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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High Performing and Durable Pyrophosphate Based Composite Membranes for Intermediate Temperature Fuel Cells [Slides]

Objective: Develop a novel proton conducting electrolyte operating at >200°C with conductivity σ ≥ 100 mScm –1 and RH < 1%. Fabrication of membranes of less than 40μm thickness while retaining high conductivity will result in ASR <0.04 Ωcm 2 . Evaluate membrane durability in terms of crossover, shorting resistance, and open circuit voltage, as well as against temperature cycling. Relevance: Operating FCs in the intermediate temperature range has the potential to greatly reduce cost and simplify water and thermal management. This effort requires novel materials and approaches to meet DOE membrane performance and durability targets. MPP/Polymer composite membranes show promise in early development for application in IT-FCs for transportation applications. Approach: We have demonstrated that both cation dopants and phosphate precursor influence MPP conductivity and identified the most promising MPP compositions for membrane fabrication. The ceramic MPP materials are fabricated as a composite membrane in a 90:10 wt% ratio with Nafion. We have modified our membrane fabrication procedure to improve the density of our membranes. Accomplishments: We demonstrated through-plane membrane conductivity of 95mScm -1 at T > 200°C and RH<0.04bar with a thickness 50μm. We demonstrated FC performance up to 94hrs at 220°C and <1% RH with a 50μm thick membrane exhibiting an OCV of 0.98V and ASR of 0.08 Wcm 2 . Future work: Further decrease in ASR is expected by decreasing the membrane thickness to <40μm. ITPP with higher P:M ratio will be used to increase the conductivity of the starting material. Long term durability will be assessed against DOE technical targets

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Materials Characterization Techniques Lecture Series: X-Ray Diffraction, A Summary of LANL's Materials Capabilities in MPA-11 [Slides]

This presentation provides an overview on X-Ray Diffraction (XRD) to cover background, fundamentals, limitations, best practices, applications, analysis, software, and resources. To summarize: XRD is a great tool for characterizing solid crystalline samples. X-Rays are E-Mag radiation and generate diffraction profiles based on the phase of the sample. Diffraction patterns are unique to the phase of the sample. Powder diffraction gives us better diffraction profiles. We can obtain both qualitative and quantitative data. Analysis requires us to know a little about our sample and a lot about our diffractometer.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Intermetallic PtCo Catalysts with Enhanced Performance and Stability [Slides]

Pt-based catalysts need systematic modifications to be adapted to different applications (LDV or HDV). L1 0 -CoPt particles have been demonstrated as highly active and durable cathode materials for fuel cells. Colloidal synthesis can generate catalysts with highly uniform particles size but the removal of surfactants is challenging. Acid leaching warrants a Pt shell with certain thickness, which mitigates the Co leaching. Controlling the size of L1 0 -CoPt particles is a robust method to alter their catalytic behaviours and tailor the function of catalysts. Modifying the carbon features (e.g. porosity and graphitization) is an effective method to regulate the performance and stability of catalysts to adapt the catalysts to different applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Tardigrade (NA-22 Quarterly Report)

Tardigrade is an effort to create tunable thermal expansion materials for use in a ruggedized lens housing. This requires new computational algorithms to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. The project is 24 months into the 36-month plan. We are continuing effort on 3 main technical thrusts: material design algorithm development (transitioning into full 3D design), multi-material additive manufacturing process exploration, and sensor/optics design and engineering. In the last quarter, we have focused on developing the code for 3D Topology Optimization, building data sets for 2D autoencoder training, and finishing lens housing engineering for the microbolometer based test sensor. We are exploring 2 potential multi-material AM technologies, a polymer-based technique in development at LLNL and a metal SLS system produced by Aconity, called the AeroSint deposition head.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tardigrade (Quarterly Report Q1 FY2022)

Tardigrade is an effort to create tunable thermal expansion materials for use in a ruggedized lens housing. This requires new computational algorithms to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. The project is 27 months into the 36-month plan. We are continuing effort on 3 main technical thrusts: material design algorithm development (transitioning into full 3D design), multi-material additive manufacturing process exploration, and sensor/optics design and engineering. In the last quarter, we have focused on developing the code for 3D Topology Optimization, building data sets for 2D autoencoder training, and finishing lens housing engineering for the microbolometer based test sensor. We are exploring 2 potential multi-material AM technologies, a polymer-based technique in development at LLNL and a metal SLS system produced by Aconity, called the AeroSint deposition head.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS

The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exceptional Points in Novel Multiscale Quantum-Nanoplasmonic Materials for Enhanced Sensing and Other Applications

Lossy quantum systems can display fascinating behaviors around singularities known as exceptional points in their complex eigenvalue spaces. Interest in these systems was ignited over two decades ago when Carl Bender and Stefan Boettcher—a LANL Director’s Postdoctoral Fellow at the time—pointed out that many features of conventional lossless quantum systems, such as real operator eigenvalues, could be recovered in lossy systems exhibiting parity- and time-reversal (ΡΤ) symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploring strongly correlated quantum spin systems with quantum computers

At inception, quantum annealing leveraged quantum mechanics for classical optimization tasks. However, as machine coherence increases, the realization of quantum spin systems has emerged as an even more fruitful application of this computational model. Alternatives to the standard gate model deserve exploration, to achieve useful quantum advantage via analog quantum computing. The recent demonstration of so-called coherent quantum annealing with 1,000s of qubits, further expands the potential for this hardware to explore quantum system dynamics where the effects of quantum fluctuations can be carefully controlled and observed directly. Implementing existing celebrated spin models—or in fact new and dedicated ones—into quantum annealers will lead to observation and detection of quantum phenomena not yet observed, or not visualized directly, in experimental physics laboratories. Rather than computing or simulating quantum systems, these quantum computers allow one to simply build quantum systems, and experiment on them in an uniquely controlled way, with characterization down to the constitutive degree of freedom. This provides an unprecedented opportunity for understanding the physics of quantum spin systems. Keywords: Theoretical physics currently abounds of interesting theoretical spin models to explore frustration, strongly correlated spins, spin liquids, fractionalized excitations, and topological matter. However enticing, such models are generally only weak proxies for the properties of actual materials. In quantum annealers these models could be realized and experimented upon. Moreover, many more realistic models of such materials could be realized in quantum annealers. Employed in this way, quantum annealers provide an extraordinary versatile platform to explore quantum effects that are hard to find, detect, and characterize in natural materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Using Magnetic Proximity Effects to Build Designer Quantum Materials [Slides]

The properties of naturally occurring materials are not necessarily commensurate with those needed for next-generation devices. Counter to conventional thought, we find magnetic proximity effects can be asymmetric. In fact, our experimental data and DFT calculations indicate this effect is universal, with material and heterostructure specificity being vital for predictive modeling. This work suggests routes towards rational design of device component materials via selective control over spin valley states.

36 MATERIALS SCIENCE↗