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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Generative attribute optimization

A generative attribute optimization (“GAO”) system facilitates understanding of effects of changes of attribute values of an object on a characteristic of the object and automatically identifying attribute values to achieve a desired result for the characteristic. The GAO system trains a generator (encoder and decoder) using an attribute generative adversarial network. The GAO model includes the trained generator and a separately trained predictor model. The GAO model inputs an input image and modified attribute values and employs the encoder and the decoder to generate a modified image that is the input image modified based on the modified attribute values. The GAO model then employs the predictor model to that inputs the modified image and generate a prediction of a characteristic of the modified image. The GAO system may employ an optimizer to modify the attribute values until an objective based on the desired result is achieved.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Integrated silicon optical amplifier with reduced residual pump

An optical amplifier device employing a Mach-Zehnder Interferometer (MZI) that reduces the amount of residual pump power in the optical output of the amplifier is disclosed. The MZI amplifier employs two geometrically linear optical amplifier arms or two multi-spatial-mode racetrack optical amplifiers to amplify a signal with a pumping beam, with the signal output port having extremely low levels of residual pump power. The MZI optical amplifier is a silicon photonic integrated circuit, with all optical amplifiers, couplers, phase shifters, and optical attenuators formed of silicon photonic integrated circuit elements. The MZI optical amplifier may include one, two, or three MZI stages, and multiple MZI optical amplifiers may be used in parallel or sequentially to achieve higher overall signal gain or power. The MZI optical amplifier may employ Brillouin-scattering-based amplifiers, Raman-based integrated waveguide optical amplifiers, or Erbium-doped integrated waveguide optical amplifiers.

Lentine, Anthony L.↗
DOE OSTI2024

Biomass Attributes and Attribute Modifications Affecting Systems and Methods to Separate and Fractionate. In: Handbook of Biorefinery Research and Technology

Chemical and physical heterogeneity in biomass feedstocks such as agricultural or forestry residues is due to substantial differences in plant tissue types. These differences can contribute significant challenges to handling, preprocessing, and conversion in biorefining processes. An understanding of this chemical and physical heterogeneity can be used to inform fractionation technologies that could facilitate more streamlined processing and potentially be employed to yield multiple co-product streams for a single feedstock. In this chapter, the motivation and scope of biomass fractionation is first outlined. Physical and chemical properties of biomass feedstocks, along with their distribution and diversity within plants is next discussed with respect to how these differences can be exploited in a fractionation process. A summary of some of the key physical principles that allow for fractionation is next covered along with how these physical principles are exploited in equipment designs. Examples from the literature are briefly discussed that highlight how these approaches can be employed to achieve processing objectives. Several case studies on physical fractionation of corn stover and forestry residues are presented that illustrate how integrated fractionation processes could be employed. Finally, prospects and potential economic drivers for adoption of biomass fractionation technologies are discussed.

Biomass chemical properties↗
DOE OSTI2023

Particulate matter sensor

Microfabricated PM sensors measure concentrations of particulate matter (PM) in air. Some sensors improve the accuracy of measurements by accounting for the effect of ambient conditions (e.g., temperature or humidity) on mass-sensitive elements employed to determine a mass of the PM in a stream of air. Some sensors improve the accuracy of measurements by controlling humidity in the stream of air measured by mass-sensitive elements. Some sensors employ a plurality of mass-sensitive elements to extend the useful life of the PM sensor. Some sensors employ one or more mass-sensitive elements and heating elements to cause deposition and allow measurement of different sizes of PM. Some sensors can measure mass concentration of coarse PM in addition to fine PM in a stream of air. Some sensors control the flow rate of a stream of air measured by mass-sensitive elements. Some sensors include features to mitigate electromagnetic interference or electromagnetic signal loss.

