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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Charge density wave memory in a cuprate superconductor

Although CDW correlations are a ubiquitous feature of the superconducting cuprates, their disparate properties suggest a crucial role for pinning the CDW to the lattice. Here, we report coherent resonant X-ray speckle correlation analysis, which directly determines the reproducibility of CDW domain patterns in La 1.875 Ba 0.125 CuO 4 (LBCO 1/8) with thermal cycling. While CDW order is only observed below 54 K, where a structural phase transition creates inequivalent Cu-O bonds, we discover remarkably reproducible CDW domain memory upon repeated cycling to far higher temperatures. That memory is only lost on cycling to 240(3) K, which recovers the four-fold symmetry of the CuO 2 planes. We infer that the structural features that develop below 240 K determine the CDW pinning landscape below 54 K. This opens a view into the complex coupling between charge and lattice degrees of freedom in superconducting cuprates.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optofluidic memory and self-induced nonlinear optical phase change for reservoir computing in silicon photonics

Nanophotonics allows to employ light-matter interaction to induce nonlinear optical effects and realize non-conventional memory and computation capabilities, however to date, light-liquid interaction was not considered as a potential mechanism to achieve computation on a nanoscale. Here, we experimentally demonstrate self-induced phase change effect which relies on the coupling between geometric changes of thin liquid film to optical properties of photonic waveguide modes, and then employ it for neuromorphic computing. In our optofluidic silicon photonics system we utilize thermocapillary-based deformation of thin liquid film capable to induce nonlinear effect which is more than one order of magnitude higher compared to the more traditional heat-based thermo-optical effect, and allowing operation as a nonlinear actuator and memory element, both residing at the same compact spatial region. The resulting dynamics allows to implement Reservoir Computing at spatial region which is approximately five orders of magnitude smaller compared to state-of-the-art experimental liquid-based systems.

42 ENGINEERING↗
DOE OSTI2020

A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

Science & Technology - Other Topics↗
DOE OSTI2017

3D Printed Silicones with Shape Memory

Direct ink writing enables the layer-by-layer manufacture of ordered, porous structures whose mechanical behavior is driven by architecture and material properties. Here, we incorporate two different gas filled microsphere pore formers to evaluate the effect of shell stiffness and T g on compressive behavior and compression set in siloxane matrix printed structures. The lower T g microsphere structures exhibit substantial compression set when heated near and above T g , with full structural recovery upon reheating without constraint. By contrast, the higher T g microsphere structures exhibit reduced compression set with no recovery upon reheating. Aside from their role in tuning the mechanical behavior of direct ink write structures, polymer microspheres are good candidates for shape memory elastomers requiring structural complexity, with potential applications toward tandem shape memory polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An organic electrochemical transistor for multi-modal sensing, memory and processing

By integrating sensing, memory and processing functionalities, biological nervous systems are energy and area efficient. Emulating such capabilities in artificial systems is, however, challenging and is limited by the device heterogeneity of sensing and processing cores. Here we report an organic electrochemical transistor capable of sensing, memory and processing. The device has a vertical traverse architecture and a crystalline–amorphous channel that can be selectively doped by ions to enable two reconfigurable modes: a volatile receptor and a non-volatile synapse. As a volatile receptor, the device is capable of multi-modal sensing and is responsive to stimuli such as ions and light. As a non-volatile synapse, it is capable of 10-bit analogue states, low switching stochasticity and good state retention. We also show that the homogeneous integration of the devices could provide functions such as conditioned reflexes and could be used for real-time cardiac disease diagnoses via reservoir computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Inductance meets memory in a quantum magnet

Orbital degrees of freedom offer a largely untapped route to emergent dynamical phenomena in correlated quantum materials. However, it remains unclear whether collective orbital states can intrinsically generate both reactive and memory functionalities in a bulk system. Here we show that in the ferrimagnet Mn₃Si₂Te₆, nonequilibrium reconfiguration of chiral orbital currents produces both emergent inductance and nonvolatile memristance as intrinsic properties of a single crystal. At low frequency and under a magnetic field along the c axis, coherent orbital-current domains generate robust clockwise inductive I-V loops. At higher frequency and low field, current-driven first-order reconfiguration leads to incomplete reversal and metastable trapping, producing an intrinsic electromotive force and a finite remanent voltage at zero current. These results establish orbital currents as a class of quantum state variables that encode both reactive and memory functionalities, opening routes toward intrinsically reconfigurable and energy-efficient electronic systems.

