the opportunity to fabricate atomic scale structures in the lateral direction. Using an atomic resolution TEM, a suspended sheet of graphene can be shaped by a Si impurity atom on its surface that acts like a chisel to open up apertures, one atom at a time. The electrons in the TEM provide both the chiseling energy and the ability to image the results. Electrons and holes in graphene form a new type of electronic system with conical conduction and valence bands that meet at the Dirac point, with no energy gap. For moderate densities, the carriers form a Fermi liquid with ballistic transport over micron-scale distances. Using a cooled SPM the cyclotron orbit of electrons in graphene has been imaged. In the magnetic focusing regime, electrons leaving a point contact circle around and leave from a second point contact when the cyclotron diameter is equal to the contact spacing. The paths of electrons are focused - they enter at different angles but converge again at the exiting contact. When the SPM tip knocks an electron out of its orbit, an imaging signal is created. The ballistic motion of carriers in graphene opens the way for ballistic devices that manipulate beams of electrons and holes. Our collaborator Gil-Ho Lee, in Philip Kim's group, created a collimating contact by placing zig-zag absorbers on either side of entering electrons. Our cooled SPM was used to image the electron beam and determine its 9-degree halfwidth. By changing the gate voltage, a collimated beam of holes was also created, opening the way for colliding beam experiments. Coherent beams of carriers are desirable for quantum information processing. Via Andreev reflection, superconducting contacts can covert Cooper pairs in a superconductor to an ingoing and outgoing electrons and holes. Using our cooled SPM, Andreev reflection was imaged from a superconducting contact on a graphene device. Magnetic focusing was used to create an incoming beam of electrons and an outgoing beam of holes, detected by a third point contact. The images show a clear transition from normal reflection above the superconducting transition temperature to Andreev reflection as the device is cooled. Transition metal dichalcogenides offer a wide array of materials that can be exfoliated into ultrathin 2D sheets. A cooled SPM can be used to detect quantum dots as well as to image electron flow. The tip charge capacitively couples to electrons on the dot, acting as a gate to tune the dot conductance. Coulomb blockade peaks appear as a bullseye pattern in an SPM image as the tip is raster scanned above the dot. This approach was used to detect quantum dots in a MoS 2 channel as the carrier density was reduced and electrons pooled in low energy points. Through our DOE supported research, cooled SPM imaging has proven to be a very useful tool to uncover the motion of electrons and holes in the new quantum materials graphene and MoS 2 .

36 MATERIALS SCIENCE↗

Light Regulation of Phytoplankton Growth in San Francisco Bay Studied Using a 3D Sediment Transport Model

In San Francisco Bay (SFB), light availability is largely determined by the concentration of suspended particulate matter (SPM) in the water column. SPM exhibits substantial variation with time, depth, and location. To study how SPM influences light and phytoplankton growth, we coupled a sediment transport model with a hydrodynamic model and a biogeochemical model. The coupled models were used to simulate conditions for the year of 2011 with a focus on northern SFB. For comparison, two simulations were conducted with ecosystem processes driven by SPM concentrations supplied by the sediment transport model and by applying a constant SPM concentration of 20 mg l –1 . The sediment transport model successfully reproduced the general pattern of SPM variation in northern SFB, which improved the chlorophyll-a simulation resulting from the biogeochemical model, with vertically integrated primary productivity varying greatly, from 40 g[C] m –2 year –1 over shoals to 160 g[C] m –2 year –1 in the deep channel. Primary productivity in northern SFB is influenced by euphotic zone depth ( Ze ). Our results show that Ze in shallow water regions (<2 m) is mainly determined by water depth, while Ze in deep water regions is controlled by SPM concentration. As a result, Ze has low (high) values in shallow (deep) water regions. Large (small) differences in primary productivity exist between the two simulations in deep (shallow) water regions. Furthermore, we defined a new parameter F light for “averaged light limitation” in the euphotic zone. The averaged chlorophyll-a concentration in the euphotic zone and F light share a similar distribution such that both have high (low) values in shallow (deep) water regions. Our study demonstrates that light is a critical factor in regulating the phytoplankton growth in northern SFB, and a sediment transport model improves simulation of light availability in the water column.