Paprotny, Igor↗
DOE OSTI2020

Panel Session 37: The Wants and Needs of Graduating Students and New Engineers: Are Companies Even Listening? (R8.1)

This panel focused on new hires, graduating scientists and engineers having open lines of communication with employers. Considering the projected shortfalls in the workforce, effective communication of wants-and-needs of both the employer and employee must exist. Do these needs differ between industries and/or generations? Currently, it seems that both sides must work harder to achieve this level of communication. With this new approach, both sides can express their wants and needs for a more satisfied workforce and a better work environment. Panelists with presentations: The Future of Work: What Employers Seek From Recent Graduates (Melody Bell); Graduating Students and New Engineers - Wants and Needs - Are Companies Even Listening? (Joseph Aylor); Industry and Education: Bridging the Gap (Arthur Baranovskiy)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗
DOE OSTI2023

Overview of H- radio frequency ion sources for particle accelerators

Particle accelerators are among the most important scientific tools of the modern era. Large accelerator complexes have supported scientific user facilities which have had an enormous societal impact spanning many decades and enabling the work of thousands of scientific users worldwide contributing to many Nobel prizes in physics, biology and chemistry [1]. Many of the large hadron facilities employ accelerator complexes which include cyclotrons, synchrotrons, storage rings, linear or tandem accelerators and deliver ion beams of very high-intensity and/or very high-energy to their user facilities. These accelerator complexes require the injection of high-intensity beams of ions which are produced within an ion source and formed within a plasma or by bombardment of a surface [2]. Increasingly, RF systems are being utilized, to generate these ion-rich plasmas due to their high reliability and minimal use of consumable components. This report will first discuss the basic mechanisms of ion formation and plasma generation as well as some specifics of RF/microwave generators, matching circuits and plasma coupling structures typically employed. A detailed discussion will then be given of the RF-driven negative ion source systems employed by US Spallation Neutron Source as well as those used in similar facilities located around the globe. REFERENCES [1]Vladimir Shiltsev, “Particle beams behind physics discoveries”, Physics Today 73, Issue 4, 32 (2020) [2]Robert Welton et al, “Negative hydrogen ion sources for particle accelerators: Sustainability issues and recent improvements in long-term operations”, Journal of Physics Conf Series, 2244 012045

Welton, Robert F.↗
DOE OSTI2025

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

RESOLVING THE ELECTROCHEMICAL EQUATIONS OF A SOLID OXIDE FUEL CELL FOR USE IN TRANSIENT SIMULATION AND INTEGRATION INTO CYBER-PHYSICAL SYSTEMS

A major challenge with complex cyber-physical systems stems from long model computational time that creates a mismatch between the model system and the physical system. The numerical modeling of solid oxide fuel cells (SOFCs) presents particular challenges due to the highly coupled nature of the underlying equations and the multiphysics needed to fully resolve their behavior during a transient event. To this end current approaches revolve around splitting the computational efforts into resolving temperature effects and resolving electrochemical effects. Current methods employed for the transient simulation of an SOFC for implementation in the Hybrid Performance (HyPer) facility cyberphysical plant at the National Energy Technology Laboratory reveal a distinct need for accelerated results with a high degree of stability. To this aim, an investigation into the computational time for the code reveals that the underlying electrochemical algorithm takes an order of magnitude more time than its thermal counterpart and has a tendency to vary in terms of iteration time and as such a rework of the underlying system is proposed. The primary method for accelerated electrochemical algorithm solutions is to employ higher order root finding recipes for the resolution of the highly coupled electrochemical equations. This is done with the intention to reduce the overall number of subiterations necessary for resolving voltage, current density, and species concentration, properties of the fuel cell that are all directly coupled and require nested iterative approaches. The overall objective of this approach is an order of magnitude reduction in calculation time without sacrificing stability and increasing accuracy. Specific approaches involve using both bounded and unbounded techniques, such as the False Position method and the Secant method (or if applicable Newton-Raphson) respectively, the drawbacks being slower convergence for False Position and instability for the Secant or Newton-Raphson methods. Current preliminary results on simplified versions of the parent functions involved for electrochemical calculations indicate a reduction in computational steps by a factor of two for the secant method and a factor of three for Newton-Raphson. When implemented into new modified electrochemical algorithms, the results indicate a possible order of magnitude reduction in calculation time.

