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At least 829 records · Page 46

Ink Casting and 3D‐Extrusion Printing of Yb 14 MnSb 11 for High‐Temperature Thermoelectric Material

Abstract Complex shapes are created from Yb 14 MnSb 11 , a high‐temperature thermoelectric Zintl phase, via a two‐step process: i) layer‐by‐layer 3D‐extrusion of ink containing partially‐reacted powders which are ball‐milled from a blend of Yb, MnSb, and Sb powders; ii) heat treatment to synthesize the ternary compound Yb 14 MnSb 11 and densify the extruded powders. A high phase purity for Yb 14 MnSb 11 (83–94%) is achieved in both cast and 3D‐extruded ink specimens via a solid‐state reaction between Yb, MnSb, and Yb 4 Sb 3 during reactive sintering. Pressure‐free sintering at temperatures of 1200–1400 °C densifies the powders to 82% relative density but can also induce the decomposition of the Yb 14 MnSb 11 phase due to Yb sublimation. A process window with optimized sintering temperature and time is identified, achieving both low porosity and high phase purity and reaching a maximum zT = 0.61 at 1000 °C, about half of the maximum zT value for bulk Yb 14 MnSb 11 made via conventional processes (pressure sintering of precursor powders). The present approach – direct ink writing of ball‐milled powders, combined with reactive sintering – is a scalable and affordable method to fabricate thermoelectric legs with intricate 3D shapes, for enhanced performances in high‐temperature thermoelectric applications.

Chen, Ming [Department of Materials Science &amp, ↗

Quantum Annealing with Inequality Constraints: The Set Cover Problem

Abstract Quantum annealing is a promising method for solving hard optimization problems by transforming them into quadratic unconstrained binary optimization (QUBO) problems. However, when constraints are involved, particularly multiple inequality constraints, incorporating them into the objective function poses challenges. In this paper, the authors present two novel approaches for solving problems with multiple inequality constraints on a quantum annealer and apply them to the set cover problem (SCP). The first approach uses the augmented Lagrangian method to represent the constraints, while the second approach employs a higher‐order binary optimization (HUBO) formulation. The experiments show that both approaches outperform the standard approach for solving the SCP on the D‐Wave Advantage quantum annealer. The HUBO formulation performs slightly better than the augmented Lagrangian method in solving the SCP, but its scalability in terms of embeddability in the quantum chip is worse. The results demonstrate that the proposed augmented Lagrangian and HUBO methods can successfully implement a large number of inequality constraints, making them applicable to a broad range of constrained problems beyond the SCP.

Djidjev, Hristo N.↗

New Directions for Thermoelectrics: A Roadmap from High‐Throughput Materials Discovery to Advanced Device Manufacturing

Thermoelectric materials, which can convert waste heat into electricity or act as solid‐state Peltier coolers, are emerging as key technologies to address global energy shortages and environmental sustainability. However, discovering materials with high thermoelectric conversion efficiency is a complex and slow process. The emerging field of high‐throughput material discovery demonstrates its potential to accelerate the development of new thermoelectric materials combining high efficiency and low cost. The synergistic integration of high‐throughput material processing and characterization techniques with machine learning algorithms can form an efficient closed‐loop process to generate and analyze broad datasets to discover new thermoelectric materials with unprecedented performances. Meanwhile, the recent development of advanced manufacturing methods provides exciting opportunities to realize scalable, low‐cost, and energy‐efficient fabrication of thermoelectric devices. This review provides an overview of recent advances in discovering thermoelectric materials using high‐throughput methods, including processing, characterization, and screening. Advanced manufacturing methods of thermoelectric devices are also introduced to realize the broad impacts of thermoelectric materials in power generation and solid‐state cooling. In the end, this article also discusses the future research prospects and directions.

Song, Kaidong↗

Hydrogen underground storage for grid electricity storage: An optimization study on techno-economic analysis

Here, this study performs a techno-economic analysis of hydrogen underground storage systems for grid electricity storage, evaluating their economic viability at the plant scale using dynamic optimization. It explores the feasibility of various system configurations and revenue models in the context of volatile electricity prices and the necessity for multiple revenue streams. The hypothesis tested is that large-scale hydrogen storage, despite its low round-trip efficiency, can be economically viable with the right mix of revenue streams. This study uses scenario-based analysis to assess the impacts of different system configurations, including engaging in time-shifting arbitrage, ancillary service markets and blending hydrogen with natural gas. Results indicate potential annual net cash flows of up to $\$$1.5 million from ancillary services integration and $\$$5.2 million from natural gas blending, contingent on specific system sizes. The study concludes that hydrogen underground storage for grid electricity storage can be profitable, and emphasizes that proper system design and precise electricity price forecasting are crucial for optimizing system performance and economic returns. This research sets the stage for further investigations into the scalability of hydrogen storage systems and their broader implications for grid electricity storage and energy market dynamics.

