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At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Medial packing and elastic asymmetry stabilize the double-gyroid in block copolymers

Triply-periodic networks are among the most complex and functionally valuable self-assembled morphologies, yet they form in nearly every class of biological and synthetic soft matter building blocks. In contrast to simpler assembly motifs – spheres, cylinders, layers – networks require molecules to occupy variable local environments, confounding attempts to understand their formation. Here, we examine the double-gyroid network phase by using a geometric formulation of the strong stretching theory of block copolymer melts, a prototypical soft self-assembly system. The theory establishes the direct link between molecular packing, assembly thermodynamics and the medial map, a generic measure of the geometric center of complex shapes. We show that “medial packing” is essential for stability of double-gyroid in strongly-segregated melts, reconciling a long-standing contradiction between infinite- and finite-segregation theories. Additionally, we find a previously unrecognized non-monotonic dependence of network stability on the relative entropic elastic stiffness of matrix-forming to tubular-network forming blocks. The composition window of stable double-gyroid widens for both large and small elastic asymmetry, contradicting intuitive notions that packing frustration is localized to the tubular domains. This study demonstrates the utility of optimized medial tessellations for understanding soft-molecular assembly and packing frustration via an approach that is readily generalizable far beyond gyroids in neat block copolymers.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Inferring assembly-curving trends of bacterial micro-compartment shell hexamers from crystal structure arrangements

Bacterial microcompartments (BMC) are complex macromolecular assemblies that participate in varied chemical processes in about one fourth of bacterial species. BMC-encapsulated enzymatic activities are segregated from other cell contents by means of semipermeable shells, justifying why BMC are viewed as prototype nano-reactors for biotechnological applications. Herein, we undertook a comparative study of bending propensities of BMC hexamers (BMC-H), the most abundant shell constituents. Published data show that some BMC-H, like β -carboxysomal CcmK, tend to assemble flat whereas other BMC-H often build curved objects. Inspection of available crystal structures presenting BMC-H in tiled arrangements permitted us to identify two major assembly modes with a striking connection with experimental trends. All-atom molecular dynamics (MD) supported that BMC-H bending is triggered robustly only from the arrangement adopted in crystals by BMC-H that experimentally form curved objects, leading to very similar arrangements to those found in structures of recomposed BMC shells. Simulations on triplets of planar-behaving hexamers, which were previously reconfigured to comply with such organization, confirmed that bending propensity is mostly defined by the precise lateral positioning of hexamers, rather than by BMC-H identity. Finally, an interfacial lysine was pinpointed as the most decisive residue in controlling PduA spontaneous curvature. Globally, results presented herein should contribute to improve our understanding of the variable mechanisms of biogenesis characterized for BMC, and of possible strategies to regulate BMC size and shape.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Building an International Flagship Neutrino Experiment

An international team of over 1,000 scientists and engineers from more than 30 countries is building the most advanced neutrino experiment in the world, which could change our understanding of the universe. Groundbreaking for this revolutionary endeavor—hosted by the U.S. Department of Energy’s Fermilab with contributions from across the U.S. and around the globe—took place in July of 2017. A large prototype detector successfully recorded data at the European research center CERN from 2018 to 2020.

Fermilab↗

DOE OSTI2020

Building an International Flagship Neutrino Experiment

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Large-scale 2D heterostructures from hydrogen-bonded organic frameworks and graphene with distinct Dirac and flat bands

The current strategies for building 2D organic-inorganic heterojunctions involve mostly wet-chemistry processes or exfoliation and transfer, leading to interface contaminations, poor crystallizing, or limited size. Here we show a bottom-up procedure to fabricate 2D large-scale heterostructure with clean interface and highly-crystalline sheets. As a prototypical example, a well-ordered hydrogen-bonded organic framework is self-assembled on the highly-oriented-pyrolytic-graphite substrate. The organic framework adopts a honeycomb lattice with faulted/unfaulted halves in a unit cell, resemble to molecular “graphene”. Interestingly, the topmost layer of substrate is self-lifted by organic framework via strong interlayer coupling, to form effectively a floating organic framework/graphene heterostructure. The individual layer of heterostructure inherits its intrinsic property, exhibiting distinct Dirac bands of graphene and narrow bands of organic framework. Our results demonstrate a promising approach to fabricate 2D organic-inorganic heterostructure with large-scale uniformity and highly-crystalline via the self-lifting effect, which is generally applicable to most of van der Waals materials.