Arias, Jesus↗
DOE OSTI2024

Breaking Barriers in Chalcogenide Perovskite Synthesis: A Generalized Framework for Fabrication of BaMS 3 (M═Ti, Zr, Hf) Materials

Abstract Chalcogenide perovskites have garnered increasing attention as stable, non‐toxic alternatives to lead halide perovskites. However, their conventional synthesis at high temperatures (>1000 °C) has hindered widespread adoption. Recent studies have developed low‐to‐moderate temperature synthesis methods (<600 °C) using reactive precursors, yet a comprehensive understanding of the pivotal factors affecting reproducibility and repeatability remains elusive. This study delineates the critical factors in the low‐temperature synthesis of BaMS 3 (M═Zr, Hf, Ti) compounds and presents a generalized framework. Innovative approaches are developed for synthesizing BaMS 3 compounds using this framework involving organometallics for solution deposition. The molecular precursor routes, employing metal acetylacetonates to generate soluble metal–sulfur bonded complexes and metal–organic compounds to produce soluble metal‐thiolate, metal‐isothiocyanate, and metal‐trithiocarbonate species, are demonstrated to yield carbon‐free BaMS 3 . These methods have achieved the most contiguous films of BaZrS 3 and BaHfS 3 using solution deposition to date. Furthermore, a hybrid solution processing method involving stacking sputter‐deposited Zr and solution‐deposited BaS layers is employed to synthesize a contiguous, oxygen‐free BaZrS 3 film. The diffuse reflectance measurements indicate a direct bandgap of ≈ 1.85 eV for the BaZrS 3 films and ≈ 2.1 eV for the BaHfS 3 film under investigation.

25 ENERGY STORAGE↗
DOE OSTI2025

Unconventional Spintronics from Chiral Perovskites

Spintronic devices typically employ heterostructures with ferromagnets which break time-reversal symmetry and have non-vanishing magnetization. With the growing class of materials that support spin-polarized carriers, current, and excitations, it is possible to envision emerging spintronic applications that are not limited to magnetoresistance. Here, chiral perovskites with no net magnetization are considered, where the space-inversion and mirror symmetries are broken to induce chiral structure. The known importance of these perovskites is further expanded by the demonstration of the chiral-induced spin selectivity (CISS). However, the generation of the spin-polarized carriers across the interface with these chiral perovskites remains to be fully understood. These first-principles studies for 2D PbBr4-based chiral perovskites provide their electronic structure and an orbital-based symmetry analysis, which allows to establish an effective Hamiltonian to elucidate the underlying origin of their chirality. The same analysis is used for the Edelstein effect, responsible for electrical generation of the nonequilibrium spin polarization in many materials, which in chiral perovskites can be a mechanism contributing to CISS. Furthermore, by examining optical properties of chiral perovskites and the opportunity to use them to realize tunable altermagnets, another class of zero-magnetization spintronic materials, a versatile materials platform is put forth for unconventional spintronics.

14 SOLAR ENERGY↗
DOE OSTI2020

Ultrafast Exciton Transport with a Long Diffusion Length in Layered Perovskites with Organic Cation Functionalization

Abstract Layered perovskites have been employed for various optoelectronic devices including solar cells and light‐emitting diodes for improved stability, which need exciton transport along both the in‐plane and the out‐of‐plane directions. However, it is not clear yet what determines the exciton transport along the in‐plane direction, which is important to understand its impact toward electronic devices. Here, by employing both steady‐state and transient photoluminescence mapping, it is found that in‐plane exciton diffusivities in layered perovskites are sensitive to both the number of layers and organic cations. Apart from exciton–phonon coupling, the octahedral distortion is revealed to significantly affect the exciton diffusion process, determined by temperature‐dependent photoluminescence, light‐intensity‐dependent time‐resolved photoluminescence, and density function theory calculations. A simple fluorine substitution to phenethylammonium for the organic cations to tune the structural rigidity and octahedral distortion yields a record exciton diffusivity of 1.91 cm 2 s −1 and a diffusion length of 405 nm along the in‐plane direction. This study provides guidance to manipulate exciton diffusion by modifying organic cations in layered perovskites.