25 ENERGY STORAGE↗

Versatile coating with multifunctional performance for solar steam generation

In this work, a new kind of material, composite complex coating (CCC), with multifunctional performance has been developed for solar steam generation. The CCC has many advantages: (a) Scalability. The fabrication process is facile and mild; it can be realized in aqueous solution at room temperature, without high pressure, toxic organic solvents, or complex equipment. (b) Cost-effectiveness. The reagents used for preparation of CCC are low-cost and readily available. (c) Universality and stability. CCC firmly adheres on surfaces of various substrates with diverse shapes (cotton, filter paper, wood, polyurethane sponge, and even chemically inert and highly hydrophobic polyvinylidene fluoride membranes), and can withstand rinsing treatment (3000 r/min for 96 h), cyclic frost-thaw test (-18 °C ⇌ 30 °C, 90 times), and both high and low pH environments. In addition, many other reported coatings, such as carbon black, fail under similar process strain. (d) Anti-crude oil-fouling property. The CCC possesses stable superhydrophilicity and underwater superoleophobicity, which collectively endow substrates with the ability to resist fouling by oils. (e) Broad and strong light absorption. CCC can transform various substrates with diverse shapes into black materials with broadband light absorption due to its d-d transitions and rough surface. Together, these properties of CCC enable substrates with nearly any structural design to be easily transformed into photothermal materials for efficient solar steam generation. Furthermore, as a proof of concept, poplar wood is treated with CCC, achieving a water evaporation rate of ~1.8 kg m-2 h-1 (one sun), which is a record among wood-based photothermal materials.

14 SOLAR ENERGY↗

Low resistance p-type contacts to monolayer WSe2 through chlorinated solvent doping

Tungsten diselenide (WSe 2 ) is a promising p-type semiconductor limited by high contact resistance (R C ) and the lack of a reliable doping strategy. Here, we demonstrate that exposing WSe 2 to chloroform provides simple and stable p-type doping. In monolayer WSe 2 transistors with Pd contacts, chloroform increases the maximum hole current by over 100× (>200 µA/µm), reduces R C to ~ 2.5 kΩ·μm, and retains an on/off ratio of 10 10 at room temperature. These improvements persist for over 8 months, survive a 150 °C thermal anneal, and remain effective down to 10 K, enabling a cryogenic R C of ~ 1 kΩ·μm. Density functional theory indicates that chloroform strongly physisorbs to WSe 2 , inducing hole doping with minimal impact on the electronic states between the valence band and conduction band edges. Auger electron spectroscopy and atomic force microscopy suggest that chloroform intercalates at the WSe 2 interface with the gate oxide, contributing to doping stability and mitigating interfacial dielectric disorder, though further studies are needed to conclusively confirm this mechanism. This robust, scalable approach enables high-yield WSe 2 transistors with good p-type performance.

42 ENGINEERING↗

Fast and flexible analysis of direct dark matter search data with machine learning

We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor of 30 when compared with the previous approach, without loss of performance on real data. We establish its flexibility to capture non-linear correlations between variables (such as smearing in light and charge signals due to position variation) by achieving equal performance using pulse areas with and without position-corrections applied. Its efficiency and scalability furthermore enables searching for dark matter using additional variables without significant computational burden. We demonstrate this by including a light signal pulse shape variable alongside more traditional inputs such as light and charge signal strengths. Furthermore, this technique can be exploited by future dark matter experiments to make use of additional information, reduce computational resources needed for signal searches and simulations, and make inclusion of physical nuisance parameters in fits tractable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Robust and Scalable Software Library for Parallel Adaptive Refinement on Unstructured Meshes

The design and implementation of Pyramid, a software library for performing parallel adaptive mesh refinement (PAMR) on unstructured meshes, is described. This software library can be easily used in a variety of unstructured parallel computational applications, including parallel finite element, parallel finite volume, and parallel visualization applications using triangular or tetrahedral meshes. The library contains a suite of well-designed and efficiently implemented modules that perform operations in a typical PAMR process. Among these are mesh quality control during successive parallel adaptive refinement (typically guided by a local-error estimator), parallel load-balancing, and parallel mesh partitioning using the ParMeTiS partitioner. The Pyramid library is implemented in Fortran 90 with an interface to the Message-Passing Interface (MPI) library, supporting code efficiency, modularity, and portability. An EM waveguide filter application, adaptively refined using the Pyramid library, is illustrated.

Lou, John Z.↗

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Guruswamy, Guru P.↗

Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems

A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.

Guruswamy, Guru P.↗

Polyphony: A Workflow Orchestration Framework for Cloud Computing

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

Space Exploration,↗

High Density Vertiplex - Scalable Autonomous Operations - Flight Test Report

This Technical Memorandum describes the approach taken within the High Density Vertiplex Project to perform rapid prototyping and assessment of the UAM Ecosystem including representative: Onboard Autonomous Systems, Ground Control and Fleet Management Systems, Airspace Management Systems, and Vertiport Automation Systems (VAS). Small Uncrewed Aerial Systems (sUAS) were employed as effective low risk and inexpensive surrogates for larger proposed UAM aircraft to accelerate the prototyping effort, ensure safety, greatly mitigate costs, and accelerate progress. Flight testing performed included multivehicle operations where usability Human Factors (HF) data was collected on the operators.