Cao, Tristan [University of Colorado, Boulder]↗
DOE OSTI2024

Energy efficient photonic memory based on electrically programmable embedded III-V/Si memristors: switches and filters

Abstract Over the past few years, extensive work on optical neural networks has been investigated in hopes of achieving orders of magnitude improvement in energy efficiency and compute density via all-optical matrix-vector multiplication. However, these solutions are limited by a lack of high-speed power power-efficient phase tuners, on-chip non-volatile memory, and a proper material platform that can heterogeneously integrate all the necessary components needed onto a single chip. We address these issues by demonstrating embedded multi-layer HfO 2 /Al 2 O 3 memristors with III-V/Si photonics which facilitate non-volatile optical functionality for a variety of devices such as Mach-Zehnder Interferometers, and (de-)interleaver filters. The Mach-Zehnder optical memristor exhibits non-volatile optical phase shifts > π with ~33 dB signal extinction while consuming 0 electrical power consumption. We demonstrate 6 non-volatile states each capable of 4 Gbps modulation. (De-) interleaver filters were demonstrated to exhibit memristive non-volatile passband transformation with full set/reset states. Time duration tests were performed on all devices and indicated non-volatility up to 24 hours and beyond. We demonstrate non-volatile III-V/Si optical memristors with large electric-field driven phase shifts and reconfigurable filters with true 0 static power consumption. As a result, co-integrated photonic memristors offer a pathway for in-memory optical computing and large-scale non-volatile photonic circuits.

Cheung, Stanley (ORCID:0000000248860013)↗
DOE OSTI2020

Bonding similarities and differences between Y–Sb–Te and Sc–Sb–Te phase-change memory materials

The scandium (Sc) – alloyed Sb 2 Te 3 phase-change alloy has recently been found to enable ultrafast crystal nucleation due to the formation of Sc-stabilized octahedral motifs in the amorphous phase, rendering cache-type phase-change memory feasible. When yttrium (Y) is added, however, non-octahedral bonding patterns form in the amorphous Sb 2 Te 3 -based network even though Y has a valence electron configuration similar to that of Sc and also forms perfect octahedral bonding environments with tellurium in the YTe crystal. Here we elucidate the origin of this difference between Sc and Y, by carrying out thorough ab initio simulations and orbital-based bonding analyses on amorphous Y–Sb–Te and Sc–Sb–Te compounds. We also demonstrate how the smooth overlap of atomic positions (SOAP) similarity kernel can be used to quantify the structural similarity of local motifs in the amorphous phase with respect to various crystalline yttrium and scandium tellurides, both in the nearest-neighbor shell and beyond. We discover that the bonding contrast of Y- and Sc-centered structural motifs in amorphous Sb 2 Te 3 stems from their parent crystals at high Te concentrations. The larger atomic radius of Y and the weaker charge transfer when bonded with Te is found to allow more Te neighbors and cause a more open bonding environment, leading to higher coordination numbers and non-octahedral environments. We discuss the implications of the different local environments for practical applications in memory devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Sn 2 Se 3 : A conducting crystalline mixed valent phase change memory compound

Thin film Sn 2 Se 3 is a promising new phase change memory material with a very high resistance contrast between insulating amorphous and conducting crystalline phases. In this paper, we identify the structure of the Sn 2 Se 3 crystalline phase using ab initio evolutionary structure search and report its properties. We find a structure based on Sn-Se ribbons with clear disproportionation of Sn into Sn(II) and Sn(IV) sites, similar to Sn 2 S 3 . The energy is only 9 meV/atom above the tie line between SnSe and SnSe 2 . Sn charge disproportionation is only marginally favored in this selenide, in contrast to sulfides. This leads to a semimetallic rather than semiconducting behavior. Finally, these findings, marginal stability of the crystalline phase and conducting character and close competition of disproportionated and non-disproportionated structures, are important for understanding the behavior of Sn 2 Se 3 as a phase change memory material, specifically the fast low energy, the low temperature switching, and the high resistance contrast.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Giant negative thermal expansion in Fe-Mn-Ga magnetic shape memory alloys

