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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Enhancing the multi-functional properties of renewable lignin carbon fibers via defining the structure–property relationship using different biomass feedstocks

Lignin has been explored extensively as a renewable precursor for carbon materials, considering its abundance as a major component of plant cell walls and its sustainability as a byproduct of both lignocellulosic biorefinery and the paper-making industry. Despite the extensive efforts to define the process–property relationship, it remains largely unknown how lignin biosynthesis and its chemistry would impact the resultant carbon fiber properties, for both mechanical and electroconductive performances. Such inadequate understanding fundamentally limits feedstock design and selection to improve carbon fiber properties toward broader commercial applications. Using lignin from a broad range of biomass feedstocks for carbon fiber manufacturing, we have fundamentally explored the structure–function relationship between lignin chemistry and carbon fiber performance. Specifically, lignin extracted from hardwood (sugar maple), softwood (loblolly pine and red cedar), and herbaceous plants (corn stover and switchgrass) was used for carbon fiber manufacturing, considering the very different lignin structures from these feedstocks. Linear regression models were established to define the relationship between carbon fiber mechanical properties and lignin structural characteristics. The results highlighted that the content of β-O-4 linkages correlates significantly with the tensile strength and elastic modulus of lignin carbon fibers, indicating that more linear β-O-4 linkages would promote the carbon fiber mechanical performance. Moreover, electroconductive properties are essential for broader energy device application of lignin-based carbon fibers, yet the mechanisms controlling their electroconductivity are largely unknown. Furthermore, we hereby demonstrated that a higher β-O-4 content also promotes the electroconductivity of lignin carbon fibers. Microstructure analysis further revealed that the crystallite size and content of the pre-graphitic turbostratic carbon structure in lignin-based carbon fibers were enhanced as the β-O-4 linkages increased. The content of β-O-4 linkages has shown a strong correlation with the crystallite content in a linear regression model. This study thus revealed the underlying mechanisms regarding how the lignin structure in planta defines the resultant carbon fiber properties. Moreover, the study also highlighted the correlation between the mechanical and electroconductive properties of lignin-based carbon fibers, both of which were defined by the lignin structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Electro-strengthening of the additively manufactured Ti–6Al–4V alloy

Structure-property-processing relationship has been studied in additively manufactured Ti–6Al–4V alloy. The processing was performed using in-situ electron microscope (EM) at a moderate current density of 5 × 105 A/cm2 applied for 5 min, and by suppressing Joule heating with massive heat sinks such that the temperature rise was <180 °C and the mechanical properties were not compromised. Overall, the results show that while the grain size increased by ~15%, the nanohardness increased by 16%. This is attributed to the pronounced dislocation generation, regeneration, and clustering as well as defect healing. Ultimately, there is a reduction in the residual strain and a significant increase in the intrinsic strength as evidenced by the high Taylor factor of the electric current processed specimen. This novel processing technique represents an alternative pathway for active controlling of microstructure and internal defects for parts that might be sensitive to high-temperature processing or conventional methods.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Achieving Innovation and Affordability Through Standardization of Materials Development and Testing