Jacob Schaefer↗

Piezoelectric deformable photonic devices

A CMOS-compatible actuator platform for implementing phase, amplitude, and frequency modulation in silicon nitride photonic integrated circuits via piezo-optomechanical coupling using tightly mechanically coupled aluminum nitride actuators is disclosed. The platform, which may be fabricated in a CMOS foundry, enables scalable active photonic integrated circuits for visible wavelengths, and the piezoelectric actuation functions without performance degradation down to cryogenic operating temperatures. A number of devices are possible, including ring modulator devices, phase shifter devices, Mach-Zehnder interferometer devices, directional coupler devices (including tunable directional coupler devices), and acousto-optic modulator and frequency shifter devices, each of which can employ the same AlN actuator platform. As all of these devices can be built on the same AlN actuator platform, numerous optical functions can be implemented on a single die.

Eichenfield, Matt↗

Additive Manufacturing of Porous Ceramics With Foaming Agent

The macro-porous ceramics has promising durability and thermal insulation performance. As porous ceramics find more and more applications across many industries, a cost-effective and scalable additive manufacturing technique for fabricating macro-porous ceramics is highly desirable. Herein, we reported a facile additive manufacturing approach to fabricate porous ceramics and control the printed porosity. Several printable ceramic inks were prepared, and the foaming agent was added to generate gaseous bubbles in the ink, followed by the direct ink writing and the ambient-pressure and room-temperature drying to create the three-dimensional geometries. In this work, a set of experimental studies were performed to optimize the printing quality. The results revealed the optimal process parameters for printing the foamed ceramic ink with a high spatial resolution and fine surface quality. Varying the concentration of the foaming agent enables the controllability of the structural porosity. The maximum porosity can reach 85%, with a crack-free internal porous structure. The tensile tests showed that the printed macro-porous ceramics possessed enhanced durability with the addition of fiber. With a high-fidelity three-dimensional (3D) printing process and the precise controllability of the porosity, we showed that the printed samples exhibited a remarkably low thermal conductivity and durable mechanical strength.

36 MATERIALS SCIENCE↗

Scalable Polymeric Few-Nanometer Organosilica Membranes with Hydrothermal Stability for Selective Hydrogen Separation

Nanoporous silica membranes exhibit excellent H 2 /CO 2 separation properties for sustainable H 2 production and CO 2 capture but are prepared via complicated thermal processes above 400 °C, which prevent their scalable production at a low cost. Here, we demonstrate the rapid fabrication (within 2 min) of ultrathin silica-like membranes (~3 nm) via an oxygen plasma treatment of polydimethylsiloxane-based thin-film composite membranes at 20 °C. The resulting organosilica membranes unexpectedly exhibit H2 permeance of 280-930 GPU (1 GPU = 3.347 x 10 -10 mol m -2 s -1 Pa -1 ) and H2/CO2 selectivity of 93-32 at 200 °C, far surpassing state-of-the-art membranes and Robeson’s upper bound for H 2 /CO 2 separation. When challenged with a 3 d simulated syngas test containing water vapor at 200 °C and a 340 d stability test, the membrane shows durable separation performance and excellent hydrothermal stability. The robust H 2 /CO 2 separation properties coupled with excellent scalability demonstrate the great potential of these organosilica membranes for economic H 2 production with minimal carbon emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗

Software-defined network for end-to-end networked science at the exascale

Domain science applications and workflow processes are currently forced to view the network as an opaque infrastructure into which they inject data and hope that it emerges at the destination with an acceptable Quality of Experience. There is little ability for applications to interact with the network to exchange information, negotiate performance parameters, discover expected performance metrics, or receive status/troubleshooting information in real time. The work presented here is motivated by a vision for a new smart network and smart application ecosystem that will provide a more deterministic and interactive environment for domain science workflows. The Software-Defined Network for End-to-end Networked Science at Exascale (SENSE) system includes a model-based architecture, implementation, and deployment which enables automated end- to-end network service instantiation across administrative domains. An intent based interface allows applications to express their high-level service requirements, an intelligent orchestrator and resource control systems allow for custom tailoring of scalability and real-time responsiveness based on individual application and infrastructure operator requirements. This allows the science applications to manage the network as a first-class schedulable resource as is the current practice for instruments, compute, and storage systems. Deployment and experiments on production networks and testbeds have validated SENSE functions and performance. Emulation based testing verified the scalability needed to support research and education infrastructures. Key contributions of this work include an architecture definition, reference implementation, and deployment. This provides the basis for further innovation of smart network services to accelerate scientific discovery in the era of big data, cloud computing, machine learning and artificial intelligence.

47 OTHER INSTRUMENTATION↗