36 MATERIALS SCIENCE↗

DOE OSTI2020

TensorFlow Quantum: A Software Framework for Quantum Machine Learning

We introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data. This framework offers high-level abstractions for the design and training of both discriminative and generative quantum models under TensorFlow and supports high-performance quantum circuit simulators. We provide an overview of the software architecture and building blocks through several examples and review the theory of hybrid quantum-classical neural networks. We illustrate TFQ functionalities via several basic applications including supervised learning for quantum classification, quantum control, simulating noisy quantum circuits, and quantum approximate optimization. Moreover, we demonstrate how one can apply TFQ to tackle advanced quantum learning tasks including meta-learning, layerwise learning, Hamiltonian learning, sampling thermal states, variational quantum eigensolvers, classification of quantum phase transitions, generative adversarial networks, and reinforcement learning. We hope this framework provides the necessary tools for the quantum computing and machine learning research communities to explore models of both natural and artificial quantum systems, and ultimately discover new quantum algorithms which could potentially yield a quantum advantage.

Broughton, Michael↗

DOE OSTI2023

Building a DFT+U machine learning interatomic potential for uranium dioxide

Despite uranium dioxide (UO 2 ) being a widely used nuclear fuel, fuel performance models rely extensively on empirical correlations of material behavior, leveraging the historical operating experience of UO 2 . Mechanistic models that consider an atomistic understanding of the processes governing fuel performance (such as fission gas release and creep) will enable a better description of fuel behavior under non-prototypical conditions such as in new reactor concepts or for modified UO 2 fuel compositions. To this end, molecular dynamics simulation is a powerful tool for rapidly predicting physical properties of proposed fuel candidates. However, the reliability of these simulations depends largely on the accuracy of the atomic forces. Traditionally, these forces are computed using either a classical force field (FF) or density functional theory (DFT). While DFT is relatively accurate, the computational cost is burdensome, especially for f-electron elements, such as actinides. By contrast, classical FFs are computationally efficient but are less accurate. For these reasons, we report a new accurate machine learning interatomic potential (MLIP) for UO 2 that provides high-fidelity reproduction of DFT forces at a similar low cost to classical FFs. We employ an active learning approach that autonomously augments the DFT training data set to iteratively refine the MLIP. To further improve the quality of our predictions, we utilize transfer learning to retrain our MLIP to higher-accuracy DFT+U data. We validate our MLIPs by comparing predicted physical properties (e.g., thermal expansion and elastic properties) with those from existing classical FFs and DFT/DFT+U calculations, as well as with experimental data when available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

X-ray induced Coulomb explosion imaging of transient excited-state structural rearrangements in CS2

Abstract Structural imaging of transient excited-state species is a key goal of molecular physics, promising to unveil rich information about the dynamics underpinning photochemical transformations. However, separating the electronic and nuclear contributions to the spectroscopic observables is challenging, and typically requires the application of high-level theory. Here, we employ site-selective ionisation via ultrashort soft X-ray pulses and time-resolved Coulomb explosion imaging to interrogate structural dynamics of the ultraviolet photochemistry of carbon disulfide. This prototypical system exhibits the complex motifs of polyatomic photochemistry, including strong non-adiabatic couplings, vibrational mode couplings, and intersystem crossing. Immediately following photoexcitation, we observe Coulomb explosion signatures of highly bent and stretched excited-state geometries involved in the photodissociation. Aided by a model to interpret such changes, we build a comprehensive picture of the photoinduced nuclear dynamics that follows initial bending and stretching motions, as the reaction proceeds towards photodissociation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Evolution of DUNE’s Production System