The successful expansion of development, innovation, and production within the aeronautics industry during the 20th century was facilitated by collaboration of government agencies with the commercial aviation companies. One of the initial products conceived from the collaboration was the ANC-5 Bulletin, first published in 1937. The ANC-5 Bulletin had intended to standardize the requirements of various government agencies in the design of aircraft structure. The national space policy shift in priority for NASA with an emphasis on transferring the travel to low earth orbit to commercial space providers highlights an opportunity and a need for the national and global space industries. The same collaboration and standardization that is documented and maintained by the industry within MIL-HDBK-5 (MMPDS-01) and MIL-HBDK-17 (nonmetallic mechanical properties) can also be exploited to standardize the thermal performance properties, processing methods, test methods, and analytical methods for use in aircraft and spacecraft design and associated propulsion systems. In addition to the definition of thermal performance description and standardization, the standardization for test methods and analysis for extreme environments (high temperature, cryogenics, deep space radiation, etc) would also be highly valuable to the industry. Its subsequent revisions and conversion to MIL-HDBK-5 and then MMPDS-01 established and then expanded to contain standardized mechanical property design values and other related design information for metallic materials used in aircraft, missiles, and space vehicles. It also includes guidance on standardization of composition, processing, and analytical methods for presentation and inclusion into the handbook. This standardization enabled an expansion of the technologies to provide efficiency and reliability to the consumers. It can be established that many individual programs within the government agencies have been overcome with development costs generated from these nonstandard requirements. Without industry standardization and acceptance, the programs are driven to shoulder the costs of determining design requirements, performance criteria, and then material qualification and certification. A significant investment that the industry could make to both reduce individual program development costs and schedules while expanding commercial space flight capabilities would be to invest in standardizing material performance properties for high temperature, cryogenic, and deep space environments for both metallic and nonmetallic materials.

Bray, M. H.↗
DOE OSTI2020

Perspectives on the relationship between materials chemistry and roll-to-roll electrode manufacturing for high-energy lithium-ion batteries

As lithium-ion battery (LIB) active material and cell manufacturing costs continue to drop with wider adoption of electric vehicles, electrode and cell processing costs remain too high in terms of reaching the ultimate U.S. Department of Energy (DOE) cell cost target of $80/kWh. This paper primarily covers major materials chemistry advancements made over the last 10 years at Oak Ridge National Laboratory (ORNL) in the space of advanced manufacturing science for LIBs with the aim of simultaneously meeting the ultimate cost target, 500 Wh/kg gravimetric energy density, 10-15-min fast charge times, and 1000 deep discharge cycles. Aqeous electrode processing with a variety of active anode and cathode materials is now a standard procedure at the DOE Battery Manufacturing R&D Facility at ORNL (BMF), including the latest processes developed for Ni-rich cathodes. New results on cobalt-free LiNi 0.8 Fe 0.1 Al 0.1 O 2 (NFA 811) are also included and discussed in an electrode processing advantage context. In addition, colloidal processing advancements have been made for Si/C composite anodes for achieving >600 mA h/g capacities. Optimization of electrode coating parameters and drying protocols have been completed, which has elucidated how key processing variables need to be changed when parameters such as slurry solids loading, solvent type, and wet electrode thickness are changed. ORNL has also increased the line speeds at which thick cathodes can be processed using ultra-fast electron beam (EB) curing and substantially decreased formation cycling times to <1 day. Finally, key details of these advancements are discussed in the context of materials chemistry and process-property-performance relationships.

25 ENERGY STORAGE↗
NASA NTRS1991

Sensor-model in-situ control of the RTM composite process

The paper reports on the use of in situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model to select and control the processing properties of an epoxy resin during RTM impregnation and cure. Once correlated with viscosity and degree of cure, FDEMS monitors the advancement of the resin, viscosity, and the impregnation of the fabric, allowing a direct means of monitoring in situ in the mold throughout the fabrication process the effects of time, temperature, vacuum, and pressure.

Kranbuehl, D. E.↗
DOE OSTI2023

Correlating viscosity and die swell in 3D printing of polyphenylsulfone: A thermo-mechanical optimization modus operandi

