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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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6 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Data-driven discovery of a formation prediction rule on high-entropy ceramics

The interest in high entropy ceramics (HECs) has increased steadily due to their superior properties. However, the prediction of their formation still poses challenges for the discovery of new systems. Here, we discover a rational rule for designing single-phase high entropy metal diborides (HEBs) using data-driven approach. The machine learning (ML) model is trained on data collected via high-throughput experiments (HTEs). K nearest neighbor (KNN) model shows an experimental validation accuracy of 93.75%. By implementing interpretable ML method, we demonstrate that a mismatch of the bonds between boron and transition metals (δ B-TM ) dominates the formation of HEBs. We propose an empirical rule that HEBs favor forming a single phase when δ B-TM < 3.66; otherwise, multiphase. The rule has a high accuracy of 93.33% for new HEBs predictions. In addition, we contribute 165 high quality HEBs data in total, which can promote the development of materials informatics in HEBs. Furthermore, this data-driven strategy can be expanded to accelerate the search for new HECs, paving a pathway to design novel HECs with superior properties rapidly.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Synergic grain boundary segregation and precipitation in W- and W-Mo-containing high-entropy borides

The structures of W- and W-Mo-containing high-entropy borides (HEBs) are systematically studied by combining atomic-resolution transmission electron microscopy imaging, electron diffraction, and chemical analysis. Here, we reveal that W or W-Mo addition in HEBs leads to segregation of these elements to the grain boundaries (GBs). In the meantime, W- or W-Mo-rich precipitates also form along the GBs. Crystallographic analysis and atomic-scale imaging show that the GB precipitates in both W- and W-Mo-containing HEBs have a cube-on-cube orientation relationship with the matrix. With further strain analysis, the coherency of the precipitate/matrix interface is validated. Nanoindentation tests show that the simultaneous GB segregation and coherent precipitation, as a supplement to the grain hardening, provide additional hardening of the HEBs. Our work provides an in-depth understanding of the GB segregation and precipitation behaviors of HEBs. It suggests that GB engineering could be potentially used for optimizing the performance of high-entropy ceramics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Experimental investigation of thermal conductivity of high entropy ceramics

In this talk, we will present the experimental investigation of thermal conductivity of high entropy carbides (HEC) and borides (HEB) with different compositions. Thermal conductivity determines the capability of a material to transport thermal energy and is considered as one critical physical property, specially in the energy industry. Due to the presences of disordered cation sublattice, it is expected that thermal conductivity of high entropy ceramics is lower than the counterparts with simpler compositions, but the experimental studies are relatively few. Using laser-based spatial-domain and frequency-domain thermoreflectance technique, we measured thermal conductivity of HECs and HEBs in a temperature range from 77K to 773K. Furthermore, by focusing the laser using an objective lens, we were able to perform the thermal property mapping on samples with the spatial resolution of micrometer. Such measurements could reveal important microstructure information in a rapid and efficient way without using scanning electron microscopy. The high spatial resolution also enables thermal conductivity measurements on ion-irradiated HECs with the damage layer of merely 1.1µm. These measurements can provide valuable information to predict the performances of HECs and HEBs with different compositions and from different manufacturing processes, and in the extreme environments such as nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2021

Final Booster Complex Design for the Jefferson Lab Electron Ion Collider*

In this work we show the final iteration of the design for the booster complex of the Jefferson Lab EIC, which would have brought the ions from an energy (proton) of 150 MeV up to 12.1 GeV. This complex would have consisted of two figure-8 rings. The Low Energy Booster (LEB) which would have accelerated its protons from 150 MeV to 8 GeV, and has had its lattice tweaked to increase the effectiveness of chromaticity cancellations. The High Energy Booster (HEB) would have brought the 8 GeV protons up to 12.1 GeV. The HEB would in the tunnel that was designed for the collider rings, sitting on top of them. It has had a bypass around the interaction region added, as well as a cooling solenoid installed.

Nissen, E. A.↗
DOE OSTI2024

Improving the Freight Productivity of a Heavy-Duty, Battery Electric Truck by Intelligent Energy Management

This project aimed to enhance the range and reduce the operating costs of battery electric Class 8 trucks traveling over 250 miles daily. This was achieved through the development and implementation of an intelligent-Energy Management System (i-EMS) that leverages vehicle and operations data, physics-aware machine learning algorithms, and vehicle-to-cloud (V2C) connectivity. The project hypothesized that advanced machine learning algorithms and real-time data analytics could significantly improve the energy efficiency and range of these trucks. Key objectives included developing a physics-aware machine learning algorithm, implementing an i-EMS with V2C connectivity and physics-aware spatial data analytics (PSDA), and validating the system’s effectiveness with fleet partners HEB Companies and Murphy Logistics. Extensive data collection from vehicle operations, including vehicle characteristics, road conditions, and payload, was conducted. A machine learning algorithm was developed to predict energy consumption and enable proactive decision-making. The i-EMS was implemented on two Volvo VNR BEVs, with operators receiving charging and routing recommendations. Charging stations were installed at depot locations in Texas and Minnesota, with an additional on-route charger in Minnesota. Significant findings included a 14% range improvement for Murphy Logistics on a highway-driving eco-route and a 22% range improvement for HEB Companies on a city-driving eco-route. The i-EMS utilized rule-based methods and physics-based algorithms to predict and reduce energy consumption, with real-time monitoring and analysis through V2C connectivity enabling proactive decision-making. The project demonstrated the feasibility and economic viability of battery electric Class 8 trucks for long-haul operations, showcasing the potential of physics-aware machine learning in optimizing energy management. The successful implementation of the i-EMS in real-world scenarios validates its practical application and effectiveness, paving the way for the widespread adoption of battery electric vehicles in the freight transportation industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

High-Entropy Borides under Extreme Environment of Pressures and Temperatures

The high-entropy transition metal borides containing a random distribution of five or more constituent metallic elements offer novel opportunities in designing materials that show crystalline phase stability, high strength, and thermal oxidation resistance under extreme conditions. We present a comprehensive theoretical and experimental investigation of prototypical high-entropy boride (HEB) materials such as (Hf, Mo, Nb, Ta, Ti)B2 and (Hf, Mo, Nb, Ta, Zr)B2 under extreme environments of pressures and temperatures. The theoretical tools include modeling elastic properties by special quasi-random structures that predict a bulk modulus of 288 GPa and a shear modulus of 215 GPa at ambient conditions. HEB samples were synthesized under high pressures and high temperatures and studied to 9.5 GPa and 2273 K in a large-volume pressure cell. The thermal equation of state measurement yielded a bulk modulus of 276 GPa, in excellent agreement with theory. The measured compressive yield strength by radial X-ray diffraction technique in a diamond anvil cell was 28 GPa at a pressure of 65 GPa, which is a significant fraction of the shear modulus at high pressures. The high compressive strength and phase stability of this material under high pressures and high temperatures make it an ideal candidate for application as a structural material in nuclear and aerospace fields.

36 MATERIALS SCIENCE↗