54 ENVIRONMENTAL SCIENCES↗

Integration of scanning probe microscope with high-performance computing: Fixed-policy and reward-driven workflows implementation

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements toward operationalization of the automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for scientific discovery. Here, we build a Python interface library that enables controlling an SPM from either a local computer or a remote high-performance computer, which satisfies the high computation power need of machine learning algorithms in autonomous workflows. We further introduce a general platform to abstract the operations of SPM in scientific discovery into fixed-policy or reward-driven workflows. Furthermore, our work provides a full infrastructure to build automated SPM workflows for both routine operations and autonomous scientific discovery with machine learning.

47 OTHER INSTRUMENTATION↗

Success Path Method: Introduction to the Success Path Method Software Tool©

As part of its commitment to advancing safety and reliability assessment methodologies, Argonne National Laboratory pioneered the use of an evaluation method called the Success Path Method (SPM) to improve risk management for offshore oil and gas operations. The development of the SPM at Argonne has been driven by the need to improve existing risk assessment methodologies by focusing on the steps necessary for success rather than failure modes alone. This is particularly important for industrial environments like offshore facilities that perform multiple functions under a continuously evolving set of operational conditions – such as water depth and temperature, currents, and weather conditions. In these dynamic environments, the traditional Probabilistic Risk Assessment (PRA) approach is far too complex as it focuses on what can go wrong – which comprises an infinite failure space that must be fully explored and understood. By shifting the focus to a finite space of success paths, the SPM enables operators and decision makers to prioritize a manageable number of steps that must go right to ensure success. Building on its five decades of experience in safety assessments for the nuclear industry, Argonne made major adaptations to existing risk assessment methods utilizing features similar to fault trees that are traditionally used in PRA to map all pathways in which the system can malfunction. In contrast, SPM identifies the components and processes that must function correctly to achieve specific outcomes – such as preventing the uncontrolled release of hydrocarbons during drilling operations. The SPM framework integrates equipment, procedures, software, processes, and human actions to ensure that physical barriers meet critical safety functions in dynamic operational conditions. This approach helps identify failure modes and improve operational risk management by narrowing the focus to key success elements, which in turn reduces uncertainty and helps users understand, manage, and respond to failures.

97 MATHEMATICS AND COMPUTING↗

Perspectives in Scanning Probe Microscopy from the 2021 Joint International Scanning Probe Microscopy and Scanning Probe Microscopy on Soft and Polymeric Materials Conference

In March of 2020 we were well on our way to organizing and hosting one of the premier scanning probe microscopy (SPM) conferences in Breckenridge, Colorado, USA. For the first time, the meeting would synergistically combine International Scanning Probe Microscopy (ISPM) and Scanning Probe Microscopy on Soft and Polymeric Materials (SPMonSPM), to increase the breadth of audience expertise and experience. We coined the joint conference iSPM 3 – a moniker we hope will persist in future events. The plan for 2020 iSPM 3 screeched to a halt in mid-March, amidst the COVID-19 pandemic. Luckily, we were able to regroup and reimagine the conference for 2021 as a virtual experience. The conference took place June 28th to July 2nd with a mix of live and pre-recorded content. Spread throughout the week were 4 live panel discussions, 3 plenary talks, 23 invited talks, 75 contributed talks, 15 posters and 3 social events. The technical program represented much of the latest and most impactful research in the field. The panel discussions sought to step back from specific research findings and assess the state of SPM as it pertains to some of the most pressing opportunities and influential successes. The lively discussions painted a vibrant future for SPM in both breadth and detail, and we hope that similar discussion can be a mainstay of future SPM conferences. In this work, we attempt to distill some of that discussion to motivate researchers across the field of SPM in the coming years.