Xiao, Xun↗
DOE OSTI2021

Novel Ultrabright and Air-Stable Photocathodes Discovered from Machine Learning and Density Functional Theory Driven Screening

The high brightness, low emittance electron beams achieved in modern X-ray free-electron lasers (XFELs) have enabled powerful X-ray imaging tools, allowing molecular systems to be imaged at picosecond time scales and sub-nanometer length scales. One of the most promising directions for increasing the brightness of XFELs is through the development of novel photocathode materials. Whereas past efforts aimed at discovering photocathode materials have typically employed trial-and-error-based iterative approaches, this work represents the first data-driven screening for high brightness photocathode materials. Through screening over 74 000 semiconducting materials, a vast photocathode dataset is generated, resulting in statistically meaningful insights into the nature of high brightness photocathode materials. This screening results in a diverse list of photocathode materials that exhibit intrinsic emittances that are up to 4x lower than currently used photocathodes. In a second effort, multiobjective screening is employed to identify the family of M 2 O (M = Na, K, Rb) that exhibits photoemission properties that are comparable to the current state-of-the-art photocathode materials, but with superior air stability. This family represents perhaps the first intrinsically bright, visible light photocathode materials that are resistant to reactions with oxygen, allowing for their transport and storage in dry air environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Sodium–Antimony–Telluride Intermetallic Allows Sodium-Metal Cycling at 100% Depth of Discharge and as an Anode-Free Metal Battery

In this work, repeated cold rolling and folding is employed to fabricate a metallurgical composite of sodium–antimony–telluride Na 2 (Sb 2/6 Te 3/6 Vac 1/6 ) dispersed in electrochemically active sodium metal, termed “NST-Na.” This new intermetallic has a vacancy-rich thermodynamically stable face-centered-cubic structure and enables state-of-the-art electrochemical performance in widely employed carbonate and ether electrolytes. NST-Na achieves 100% depth-of-discharge (DOD) in 1 m NaPF 6 in G2, with 15 mAh cm –2 at 1 mA cm –2 and Coulombic efficiency (CE) of 99.4%, for 1000 h of plating/stripping. Sodium-metal batteries (SMBs) with NST-Na and Na 3 V 2 (PO 4 ) 3 (NVP) or sulfur cathodes give significantly improved energy, cycling, and CE (>99%). An anode-free battery with NST collector and NVP obtains 0.23% capacity decay per cycle. Imaging and tomography using conventional and cryogenic microscopy (Cryo-EM) indicate that the sodium metal fills the open space inside the self-supporting sodiophilic NST skeleton, resulting in dense (pore-free and solid electrolyte interphase (SEI)-free) metal deposits with flat surfaces. The baseline Na deposit consists of filament-like dendrites and “dead metal”, intermixed with pores and SEI. Density functional theory calculations show that the uniqueness of NST lies in the thermodynamic stability of the Na atoms (rather than clusters) on its surface that leads to planar wetting, and in its own stability that prevents decomposition during cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Elucidating and Mitigating High-Voltage Degradation Cascades in Cobalt-Free LiNiO 2 Lithium-Ion Battery Cathodes

LiNiO 2 (LNO) is a promising cathode material for next-generation Li-ion batteries due to its exceptionally high capacity and cobalt-free composition that enables more sustainable and ethical large-scale manufacturing. However, its poor cycle life at high operating voltages over 4.1 V impedes its practical use, thus motivating efforts to elucidate and mitigate LiNiO 2 degradation mechanisms at high states of charge. Here, a multiscale exploration of high-voltage degradation cascades associated with oxygen stacking chemistry in cobalt-free LiNiO 2 , is presented. In this work, lattice oxygen loss is found to play a critical role in the local O3–O1 stacking transition at high states of charge, which subsequently leads to Ni-ion migration and irreversible stacking faults during cycling. This undesirable atomic-scale structural evolution accelerates microscale electrochemical creep, cracking, and even bending of layers, ultimately resulting in macroscopic mechanical degradation of LNO particles. By employing a graphene-based hermetic surface coating, oxygen loss is attenuated in LNO at high states of charge, which suppresses the initiation of the degradation cascade and thus substantially improves the high-voltage capacity retention of LNO. Overall, this study provides mechanistic insight into the high-voltage degradation of LNO, which will inform ongoing efforts to employ cobalt-free cathodes in Li-ion battery technology.

