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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Thermal hysteresis controlled reconfigurable MoS 2 nanomechanical resonators

Two-dimensional (2D) structures from layered materials have enabled a number of novel devices including resonant nanoelectromechanical systems (NEMS). 2D NEMS resonators are highly responsive to strain, allowing their resonance frequencies to be efficiently tuned over broad ranges, which is a feature difficult to attain in conventional micromachined resonators. In electrically configured and tuned devices, high external voltages are typically required to set and maintain different frequencies, limiting their applications. Here we experimentally demonstrate molybdenum disulfide (MoS 2 ) nanomechanical resonators that can be reconfigured between different frequency bands with zero maintaining voltage in a non-volatile fashion. By leveraging the thermal hysteresis in these 2D resonators, we use heating and cooling pulses to reconfigure the device frequency, with no external voltage required to maintain each frequency. Here, we further show that the frequency spacing between the bands can be tuned by the thermal pulse strength, offering full control over the programmable operation. Such reconfigurable MoS 2 resonators may provide an alternative pathway toward small-form-factor and low-power tunable devices in future reconfigurable radio-frequency circuits with multi-band capability.

42 ENGINEERING↗
DOE OSTI2024

Ferroelectric FET-based context-switching FPGA enabling dynamic reconfiguration for adaptive deep learning machines

Field programmable gate array (FPGA) is widely used in the acceleration of deep learning applications because of its reconfigurability, flexibility, and fast time-to-market. However, conventional FPGA suffers from the trade-off between chip area and reconfiguration latency, making efficient FPGA accelerations that require switching between multiple configurations still elusive. Here, we propose a ferroelectric field-effect transistor (FeFET)–based context-switching FPGA supporting dynamic reconfiguration to break this trade-off, enabling loading of arbitrary configuration without interrupting the active configuration execution. Leveraging the intrinsic structure and nonvolatility of FeFETs, compact FPGA primitives are proposed and experimentally verified. The evaluation results show our design shows a 63.0%/74.7% reduction in a look-up table (LUT)/connection block (CB) area and 82.7%/53.6% reduction in CB/switch box power consumption with a minimal penalty in the critical path delay (9.6%). Besides, our design yields significant time savings by 78.7 and 20.3% on average for context-switching and dynamic reconfiguration applications, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Fabrication Strategy for Reconfigurable Millimeter–Scale Metamaterials

Rather than depending on material composition to primarily dictate performance metrics, metamaterials can leverage geometry to achieve specific properties of interest. For example, reconfigurable metamaterials have enabled programmable shape transformations, tunable mechanical properties, and energy absorption. While several methods exist to fabricate such structures, they often place severe restrictions on manufacturing materials, or require significant manual assembly. Moreover, these arrays are typically composed of unit cells that are either macro–scale or micro–scale in dimension. Here, the fabrication gap is bridged, and laminate manufacturing is used to develop a method for designing reconfigurable metamaterials at the millimeter–scale, that is compatible with a wide range of materials, and that requires minimal manual assembly. In addition to showing the versatility of this fabrication method, how the use of laminate manufacturing affects the behavior of these multi–component arrays is also characterized. To this end, a numerical model that captures the deformations exhibited by the structures is developed, and an analytic model that predicts the strain of the structure under compressive stress is built. Overall, this approach can be leveraged to develop millimeter–scale metamaterials for applications that require reconfigurable materials, such as in the design of tunable acoustics, photonic waveguides, and electromagnetic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Repairable and Reconfigurable Structured Liquid Circuits