Additive manufacturing (AM) of polyphenylsulfone (PPSU), an amorphous high-performance polymer (HPP), has shown promise in exhibiting structural integrity for many applications. With thermoplastic material extrusion 3D printing, parts consisting of layered melts exhibited voids, where the adhesion quality and void size depend on the processing parameters implemented during printing. However, the structure-process-property (SPP) relationships between the thermal properties and rheological and mechanical behavior of AM PPSU are poorly understood. Here, in this study, a comprehensive analysis of the thermal, thermo-mechanical, and layer-by-layer build-up of PPSU is investigated and correlated with viscosity and extrudate die swell behavior with void fraction volume as confirmed by high-resolution x-ray computed tomography (XCT). Gas chromatography–mass spectrometry (GC–MS) pyrolysis confirmed PPSU composition and degradation at 480 °C, consistent with thermo-gravimetric analysis TGA. A 141% difference in viscosity was observed when processing temperatures increased from 350 °C to 400 °C. Likewise, extrudate die swell decreased with increasing temperatures, resulting in a 17% difference. Tensile and compressive properties confirmed that higher extruding temperatures resulted in lower porosity and higher mechanical strength. In general, higher extruding temperatures lower the viscosity to allow for stronger cohesion between layers; however, increasing the temperature too high results in a below unity extrudate die swell, reducing mechanical properties. Therefore, to optimize the mechanical integrity of 3D printed amorphous PPSU parts, an increase in the viscosity, near unity of the extrudate die swell, and tempered extrusion temperature are needed.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Logarithmic spiral grids for image processing

A picture digitization grid based on logarithmic spirals rather than Cartesian coordinates is presented. Expressing this curvilinear grid as a conformal exponential mapping reveals useful image processing properties. The mapping induces a computational simplification that suggests parallel architectures in which most geometric transformations are effected by data shifting in memory rather than arithmetic on coordinates. These include fast, parallel noise-free rotation, scaling, and some projective transformations of pixel defined images. Conformality of the mapping preserves local picture-processing operations such as edge detection.

Weiman, C. F. R.↗
NASA NTRS1988

Monitoring cure of composite resins using frequency dependent electromagnetic sensing techniques

A nondestructive in situ measurement technique has been developed for monitoring and measuring the cure processing properties of composite resins. Frequency dependent electromagnetic sensors (FDEMS) were used to directly measure resin viscosity during cure. The effects of the cure cycle and resin aging on the viscosity during cure were investigated using the sensor. Viscosity measurements obtained using the sensor are compared with the viscosities calculated by the Loos-Springer cure process model. Good overall agreement was obtained except for the aged resin samples.

Kranbuehl, D. E.↗
DOE OSTI2022

5.1.6 Demo #6: NanoStitch (NAWAStitch) Multifunctional Composites Trade Validation

The overall objective of the NanoStitch Multifunctional Composites Trade Validation Demonstration project was to determine the value proposition of adding NanoStitch to rapid-cure composite systems for structures used in the expanding sector of advanced air mobility (AAM) and specifically electric vertical take-off and landing (eVTOL) aircraft. The expected value proposition was stronger composite parts, with new multifunctional attributes, that are lower cost to fabricate and maintain. NanoStitch is a new composite innovation where a contiguous vertically aligned carbon nanotube (VACNT) forest is located between each ply of a laminate composite resulting in improved mechanical properties as well as other multifunctional properties such as enhanced thermal and electrical conductivity. NanoStitch was originally distributed by N12, later acquired by NAWA Technologies, now called NAWAStitch, and henceforth referred to in this document as NAWAStitch. Two significant evaluations were framed to help meet the overall objective. First, was Task 1 to evaluate the effects that adding NAWAStitch to a rapid cure material system would have on the mechanical and processing properties of the material. Second, was Task 2 to evaluate the workability of adding NAWAStitch to practical flight demonstration articles. From previous research, it was already known that the application of NAWAStitch to a composite structure can enhance the mechanical properties of that structure. However, this project will help the engineering community understand those benefits and the basic structural strength values to apply when incorporating NAWAStitch material into composite structure that utilizes a rapid-cure resin system, which is novel. Testing showed that by adding NAWAStitch to the prepreg, most material properties were improved because the VACNTs strengthened the resin to fiber interface, and the interface itself, between plies. For example compression strength improved by more than 20%, and erosion resistance by more than 50%. The UDRI team identified two flight demonstration articles through discussions with Aurora Flight Sciences (Aurora) and reviewing literature on air mobility and the eVTOL market. The demonstration articles were a thin skin honeycomb panel and a section from an eVTOL propeller blade. The manufacturing and testing trials of the demonstration articles were as follows: • NAWAStitch added no manufacturing complexity or detriment to the article physical qualities, while at the same time added multifunctional properties such as enhanced rain erosion and electrothermal de-icing besides enhanced mechanical properties • VACNTs did not increase or hurt the mechanical properties of the interface between honeycomb core materials and the thin skin face sheet • Demonstrated successful de-icing function in an eVTOL propeller meeting real-world specifications in uniformity and endurance • Multifunctional eVTOL propeller cost analysis showed a cost savings of at least 67 % for a single propeller blade with multifunctional de-icing capability and improved mechanical properties which equates to a potential savings of $10,116 per eVTOL aircraft with six three-bladed propellers Overall, the results of this project can provide additional tools for the composite industry to optimize energy efficiency through faster and stronger composite parts that are lower cost to fabricate and maintain. Additionally, the results of this effort can help US industry like NAWA America set the stage for rapid growth and establishment of a manufacturing facility in Ohio. The project has given NAWA America the basic understanding of how the addition of VACNTs to a composite structure can affect the mechanical properties and hence point them to potential commercial applications. The project has also provided Teijin Carbon US with another potential material application for their rapid cure materials that are manufactured at the Renegade facility in Miamisburg, OH.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Experimental Observations of Mechanisms of Pattern Formation During Freeze Casting