25 ENERGY STORAGE↗
DOE OSTI2022

A Top-Down Strategy to Engineer ActiveLayer Morphology for Highly Efficient and Stable All-Polymer Solar Cells

A major challenge hindering the further development of all-polymer solar cells (all-PSCs) employing polymerized small-molecule acceptors is the relatively low fill factor (FF) due to the difficulty in controlling the active-layer morphology. The issues typically arise from oversized phase separation resulting from the thermodynamically unfavorable mixing between two macromolecular species, and disordered molecular orientation/packing of highly anisotropic polymer chains. Herein, a facile top-down controlling strategy to engineer the morphology of all-polymer blends is developed by leveraging the layer-by-layer (LBL) deposition. Optimal intermixing of polymer components can be achieved in the two-step process by tuning the bottom-layer polymer swelling during top-layer deposition. Consequently, both the molecular orientation/packing of the bottom layer and the molecular ordering of the top layer can be optimized with a suitable top-layer processing solvent. A favorable morphology with gradient vertical composition distribution for efficient charge transport and extraction is therefore realized, affording a high all-PSC efficiency of 17.0% with a FF of 76.1%. The derived devices also possess excellent long-term thermal stability and can retain >90% of their initial efficiencies after being annealed at 65 °C for 1300 h. In conclusion, these results validate the distinct advantages of employing an LBL processing protocol to fabricate high-performance all-PSCs.

14 SOLAR ENERGY↗
DOE OSTI2025

3D Printing of Highly Porous Polypropylene Separators for Lithium‐Ion Batteries Using Fused Deposition Modeling and Thermally Induced Phase Separation

Appearing as one of the key-components of lithium-ion batteries (LIBs), this work specifically focuses on the additive manufacturing (AM) of custom-shape separators, facilitated by the filament material extrusion process, also called fused deposition modeling (FDM). The development and optimization of composite thermoplastic filament feedstocks combining polypropylene and paraffin wax, followed by the 3D printing of the separator membranes is shown. A post-processing step, based on thermal induced phase separation (TIPS), is introduced to promote porosity formation through removal of the paraffin wax sacrificial phase within the 3D printed items. Separators with different polypropylene/paraffin wax ratios are developed and the impact on printability, mechanical strength, porosity, and electrochemical performances, is thoroughly discussed. X-ray micro-computed tomography is employed to assess the geometric fidelity and to detect printing defects in a complex 3D lattice structure. The performance of the 3D printed porous separators is also compared to a commercial separator. This pioneering research establishes a foundation for the creation of porous separators that can adapt to and conform into 3D printed battery architectures with novel form factors, and also creates opportunities for the use of FDM and TIPS for a wide range of applications that employ porous structures beyond the energy storage field.

3D printing↗
DOE OSTI2021

PyCCE: A python package for custer correlation expansion simulations of spin qubit dynamics.

PyCCE, an open-source Python library for simulating the dynamics of spin qubits in a spin bath, is presented using the cluster-correlation expansion (CCE) method. PyCCE includes modules to generate realistic spin baths, employing coupling parameters computed from first principles with electronic structure codes, and enables the user to run simulations with either the conventional or generalized CCE method. Three use cases of the Python library are illustrated: the calculation of the Hahn-echo coherence time of the nitrogen-vacancy in diamond; the calculation of the coherence time of the basal divacancy in silicon carbide at avoided crossings; and the calculation for magnetic field orientation-dependent dynamics of a shallow donor in silicon. The complete documentation, downloadable tutorials, and installation instructions are available at https://pycce.readthedocs.io/en/latest/.

coherence↗