The advance of printed electronics is significantly bolstered by the development of liquid-state electronics that overcome the inherent limitations in flexibility and reconfigurability of solid-state electronics. By integrating the biocompatibility and conductivity of sulfonated polyaniline (S-PANI) and phytic acid (PA) with the reconfigurability of structured liquids, highly conductive all-liquid threads are developed. The dense packing and overlap of PA/S-PANI complexes at an oil/water interface promotes in-plane electron transport, and standard four-point probe measurements of PA/S-PANI interfacial assemblies demonstrate enhanced electrical properties. Notably, the rapid jetting of the ink phase into the matrix phase allows for liquid threads to be printed, enabling the fabrication of large-scale, conductive pathways between two electrodes and liquid circuits. Upon mechanical cleavage of the liquid wires, circuits can be broken, but will easily self-repair using an electric field, making this motif useful in the design of switches as well as restoring conductive pathways in series or in parallel. In conclusion, the demonstrated flexibility and reconfigurability these PA/S-PANI wires possess hold significant promise for their practical use in the design of flexible and adaptive bioelectronics that can be repaired on demand, signifying a transformative step in the evolution of liquid electronic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reconfiguration of Amorphous Complex Oxides: A Route to a Broad Range of Assembly Phenomena, Hybrid Materials, and Novel Functionalities

This work demonstrate that reconfiguration of amorphous oxide layers drives the assembly of oxide-based and freestanding nanomembranes into 3D structures with a radius of a few hundred nanometers. Reconfiguration-driven assembly is a versatile approach to impart large strains and strain gradients in a broad palette of complex oxides. This capability allows for manipulating and enhancing ferroelectricity, flexoelectricity, piezoelectricity, superconductivity, and ferromagnetism in complex oxides. Moreover, by the approach presented in this work, strain-engineered oxides are obtained in the form of 3D structures that can be fabricated in parallel on any substrate, including large-area and single crystalline semiconductor substrates. This approach will create a vast expanse of possibilities to investigate and leverage strain-tunable effects in amorphous, poly-crystalline, and single-crystalline complex oxides. Reconfiguration-driven assembly of NMs also allows combining different materials in a radial geometry and through scalable processes. For example, radial superlattices of Si (or GaAs) and various complex oxides or alternating layers of different complex oxides (e.g., SrTiO 3 and LaAlO 3 ) could be fabricated by release and heating of bilayer NMs. Here, a broad palette of electronic band structures and spin–orbit interactions could then be obtained by tailoring the curvature of the self-assembled NMs and the materials that the heterostructure comprises.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Seasonal Reconfiguration of Electrical Distribution Systems to Mitigate the Impact of Electric Vehicle Charging

Power grids face challenges in their infrastructure related to the integration of electric vehicles (EV). In particular, EV charging stations may induce instability in key system parameters such as substantial voltage drops, active power losses, and transformer overload due to high demand during charging periods. This article presents a seasonal reconfiguration strategy based on the differential evolution (DE) algorithm, aimed at enhancing system performance under highly variable and stochastic load profiles, particularly those driven by EV charging. The DEA algorithm is hybridized with the find-union (FU) algorithm to efficiently ensure network radiality throughout the optimization process. The proposed methodology is validated on a hybrid distribution system composed of the IEEE 33-bus network, a modified IEEE 13-bus system, and a specific 13-bus microgrid. Results have demonstrated that seasonal reconfiguration significantly reduces active power losses and mitigates transformer loading during critical demand hours, thereby quantifiably increasing the system’s performance. As an integral component of the proposed approach, an analysis of CO2 emissions associated with energy losses is included, allowing a contextualized assessment of the environmental benefits of seasonal reconfiguration in various geographical areas.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Physics-Informed Graph Neural Networks for Collaborative Dynamic Reconfiguration and Voltage Regulation in Unbalanced Distribution Systems

Network reconfiguration has long been employed as a strategic approach to minimize power distribution system losses and effectively regulate voltage levels. Tap-changing voltage regulators are also critical for controlling bus voltages, especially in accommodating the increasing integration of distributed energy resources (DERs) with intermittent outputs. This paper introduces novel methodologies to address the challenges of dynamic reconfiguration and optimal tap setting in unbalanced three-phase distribution systems. We propose an approximated mixed-integer quadratically constrained program (MIQCP) to model dynamic reconfiguration, along with a pioneering formulation for voltage regulator (VR) tap-setting based on Special Ordered Set type 1 (SOS1). To mitigate computational complexity, we propose a physics-informed spatial-temporal graph convolutional network (STGCN) with an integrated link classifier. The proposed approach enables efficient solution generation by fixing specific variables in the MIQCP instance and solving the simplified sub-MIP using an MIP solver. Numerical studies demonstrate the superior prediction accuracy of our STGCN model compared to baseline neural network models, resulting in reduced DER curtailment and voltage deviation with shorter computation time.