Empirically, many different materials compositions have been freeze cast over the years. Few have been analyzed to better understand the mechanisms by which the ice crystal growth drives structure formation, particularly the substructures on the cell walls. Collating substructural features, for example, ridges, bridges, and “jellyfish-like” substructures, found on the cell walls of freeze-cast ceramics (platelets versus particles), fibrillated biopolymers (collagen, nanocellulose), and "smooth" biopolymers (chitosan, trehalose), we capture the ice crystal growth process and analyze it both in situ in 2D and "post-mortem" in 3D to gain insights into anisotropic ice crystal growth and other self-assembly mechanisms. Combining these experimental observations with 3D Phase-field simulations of structure formation in ice-templated materials, detailed in a companion presentation, it becomes possible to gain fundamental science insights and to obtain the desired structure-property-processing correlations not only at the more traditional macroscopic, but also at the meso- and microscopic scales.

Kaiyang Yin↗
NASA NTRSDate not supplied

Experimental Observations of Mechanisms of Pattern Formation During Freeze Casting

Empirically, many different materials compositions have been freeze cast over the years. Few have been analyzed to better understand the mechanisms by which the ice crystal growth drives structure formation, particularly the substructures on the cell walls. Collating substructural features, for example, ridges, bridges, and “jellyfish-like” substructures, found on the cell walls of freeze-cast ceramics (platelets versus particles), fibrillated biopolymers (collagen, nanocellulose), and "smooth" biopolymers (chitosan, trehalose), we capture the ice crystal growth process and analyze it both in situ in 2D and "post-mortem" in 3D to gain insights into anisotropic ice crystal growth and other self-assembly mechanisms. Combining these experimental observations with 3D Phase-field simulations of structure formation in ice-templated materials, detailed in a companion presentation, it becomes possible to gain fundamental science insights and to obtain the desired structure-property-processing correlations not only at the more traditional macroscopic, but also at the meso- and microscopic scales.

Kaiyan Yin↗
DOE OSTI2024

Improving Charge Transport and Environmental Stability of Carbohydrate-Bearing Semiconducting Polymers in Organic Field-Effect Transistors

Semiconducting polymers offer synthetic tunability, good mechanical properties, and biocompatibility, enabling the development of soft technologies previously inaccessible. Side-chain engineering is a versatile approach for optimizing these semiconducting materials, but minor modifications can significantly impact material properties and device performance. Carbohydrate side chains have been previously introduced to improve the solubility of semiconducting polymers in greener solvents. Despite this achievement, these materials exhibit suboptimal performance and stability in field-effect transistors. In this work, structure–property relationships are explored to enhance the device performance of carbohydrate-bearing semiconducting polymers. Toward this objective, a series of isoindigo-based polymers with carbohydrate side chains of varied carbon-spacer lengths is developed. Material and device characterizations reveal the effects of side chain composition on solid-state packing and device performance. With this new design, charge mobility is improved by up to three orders of magnitude compared to the previous studies. Processing–property relationships are also established by modulating annealing conditions and evaluating device stability upon air exposure. Notably, incidental oxygen-doping effects lead to increased charge mobility after 10 days of exposure to ambient air, correlated with decreased contact resistance. Bias stress stability is also evaluated. This work highlights the importance of understanding structure–property relationships toward the optimization of device performance