Fe-Mn-Ga magnetic shape memory alloys can undergo martensitic transformation (MT) from a paramagnetic cubic phase to a ferromagnetic tetragonal phase. The MT is accompanied by a large volume change; yet, these alloys have never been explored for technological applications as negative thermal expansion (NTE) materials. Here, by careful chemical modification, tunable NTE characteristics including wide operating temperature windows (Delta T) and large negative linear coefficients of thermal expansion (alpha(l)) have been achieved in Fe 44-x Mn 28 Ga 28+x (x = 1, 2, and 2.5) alloys. Typically, a giant NTE Delta T of 81 K and alpha(l =) -50.2 x 10(-6) K-1 were realized in the Fe43Mn28Ga29 alloy upon cooling from 290 K. The relationships between the NTE features, the MT, and the substitution of Ga for Fe were discussed. Furthermore, the Fe-Mn-Ga alloys possess excellent mechanical properties, high electrical conductivity and high thermal conductivity. With these advantages, the Fe-Mn-Ga magnetic shape memory alloys show promising prospects for use as advanced NTE materials.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Understanding the switching mechanism of interfacial phase change memory

Phase Change Memory (PCM) is a top candidate for next generation data storage, but it typically suffers from high switching (RESET) current density (20–30 MA/cm 2 ). Interfacial Phase Change Memory (IPCM) is a type of PCM using multilayers of Sb 2 Te 3 /GeTe, with up to 100× lower reported RESET current compared to the standard Ge 2 Sb 2 Te 5 -based PCM. Several hypotheses involving fundamentally new switching mechanisms have been proposed to explain the low switching current densities, but consensus is lacking. Here, we investigate IPCM switching by analyzing its thermal, electrical, and fabrication dependencies. First, we measure the effective thermal conductivity (~0.4 W m -1 K -1 ) and thermal boundary resistance (~3.4 m 2 K GW -1 ) of Sb 2 Te 3 /GeTe multilayers. Simulations show that IPCM thermal properties account only for an ~13% reduction of current vs standard PCM and cannot explain previously reported results. Interestingly, electrical measurements reveal that our IPCM RESET indeed occurs by a melt-quench process, similar to PCM. Finally, we find that high deposition temperature causes defects including surface roughness and voids within the multilayer films. Thus, the substantial RESET current reduction of IPCM appears to be caused by voids within the multilayers, which migrate to the bottom electrode interface by thermophoresis, reducing the effective contact area. These results shed light on the IPCM switching mechanism, indicating that an improved control of layer deposition is necessary to obtain reliable switching.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Thermal-gradient-driven elemental segregation in Ge 2 Sb 2 Te 5 phase change memory cells

Thermal gradients have been predicted to play a large role in compositional segregation leading to failure in phase change memories. We have developed a methodology for isolating thermal-gradient driven segregation effects without interference from the electric field. In Ge 2 Sb 2 Te 5 functional layers, Sb and Te move along the temperature gradient, while Ge segregates in the opposite direction. The direction of segregation is consistent for devices that were repeatedly melted, as well as for devices that were never melted and remained in the polycrystalline state. Here, the results have implications for the reliability of phase change memories.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficient construction of generalized master equation memory kernels for multi-state systems from nonadiabatic quantum-classical dynamics

Techniques derived from the generalized quantum master equation (GQME) framework have provided the basis for elucidating energy and charge transfer in systems ranging from molecular solids to photosynthetic complexes. Recently, the nonperturbative combination of the GQME with quantum-classical methods has resulted in approaches whose accuracy and efficiency exceed those of the original quantumclassical schemes while offering significant accuracy improvements over perturbative expansions of the GQME. In this work, we show that, while the non-Markovian memory kernel required to propagate the GQME scales quartically with the number of subsystem states, the number of trajectories required scales at most quadratically when using quantum-classical methods to construct the kernel. We then present an algorithm that allows further acceleration of the quantum-classical GQME by offering a way to selectively sample the kernel matrix elements that are most important to the process of interest. We demonstrate the utility of these advances by applying the combination of Ehrenfest mean field theory with the GQME (MF-GQME) to models of the Fenna-Matthews-Olson (FMO) complex and the light harvesting complex II (LHCII), with 7 and 14 states, respectively. This allows us to show that the MF-GQME is able to accurately capture all the relevant dynamical time scales in LHCII: the initial nonequilibrium population transfer on the femtosecond time scale, the steady state-type trapping on the picosecond time scale, and the long time population relaxation. Remarkably, all of these physical effects spanning tens of picoseconds can be encoded in a memory kernel that decays only after ~65 fs.