dynamic reconfiguration↗
DOE OSTI2023

Exploring the Performance Boundaries of a Small Reconfigurable Multi-Mission UAV through Multidisciplinary Analysis

The performance of a small reconfigurable unmanned aerial vehicle (UAV) is evaluated, combining a multidisciplinary approach in the computational analysis of additive manufactured structures, fluid dynamics, and experiments. Reconfigurable UAVs promise cost savings and efficiency, without sacrificing performance, while demonstrating versatility to fulfill different mission profiles. The use of computational fluid dynamics (CFD) in UAV design produces higher accuracy aerodynamic data, which is particularly important for complex aircraft concepts such as blended wing bodies. To address challenges relating to anisotropic materials, the Tsai–Wu failure criterion is applied to the structural analysis, using CFD solutions as load inputs. Aerodynamic performance results show the low-speed variant attains an endurance of 1 h, 48 min, whereas its high-speed counterpart is 29 min at a 66.7% higher cruise speed. Each variant serves different aspects of small UAS deployment, with low speed envisioned for high-endurance surveying, and high speed for long-range or time-critical missions such as delivery. The experimental and simulation results suggest room for design iteration, in wing area and geometry adjustments. Structural simulations demonstrated the need for airframe improvements to the low-speed configuration. This paper highlights the potential of reconfigurable UAVs to be useful across multiple industries, advocating for further research and design improvements.

42 ENGINEERING↗
DOE OSTI2024

Construction of Reconfigurable and Polymorphic DNA Origami Assemblies with Coiled‐Coil Patches and Patterns

Abstract DNA origami nanodevices achieve programmable structure and tunable mechanical and dynamic properties by leveraging the sequence‐specific interactions of nucleic acids. Previous advances have also established DNA origami as a useful building block to make well‐defined micron‐scale structures through hierarchical self‐assembly, but these efforts have largely leveraged the structural features of DNA origami. The tunable dynamic and mechanical properties also provide an opportunity to make assemblies with adaptive structures and properties. Here the integration of DNA origami hinge nanodevices and coiled‐coil peptides are reported into hybrid reconfigurable assemblies. With the same dynamic device and peptide interaction, it is made multiple higher‐order assemblies (i.e., polymorphic assembly) by organizing clusters of peptides into patches or arranging single peptides into patterns on the surfaces of DNA origami to control the relative orientation of devices. The coiled‐coil interactions are used to construct circular and linear assemblies whose structure and mechanical properties can be modulated with DNA‐based reconfiguration. Reconfiguration of linear assemblies leads to micron scale motions and ≈2.5‐10‐fold increase in bending stiffness. The results provide a foundation for stimulus‐responsive hybrid assemblies that can adapt their structure and properties in response to nucleic acid, peptide, protein, or other triggers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Non-Reciprocity, Metastability, and Dynamic Reconfiguration in Co-Assembly of Active and Passive Particles

Living organisms often exhibit non-reciprocal interactions where the forces acting on the objects are not equal in magnitude or opposite in direction. The combination of reciprocal and non-reciprocal interactions between synthetic building blocks remains largely unexplored. Here, out-of-equilibrium assemblies of non-motile isotropic passive and metal-patched motile active particles are formed by overlapping bulk interactions with directed self-propulsion. An external alternating current (AC) electric field generates concurrent dipolar and induced-charge electrophoretic forces between the particles which are evaluated using microscopy. The interaction force measurements allow to determine the degree of reciprocity in interactions, which is tunable by designing the active particle and its trajectory. While linearly-propelled active particles evade assembly with passive particles, helically propelled active particles form active-passive clusters with dynamic reconfiguration and long-lived metastability. Large clusters display programmable fluctuations and reconfigurability by controlling the fraction of active particles. The study establishes principles of integrating reciprocal and non-reciprocal interactions in guided colloidal assembly of reconfigurable metastable structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Reconfigurable self-assembly of porous anisotropic colloids in nematic liquid crystals