47 OTHER INSTRUMENTATION↗

Enhancing Lithium-Ion Battery Aging Simulations: Coupling a High-Resolution, 3D, Grain-Scale Electromechanical Model to a Single-Particle Model

One of the main goals in modeling lithium-ion batteries is to improve/predict longevity and resilience of new chemistries. Unfortunately, this requires simulation of thousands of charge/discharge cycles, which can be rather time consuming depending on the fidelity of the simulation. The purpose of this talk is to discuss a new modeling framework that couples a high-resolution, continuous damage model (CDM) to a single particle model (SPM) resulting in a good combination of speed and fidelity. In previous work, a 3D, continuum-level chemo-mechanical model was developed to investigate cracking within a single cathode particle comprised of hundreds to thousands of randomly oriented grains. The CDM predicted that particle fracture is primarily due to non-ideal grain interactions with slight dependence on high-rate charge demands. Essentially, when neighboring grains were misaligned, they expanded different rates relative to one another leading to high stresses and ultimately the formation of intraparticle cracks. The model predicted that small particles with large grains develop significantly less damage than larger particles with small grains. Finally, the model predicted most of the chemo-mechanical damage accumulates in the first charge after formation. This chemo-mechanical "damage saturation" effect indicated that initial particle fracture occurs within the first few cycles, while long-term cathode degradation is not solely chemo-mechanically induced. This led to a need for simulating fatigue-like mechanism that degrade the battery over longer time scales. In order to reach the time scales, need to resolve fatigue-like degradation, the CDM needs to be complemented by a faster model. Therefore, recent efforts have been focused on using results from the CDM to inform parameters within the SPM. These parameters are homogenization factors that are associated with diffusion, particle radius, and/or exchange current density. By coupling the CDM to the SPM, the aging simulation is broken up into two domains: short-term and long-term degradation. The short-term degradation occurs over a single cycle and is handled by the CDM due of its high fidelity, but relatively expensive computational cost. Such mechanism include break-in crack caused by mismatches in grain orientation. The long-term degradation occurs over tens of cycles and is handled by the SPM due it's computational efficiency. Most of the fatigue-like mechanism fall into this category. The eventual goal of this modeling framework is to upscale to a psudo-2D model allowing for full electrode simulation, which are informed by high-fidelity grain-scale simulations.

electrochemistry↗

Metal (Fe, Cu, and As) transformation and association within secondary minerals in neutralized acid mine drainage characterized using X-ray absorption spectroscopy

The formation and transformation of secondary minerals in areas affected by neutralized acid mine drainage (AMD) determine the behavior of toxic elements. To better understand the binding form of toxic elements in the secondary minerals, we focused on the distribution of secondary precipitates and heavy metals in neutralized AMD near a typical Cu-polymetallic deposit located in central Tibet. Compared to background values, the average heavy metal (As, Cu, Co, Cu, Mo, Pb, and Zn) content is higher in sediments close to the neutralized AMD drain. X-ray absorption spectroscopy (XAS) characterization shows the Fe in the suspended particulate matter (SPM) first aggregate as small Fe(III) octahedra clusters and then precipitate as ferrihydrite along the river. The XAS results also show the by-products of neutralization-ferrihydrite and sulfate-are the primary forms of Fe and S in the sediments, respectively. Gypsum retains Cu in the sediments via structural fixation, surface adsorption, and surface coprecipitation. The difference of Cu-O coordination number between the SPM and the sediments reveals the Cu sulfate coprecipitation on the surface of gypsum accompanied by SPM transporting along the river. XAS results confirm that ferrihydrite act as an essential sink for heavy metals, especially As. As (III) mineral in the sediment near the neutralized AMD outfall is dissolved and oxidized to arsenate downstream, which then adsorb to ferrihydrite and/or form As(V)-Fe minerals along the river. Gypsum and ferrihydrite have the potential to release heavy metals with changes in water chemistry, which may pose a threat to the safety of drinking water for downstream residents. These results deepen the understanding of the influence of secondary minerals (especially gypsum and ferrihydrite) on the migration and transformation process of heavy metal pollutants in mine drainage system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