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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Real-time quantum error correction beyond break-even

The ambition of harnessing the quantum for computation is at odds with the fundamental phenomenon of decoherence. The purpose of quantum error correction (QEC) is to counteract the natural tendency of a complex system to decohere. This cooperative process, which requires participation of multiple quantum and classical components, creates a special type of dissipation that removes the entropy caused by the errors faster than the rate at which these errors corrupt the stored quantum information. Previous experimental attempts to engineer such a process faced an excessive generation of errors that overwhelmed the error-correcting capability of the process itself. Whether it is practically possible to utilize QEC for extending quantum coherence thus remains an open question. We answer it by demonstrating a fully stabilized and error-corrected logical qubit whose quantum coherence is significantly longer than that of all the imperfect quantum components involved in the QEC process, beating the best of them with a coherence gain of G=2.27±0.07. Here we achieve this performance by combining innovations in several domains including the fabrication of superconducting quantum circuits and model-free reinforcement learning.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

In vivo mapping of mutagenesis sensitivity of human enhancers

Distant-acting enhancers are central to human development1. However, our limited understanding of their functional sequence features prevents the interpretation of enhancer mutations in disease2. Here we determined the functional sensitivity to mutagenesis of human developmental enhancers in vivo. Focusing on seven enhancers that are active in the developing brain, heart, limb and face, we created over 1,700 transgenic mice for over 260 mutagenized enhancer alleles. Systematic mutation of 12-base-pair blocks collectively altered each sequence feature in each enhancer at least once. We show that 69% of all blocks are required for normal in vivo activity, with mutations more commonly resulting in loss (60%) than in gain (9%) of function. Using predictive modelling, we annotated critical nucleotides at the base-pair resolution. The vast majority of motifs predicted by these machine learning models (88%) coincided with changes in in vivo function, and the models showed considerable sensitivity, identifying 59% of all functional blocks. Taken together, our results reveal that human enhancers contain a high density of sequence features that are required for their normal in vivo function and provide a rich resource for further exploration of human enhancer logic.

Kosicki, Michael↗
DOE OSTI2026

Multiomics and deep learning dissect regulatory syntax in human development

Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression1. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities2. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify ‘hard’ syntactic rules requiring precise motif spacing and orientation, ‘soft’ rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation during human development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Origin of Rashba Spin-Orbit Coupling in 2D and 3D Lead Iodide Perovskites

isaWhittaker-Brooks2 & Tho D. Nguyen1* We studied spin dynamics of charge carriers in the superlattice-like Ruddlesden-Popper hybrid lead iodide perovskite semiconductors, 2D (BA)2(MA)Pb2I7 (with MA= CH3NH3, and BA= CH3(CH2)3NH3), and 3D MAPbI3 using the magnetic field effect (MFE) on conductivity and electroluminescence in their light emitting diodes (LEDs) at cryogenic temperatures. The semiconductors with distinct structural/ bulk inversion symmetry breaking, when combined with colossal intrinsic spin–orbit coupling (SOC), theoretically give rise to giant Rashba-type SOC. We found that the magneto-conductance (MC) magnitude increases monotonically with the emission intensity and saturates at ≈0.05% and 0.11% for the MAPbI3 and (BA)2(MA)Pb2I7, respectively. The magneto-electroluminescence (MEL) response with similar line shapes as the MC response has a significantly larger magnitude, and essentially stays constant at ≈0.22% and ≈0.20% for MAPbI3 and (BA)2(MA)Pb2I7, respectively. The sign and magnitude of the MC and MEL responses can be quantitatively explained in the framework of the Δg-based excitonic model using rate equations. Remarkably, the width of the MEL response in those materials linearly increases with increasing the applied electric field, where the Rashba coefficient in (BA)2(MA) Pb2I7 is estimated to be about 7 times larger than that in MAPbI3. Our studies might have significant impact on future development of electrically-controlled spin logic devices via Rashba-like effects

36 MATERIALS SCIENCE↗
DOE OSTI2020

A regression algorithm for accelerated lattice QCD that exploits sparse inference on the D-Wave quantum annealer