Dispersions of anisotropic nanoparticles in liquid crystalline hosts recently yielded new soft condensed matter states, like the thermally reconfigurable monoclinic and orthorhombic biaxial nematic liquid crystals, with a plethora of unusual phases and phase transformations. Our current study shows that the nanoscale porous nature of colloids with micrometer-range overall dimensions also enables highly reconfigurable orientations and assemblies of the microparticles, allowing for realization of condensed matter states with unusual combinations of low-symmetry nematic or smectic order and fluidity. Much like the anisotropic nanoparticles studied previously, these nanoporous anisotropic colloids exhibit thermally reconfigurable oriented alignment with respect to the far-field director, as well as diverse low-symmetry liquid crystalline phase behaviors. Furthermore, our findings open doors to fundamental and applied uses of low-symmetry molecular-colloidal orientationally ordered states of matter with uninhibited fluidity, as well as liquid crystals with partial positional ordering, like low-symmetry smectics, which could lead to applications in metamaterial designs, electro-optics, photonics, etc.

colloidal dispersion↗
DOE OSTI2020

Dynamics of reconfigurable artificial spin ice: Toward magnonic functional materials

Over the past few years, the study of magnetization dynamics in artificial spin ices has become a vibrant field of study. Artificial spin ices are ensembles of geometrically arranged, interacting magnetic nanoislands, which display frustration by design. These were initially created to mimic the behavior in rare earth pyrochlore materials and to study emergent behavior and frustration using two-dimensional magnetic measurement techniques. Recently, it has become clear that it is possible to create artificial spin ices, which can potentially be used as functional materials. In this perspective, we review the resonant behavior of spin ices in the GHz frequency range, focusing on their potential application as magnonic crystals. In magnonic crystals, spin waves are functionalized for logic applications by means of band structure engineering. While it has been established that artificial spin ices can possess rich mode spectra, the applicability of spin ices to create magnonic crystals hinges upon their reconfigurability. Consequently, we describe recent work aiming to develop techniques and create geometries allowing full reconfigurability of the spin ice magnetic state. We also discuss experimental, theoretical, and numerical methods for determining the spectral response of artificial spin ices and give an outlook on new directions for reconfigurable spin ices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mechanisms enabling reconfigurability and long-term retention in vanadium oxide electrochemical memory

Phase coexistence in nanoscale electrochemical random-access memory (ECRAM) has recently been demonstrated to enable both information storage and extraordinary reconfigurability. These proof-of-principle demonstrations have left the mechanistic details of such a process unresolved. Particularly, the mechanisms that stabilize the multiple phases, and the underlying processes behind sustained memory retention, remain unclear, and are necessary to design such devices. Here we report microscale ECRAM devices composed of V⁢O𝑥, which enables us to directly probe the active region in an operando fashion using optical techniques. Using Raman mapping, we show the phase coexistence driven by the electrochemical injection of O vacancies to be spatially uniform (i.e., with no filaments). The stability was observed to be unusually long, with 1% loss over 14 years in ambient conditions. First-principles calculations of the oxygen vacancy formation energies in V⁢O 𝑥 further support the thermodynamic coexistence of multiple V⁢O 𝑥 phases and clarify the origin of the observed long-term retention in the ECRAM devices. Further, we demonstrate single devices that can be voltage programmed to exhibit synaptic, neuronal, and reconfigurable logic gate functionalities. Furthermore, we not only uncover the phase coexistence mechanism that may help device design, but also demonstrate the circuit-level applications of reconfigurability.