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

Phase control of coherent acoustic phonons in gold bipyramids for optical memory and manipulating plasmon–exciton coupling

Recent efforts have targeted manipulation of nanomaterial vibrational modes in applications such as chemical/mass sensing, optical switching, and phonon-driven photochemistry. While impulsive photoexcitation can generate coherent phonons, multiple excitation pulses offer the prospect of control and manipulation of coherent phonon modes for functions of optical memory and logic. In this work, we use such an approach to inject an arbitrary coherent phonon phase into a colloidal ensemble of highly monodisperse gold bipyramids. We then demonstrate that this technique can be applied to a system that exhibits plasmon-exciton coupling to further manipulate the hybridization of the system. This ability to manipulate acoustic phonons and hybridization can enable optical logic applications of acoustic phonons in addition to optical memory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A nanocryotron memory and logic family

The development of superconducting electronics based on nanocryotrons has been limited so far to few device circuits, in part due to the lack of standard and robust logic cells. Here, we introduce and experimentally demonstrate designs for a set of nanocryotron-based building blocks that can be configured and combined to implement memory and logic functions. The devices were fabricated by patterning a single superconducting layer of niobium nitride and measured in liquid helium on a wide range of operating points. The tests show 10 - 4 bit error rates with above ± 20 % margins up to 50 MHz and the possibility of operating under the effect of an out-of-plane 36 mT magnetic field, with ± 30 % margins at 10 MHz. Additionally, we designed and measured an equivalent delay-flip-flop made of two memory cells to show the possibility of combining multiple building blocks to make larger circuits. These blocks may constitute a solid foundation for the development of nanocryotron logic circuits and finite-state machines with potential applications in the integrated processing and control of superconducting nanowire single-photon detectors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

A parallel, distributed memory implementation of the adaptive sampling configuration interaction method

The many-body simulation of quantum systems is an active field of research that involves several different methods targeting various computing platforms. Many methods commonly employed, particularly coupled cluster methods, have been adapted to leverage the latest advances in modern high-performance computing. Selected configuration interaction (sCI) methods have seen extensive usage and development in recent years. However, the development of sCI methods targeting massively parallel resources has been explored only in a few research works. Here, we present a parallel, distributed memory implementation of the adaptive sampling configuration interaction approach (ASCI) for sCI. In particular, we will address the key concerns pertaining to the parallelization of the determinant search and selection, Hamiltonian formation, and the variational eigenvalue calculation for the ASCI method. Load balancing in the search step is achieved through the application of memory-efficient determinant constraints originally developed for the ASCI-PT2 method. The presented benchmarks demonstrate near optimal speedup for ASCI calculations of Cr 2 (24e, 30o) with 10 6 , 10 7 , and 3 × 10 8 variational determinants on up to 16 384 CPUs. Importantly, to the best of the authors’ knowledge, this is the largest variational ASCI calculation to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum memory in the revival of silenced echo scheme in an optical resonator

The protocol of optical quantum memory in the revival of silenced photon echo (ROSE) scheme is experimentally implemented in a Tm{sup 3+} :Y{sub 3}Al{sub 5}O{sub 12} crystal (c = 0.1 at.%) placed in an impedance-matched optical Fabry–Perot resonator. The input signal recovery efficiency of ∼21 % is achieved for a light pulse with a storage time of 36 μs. The main sources of loss and their impact on the achieved quantum efficiency are discussed, as well as the advantages of the implemented scheme and the possibilities of the further improvement of the main parameters of quantum memory. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Characterizing Tradeoffs in Memory, Accuracy, and Speed for Chemistry Tabulation Techniques

Chemistry tabulation is a common approach in practical simulations of turbulent combustion at engineering scales. Linear interpolants have traditionally been used for accessing precomputed multidimensional tables but suffer from large memory requirements and discontinuous derivatives. Higher-degree interpolants address some of these restrictions but are similarly limited to relatively low-dimensional tabulation. Artificial neural networks (ANNs) can be used to overcome these limitations but cannot guarantee the same accuracy as interpolants and introduce challenges in reproducibility and reliable training. These challenges are enhanced as the physics complexity to be represented within the tabulation increases. Here, we assess the efficiency, accuracy, and memory requirements of Lagrange polynomials, tensor product B-splines, and ANNs as tabulation strategies. We analyze results in the context of nonadiabatic flamelet modeling where higher dimension counts are necessary. While ANNs do not require structuring of data, providing benefits for complex physics representation, interpolation approaches often rely on some structuring of the table. Interpolation using structured table inputs that are not directly related to the variables transported in a simulation can incur additional query costs. This is demonstrated in the present implementation of heat losses. We show that ANNs, despite being difficult to train and reproduce, can be advantageous for high-dimensional, unstructured datasets relevant to nonadiabatic flamelet models. Furthermore we demonstrate that Lagrange polynomials show significant speedup for similar accuracy compared to B-splines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