We propose a regression algorithm that utilizes a learned dictionary optimized for sparse inference on a D-Wave quantum annealer. In this regression algorithm, we concatenate the independent and dependent variables as a combined vector, and encode the high-order correlations between them into a dictionary optimized for sparse reconstruction. On a test dataset, the dependent variable is initialized to its average value and then a sparse reconstruction of the combined vector is obtained in which the dependent variable is typically shifted closer to its true value, as in a standard inpainting or denoising task. Here, a quantum annealer, which can presumably exploit a fully entangled initial state to better explore the complex energy landscape, is used to solve the highly non-convex sparse coding optimization problem. The regression algorithm is demonstrated for a lattice quantum chromodynamics simulation data using a D-Wave 2000Q quantum annealer and good prediction performance is achieved. The regression test is performed using six different values for the number of fully connected logical qubits, between 20 and 64. The scaling results indicate that a larger number of qubits gives better prediction accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Magnetic flux imaging in a 3D superconductor integrated circuit

We report on imaging magnetic flux distributions in a multilayered superconductor integrated circuit which emerge during magnetization and after field cooling of the circuit in the DC magnetic field. The obtained complicated field maps expose the flux propagation across the patterned superconducting ground planes sandwiching layers with Josephson junction-based logic cells, fine wire grid around the functional units, and multiple superconducting fill structures located in different inner layers. The observed intricate flux distributions are explained by specific patterns of Meissner screening currents and superconducting critical currents in different mutually interacting parts of the integrated circuit. Our results provide important insights into possible ways of improving the protection of superconductor integrated circuits from magnetic fields and their resilience against flux trapping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Domain wall enabled steep slope switching in MoS2 transistors towards hysteresis-free operation

Abstract The device concept of ferroelectric-based negative capacitance (NC) transistors offers a promising route for achieving energy-efficient logic applications that can outperform the conventional semiconductor technology, while viable operation mechanisms remain a central topic of debate. In this work, we report steep slope switching in MoS 2 transistors back-gated by single-layer polycrystalline PbZr 0.35 Ti 0.65 O 3 . The devices exhibit current switching ratios up to 8 × 10 6 within an ultra-low gate voltage window of $$V_{{{\mathrm{g}}}} = \pm \! 0.5$$ V g = ± 0.5 V and subthreshold swing (SS) as low as 9.7 mV decade −1 at room temperature, transcending the 60 mV decade −1 Boltzmann limit without involving additional dielectric layers. Theoretical modeling reveals the dominant role of the metastable polar states within domain walls in enabling the NC mode, which is corroborated by the relation between SS and domain wall density. Our findings shed light on a hysteresis-free mechanism for NC operation, providing a simple yet effective material strategy for developing low-power 2D nanoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A scalable superconducting nanowire memory array with row–column addressing

Scalable superconducting memory is required for the development of low-energy superconducting computers and fault-tolerant quantum computers. Conventional superconducting logic-based memory cells possess a large footprint that limits scaling; nanowire-based superconducting memory cells, although more compact, have high error rates, which hinders integration into large arrays. Here we report a 4 × 4 superconducting nanowire memory array that is designed for scalable row–column operations and has a functional density of 2.6 Mbit cm −2 . Each memory cell is based on a nanowire loop consisting of two temperature-dependent superconducting switches and a variable kinetic inductor. The arrays operate at 1.3 K, where we implement and characterize multiflux quanta state storage and destructive read-out. By optimizing the write- and read-pulse sequences, we minimize bit errors and maximize operating margins. We achieve a minimum bit error rate of 10 −5 . Here, we also use circuit-level simulations to understand the memory cell’s dynamics, performance limits and stability under varying pulse amplitudes.