Electrical conductivity↗
DOE OSTI2022

Reconfigurable perovskite nickelate electronics for artificial intelligence

Reconfigurable devices offer the ability to program electronic circuits on demand. Here, in this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in post-fabricated perovskite NdNiO 3 devices that can be simply reconfigured for a specific purpose by single-shot electric pulses. The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Reconfigurable Framework for Resilient Semantic Segmentation for Space Applications

Deep learning (DL) presents new opportunities for enabling spacecraft autonomy, onboard analysis, and intelligent applications for space missions. However, DL applications are computationally intensive and often infeasible to deploy on radiation-hardened (rad-hard) processors, which traditionally harness a fraction of the computational capability of their commercial-off-the-shelf counterparts. Commercial FPGAs and system-on-chips present numerous architectural advantages and provide the computation capabilities to enable onboard DL applications; however, these devices are highly susceptible to radiation-induced single-event effects (SEEs) that can degrade the dependability of DL applications. In this article, we propose Reconfigurable ConvNet (RECON), a reconfigurable acceleration framework for dependable, high-performance semantic segmentation for space applications. In RECON, we propose both selective and adaptive approaches to enable efficient SEE mitigation. In our selective approach, control-flow parts are selectively protected by triple-modular redundancy to minimize SEE-induced hangs, and in our adaptive approach, partial reconfiguration is used to adapt the mitigation of dataflow parts in response to a dynamic radiation environment. Combined, both approaches enable RECON to maximize system performability subject to mission availability constraints. We perform fault injection and neutron irradiation to observe the susceptibility of RECON and use dependability modeling to evaluate RECON in various orbital case studies to demonstrate a 1.5–3.0× performability improvement in both performance and energy efficiency compared to static approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

AURORA: Automated Refinement of Coarse-Grained Reconfigurable Accelerators

Coarse-grained reconfigurable arrays (CGRAs), loosely defined as arrays of functional units interconnected through a network-on-chip (NoC), provide higher flexibility than domain-specific ASIC accelerators while offering increased hardware efficiency with respect to fine-grained reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs). Un-fortunately, designing a CGRA for a specific application domain involves enormous software/hardware engineering effort (e.g., designing the CGRA, map operations onto the CGRA, etc) and requires the exploration on a large design space (e.g., applying appropriate loop transformation on each application, specializing the reconfigurable processing elements of the CGRA, refining the network topology, deciding the size of the data memory, etc). Int his paper, we propose AURORA – a software/hardware co-design framework to automatically synthesize optimal CGRA given a set of applications of interest

Tan, Cheng↗
DOE OSTI2023

Optimizing connectivity in reconfigurable networks

A method may include determining whether the topology of a network includes a direct path between a first endpoint and a second endpoint in the network. A direct path may be used to send a first type of traffic from the first endpoint to the second endpoint whereas any currently available path may be used to send a second type of traffic from the first endpoint to the second endpoint. If the topology of the network does not include a direct path, the first type of traffic may be buffered at the first endpoint until the topology of the network is reconfigured to include the direct path. The topology of the network may be reconfigured when at least one switch in the network reconfigures, for example, by switching from one interconnection to another interconnection pattern. Related systems and articles of manufacture are also provided.

Mellette, William↗
DOE OSTI2023

All‐Liquid Reconfigurable Electronics Using Jammed MXene Interfaces

Abstract Rigid, solid‐state components represent the current paradigm for electronic systems, but they lack post‐production reconfigurability and pose ever‐increasing challenges to efficient end‐of‐life recycling. Liquid electronics may overcome these limitations by offering flexible in‐the‐field redesign and separation at end‐of‐life via simple liquid phase chemistries. Up to now, preliminary work on liquid electronics has focused on liquid metal components, but these devices still require an encapsulating polymer and typically use alloys of rare elements like indium. Here, using the self‐assembly of jammed 2D titanium carbide (Ti 3 C 2 T x ) MXene nanoparticles at liquid–liquid interfaces, “all‐liquid” electrically conductive sheets, wires, and simple functional devices are described including electromechanical switches and photodetectors. These assemblies combine the high conductivity of MXene nanosheets with the controllable form and reconfigurability of structured liquids. Such configurations can have applications not only in electronics, but also in catalysis and microfluidics, especially in systems where the product and substrate have affinity for solvents of differing polarity.

36 MATERIALS SCIENCE↗