36 MATERIALS SCIENCE↗
NASA NTRS1973

Development of design allowables data for adhesives for attaching reusables surface insulation, addendum 1A

The task consisted of conducting mechanical and thermal tests to establish design allowables data on a new room temperature vulcanizing (RTV) silicone adhesive, X3-6004. Low modulus, coupled with relatively low density and good low-temperature properties of this adhesive, places it in contention as a candidate for attaching reusable surface insulation on the space shuttle. Data obtained show that the modulus values of X3-6004 are significantly lower than those of RTV-560 and the other three adhesives characterized at test temperatures from 550 to -175 F. At -175, -200 and -270 F, the modulus of X3-6004 is approximately the same as GE RTV-560 and the other three silicone adhesives. The X3-6004 adhesive exhibits good processing properties. It has a 12 percent lower density than RTV-560. Although lower in overall strength properties as compared to the other adhesives in the program, X3-6004 has adequate adhesion to 2024T81 aluminum to compete as an adhesive for attaching reusable surface insulation. It does exhibit some tendency to revert and soften at temperatures above 350 F when in a confined area.

Owen, H. P.↗
DOE OSTI2025

Engineered Barrier System Research Activities at SNL: FY25 Report

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

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Heterogeneous Structural Evolution of In–Zn–O Thin Films during Annealing

Amorphous In-Zn-O (a-IZO) thin films are among the most promising transparent conducting materials. Applications of a-IZO include thin film transistors for display technology and photovoltaic devices. However, the use of this material in practical devices has been impeded by limitations in our understanding of the relationship between a-IZO film structure and electrical properties. Here, we use in situ X-ray reflectivity to provide experimental evidence for a vertically heterogeneous, thermally induced structural relaxation that had been predicted for amorphous oxide films but not previously observed. The structural relaxation is shown to be dependent on the thermal annealing environment. Complementary in situ current-voltage curves and ex situ Van der Pauw measurements further show that thermal annealing also influences the electrical performance of the films. Here our results suggest that both oxygen uptake and structural relaxation contribute to the reduction in free carriers within a-IZO films during postdeposition processing. The structural heterogeneity and loss of carriers that occur during thermal annealing are only partly reversible. We anticipate that this insight into the structure-processing-property relationships within a-IZO will help to enable a-IZO-based devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗
DOE OSTI2026

Statistical generic design of glass and optimization: Selective review on oxide glasses

Designing a single glass composition for a multidimensional property space is challenging, and the difficulty increases with the number of design criteria. Traditionally, the task is accomplished using multiple statistical models that describe the relationships between composition (C) and property (P) values, i.e., C-P models. Recently, the structure (S)-property (P) statistical modeling has emerged as a complementary approach. The S-P modeling approach has also been shown to be a preferred method for modeling glass properties, particularly when a small data set is available, such as in single-component studies, or when strong nonlinearities exist between composition and properties. The combined model package, C-S-P, implements the concept of generic glass design, i.e., designing glass for performance by first selecting a specific or optimized set of glass network structural groups using S-P models and then transferring the designed structures (genes) to a particular composition using C-S models. This article reviews a set of supporting cases from the previous C-S-P modeling studies of phosphate, silicate, and borosilicate glasses, which are relevant for many critical commercial applications. The methodology for developing the statistical C-S-P database is presented, enabling the application of P?S?C to achieve a generic glass design and optimization, targeting multiple design criteria for both performance and processing properties simultaneously.

Network structure↗