Electrical and electronic engineering↗
DOE OSTI2022

Interpretable machine learning for knowledge generation in heterogeneous catalysis

Most applications of machine learning in heterogeneous catalysis thus far have used black-box models to predict computable physical properties (descriptors), such as adsorption or formation energies, that can be related to catalytic performance (that is, activity or stability). Here, extracting meaningful physical insights from these black-box models has proved challenging, as the internal logic of these black-box models is not readily interpretable due to their high degree of complexity. Interpretable machine learning methods that merge the predictive capacity of black-box models with the physical interpretability of physics-based models offer an alternative to black-box models. In this Perspective, we discuss the various interpretable machine learning methods available to catalysis researchers, highlight the potential of interpretable machine learning to accelerate hypothesis formation and knowledge generation, and outline critical challenges and opportunities for interpretable machine learning in heterogeneous catalysis.

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

In-plane selective area InSb–Al nanowire quantum networks

Abstract Strong spin–orbit semiconductor nanowires coupled to a superconductor are predicted to host Majorana zero modes. Exchange (braiding) operations of Majorana modes form the logical gates of a topological quantum computer and require a network of nanowires. Here, we utilize an in-plane selective area growth technique for InSb–Al semiconductor–superconductor nanowire networks. Transport channels, free from extended defects, in InSb nanowire networks are realized on insulating, but heavily mismatched InP (111)B substrates by full relaxation of the lattice mismatch at the nanowire/substrate interface and nucleation of a complete network from a single nucleation site by optimizing the surface diffusion length of the adatoms. Essential quantum transport phenomena for topological quantum computing are demonstrated in these structures including phase-coherence lengths exceeding several micrometers with Aharonov–Bohm oscillations up to five harmonics and a hard superconducting gap accompanied by 2 e -periodic Coulomb oscillations with an Al-based Cooper pair island integrated in the nanowire network.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Inducing a tunable skyrmion-antiskyrmion system through ion beam modification of FeGe films

Abstract Skyrmions and antiskyrmions are nanoscale swirling textures of magnetic moments formed by chiral interactions between atomic spins in magnetic noncentrosymmetric materials and multilayer films with broken inversion symmetry. These quasiparticles are of interest for use as information carriers in next-generation, low-energy spintronic applications. To develop skyrmion-based memory and logic, we must understand skyrmion-defect interactions with two main goals—determining how skyrmions navigate intrinsic material defects and determining how to engineer disorder for optimal device operation. Here, we introduce a tunable means of creating a skyrmion-antiskyrmion system by engineering the disorder landscape in FeGe using ion irradiation. Specifically, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au 4+ ions at varying fluences, inducing amorphous regions within the crystalline matrix. Using low-temperature electrical transport and magnetization measurements, we observe a strong topological Hall effect with a double-peak feature that serves as a signature of skyrmions and antiskyrmions. These results are a step towards the development of information storage devices that use skyrmions and antiskyrmions as storage bits, and our system may serve as a testbed for theoretically predicted phenomena in skyrmion-antiskyrmion crystals.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Electrochemical and spectroelectrochemical characterization of bacteria and bacterial systems

Microbes, such as bacteria, can be described, at one level, as small, self-sustaining chemical factories. Based on the species, strain, and even the environment, bacteria can be useful, neutral or pathogenic to human life, so it is increasingly important that we be able to characterize them at the molecular level with chemical specificity and spatial and temporal resolution in order to understand their behavior. Bacterial metabolism involves a large number of internal and external electron transfer processes, so it is logical that electrochemical techniques have been employed to investigate these bacterial metabolites. In this mini-review, we focus on electrochemical and spectroelectrochemical methods that have been developed and used specifically to chemically characterize bacteria and their behavior. First, we discuss the latest mechanistic insights and current understanding of microbial electron transfer, including both direct and mediated electron transfer. Second, we summarize progress on approaches to spatiotemporal characterization of secreted factors, including both metabolites and signaling molecules, which can be used to discern how natural or external factors can alter metabolic states of bacterial cells and change either their individual or collective behavior. Finally, we address in situ methods of single-cell characterization, which can uncover how heterogeneity in cell behavior is reflected in the behavior and properties of collections of bacteria, e.g. bacterial communities. Recent advances in (spectro)electrochemical characterization of bacteria have yielded important new insights both at the ensemble and the single-entity levels, which are furthering our understanding of bacterial behavior. Furthermore, these insights, in turn, promise to benefit applications ranging from biosensors to the use of bacteria in bacteria-based bioenergy generation and storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Challenges in synthesis of heterostructures

Developing the ability to reproducibly prepare materials drives the advancement of human technology. Trends in historical advances and extrapolation of current technologies suggest that the next logical step is developing the ability to control structure and composition at near atomic scales in device manufacturing to take advantage of emergent properties discovered in 2D materials and heterostructures. This article reviews a subset of synthetic approaches used to prepare heterostructures, outlining key reaction steps, and how experimental parameters are used to control which product forms. The positive attributes of each synthesis approach are discussed along with some of their limitations. The elemental reactant (MER) approach is discussed in more depth.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Integrating magnetic Co-nanopillars in a NbN-based VAN thin film as a multifunctional hybrid metamaterial

NbN thin films are considered as a promising alternative candidate to conventional Al superconducting electrodes for Josephson junction devices, superconducting qubits and quantum logic circuits. Herein, by co-growing ferromagnetic Co with superconducting NbN, self-assembled NbN–Co vertically aligned nanocomposite (VAN) thin films have been successfully deposited on a MgO substrates, with NbN in its cubic superconducting phase. The obtained VAN metamaterials exhibit epitaxial growth of NbN with uniformly dispersed Co nanoplates. Further physical property characterization reveals that the NbN–Co VAN presents ferromagnet properties with strong out-of-plane magnetic anisotropy and optical anisotropy. This hybrid metamaterial system could find future applications in superconducting spintronic devices and quantum computing devices.

Zhang, Yizhi [Purdue Univ., West Lafayette, IN (Un↗
DOE OSTI2024

Imaging of voltage-controlled switching of magnetization in highly magnetostrictive epitaxial Fe–Ga microstructures

The magnetoelectric behavior of epitaxial Fe–Ga microstructures on top of a (001)-oriented PMN–PT piezoelectric substrate is imaged with magnetic X-ray microscopy. Additionally, the micron-scale strain distribution in PMN–PT is characterized by X-ray microdiffraction and examined with respect to the results of the Fe–Ga magnetoelectric switching. The magnetic reorientation of Fe–Ga is found to be strongly correlated with size, shape, and crystallographic orientation of the microstructures. In the case of square-shaped structures, size dictates the influence of the strain distribution on both the initialization of the ground state and on the magnetic reorientation during application of voltage. On the other hand, elliptical microstructures demonstrate completely different magnetic responses depending on the relative orientation of their long axis with respect to the crystallographic directions of the PMN–PT. This study demonstrates that engineering the behavior of highly magnetostrictive epitaxial microdevices is possible. It further elucidates that voltage-induced actuation can be largely tuned to achieve the desired type of magnetic switching ranging from vortex circulation reversal, domain wall motion, to a large rotation of magnetization. Because of the outstanding properties of the investigated material system, the reported findings are expected to be of great interest for the realization of next-generation energy-efficient magnetic memory and logic devices.

42 ENGINEERING↗
DOE OSTI2024

Recent advancements in chiral spintronics: from molecular-level insights to device applications. A prospect based on the interplay between physical and chemical properties of chiral systems

This review discusses recent advancements in chiral-based spin-electronic devices achieved using suitable combinations of organic, inorganic and hybrid materials. The focus is on how chirality can be effectively used to control spin in practical applications, particularly in spintronic sensors and consumer devices. Interestingly, the underlying mechanism for this control is the chiral-induced spin selectivity (CISS) effect, which links the structural chirality of a material to its spin-selective electronic transport properties. The CISS effect arises from the observation that charge transmission in chiral systems is spin selective. Experimental evidence suggests a relationship between electron spin and the structural handedness of the material. In conclusion, this unique structure-transport relationship can be exploited to design a wide range of spintronics devices, including memory, transistors, logic gates and molecular q-bits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