The DUNE experiment will start running in 2029 and record 30 PB/year of raw waveforms from Liquid Argon TPCs and photon detectors. The size of individual readouts can range from 100 MB to a typical 8 GB full readout of the detector, and even 100 TB for extended readouts from supernova candidates. These data then need to be cataloged, stored and distributed for processing worldwide. This massive amount of data and a heterogeneous computing environment necessitates a powerful and robust distributed computing infrastructure. In the process of building up that infrastructure, DUNE’s production system has recently undergone an overhaul, in which it has integrated 1) a new workflow management system (justIN) 2) a new data catalog (MetaCat) and 3) a state-of-the-art data management system (Rucio). Simulations of DUNE’s Far Detector and its prototypes ProtoDUNE Horizontal Drift (ProtoDUNE-HD) and ProtoDUNE Vertical Drift (ProtoDUNE-VD), as well as data from ProtoDUNE-HD serve as the first tests of this infrastructure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Open Radiation Monitoring: Histogram Builder Module Design

The Open Radiation Monitoring Project seeks to develop and demonstrate a modular radiation detection architecture designed specifically for use in arms control treaty verification (ACTV) applications that will facilitate rapid development of trusted systems to meet the needs of potential future treaties. A modular architecture can be used to reduce more complex systems to a series of single purpose building blocks, thereby facilitating equipment inspection and in turn building trust in the equipment by all treaty parties. Furthermore, a modular architecture can be used to control data flow within the measurement system, reducing the risk of "hidden switches" and constraining the amount of sensitive information that could potentially be inadvertently leaked. This report details the first revision of a prototype circuit that will convert analog pulses directly into a histogrammed data set for further processing. The circuit was designed with both spectroscopy and multiplicity analysis in mind but can, in principle, be used to reduce any raw data stream into a histogram. The number of output channels is limited, and the histogram bin ranges are user configurable to allow for non-uniform and discontinuous bins, which makes it possible to restrict the information being passed down stream if desired. Pulse processing relies entirely on analog circuitry and non- programmable logic, which enables operation without the need for a central processor or other programmable control unit. The circuit remains untested under the Open Radiation Monitoring project due to the closure of the sponsoring program. However, further development and testing is scheduled to take place in support of a purpose-built trusted verification system development effort known as COGNIZANT, which demonstrates the potential benefit of developing a suite of modular trusted system components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Report on the Second MPEX User Research Forum

The Material Plasma Exposure eXperiment (MPEX) User Research Forum (MURF), a 2 day workshop, was held virtually on September 13–14, 2021, to seek community input for MPEX, a new high-power linear plasma device that is currently being built at Oak Ridge National Laboratory (ORNL). This was the second MURF workshop. The first MURF workshop was held in October 2019 in La Jolla, California, and focused exclusively on the definition of the surface analysis station for MPEX. MPEX is designed to address crucial R&D gaps in plasma material interactions (PMI) for future fusion reactors. The MPEX plasma source and heating systems will allow plasma exposures of plasma-facing materials and components to prototype fusion reactor divertor plasma conditions. The MPEX design accommodates the introduction of previously neutron-irradiated materials for fusion reactor-relevant plasma exposures. This capability will be unique worldwide. The US fusion program has advocated for such a device in numerous community reports in recent years, and now ORNL is building this new device. MPEX is a Major Item of Equipment project executed by the US Department of Energy’s Office of Science Fusion Energy Sciences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Building an International Flagship Neutrino Experiment

An international team of over 1,000 scientists and engineers from more than 30 countries is building the most advanced neutrino experiment in the world, which could change our understanding of the universe. Groundbreaking for this revolutionary endeavor—hosted by the U.S. Department of Energy’s Fermilab with contributions from across the U.S. and around the globe—took place in July of 2017. The first of two large prototype detectors started recording data in Sept. 2018.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Investigation of a Multi-Rotor Triboelectric Nanogenerator Using a Modular Flexible Circuit Board Stack

Triboelectric nanogenerators (TENGs) are a nascent class of energy harvester that are being explored for scavenging energy from small ocean waves. To date, they have been integrated in wave energy converters (WECs) designed to capture random motion caused by the perturbations of the ocean surface. Blue economy applications such as ocean observation can benefit greatly from more substantial wave-derived power, as such, the power output of existing TENG WECs must be increased several-fold to become viable. This study describes the conceptualization of a rotary TENG, and the subsequent efforts to increase its power output by stacking multiple stator and rotor pairs. In the latter part of this study, we introduce a novel means of incorporating a friction element into the design of the TENG by employing flexible printed circuit board (PCB) rotors. At rest, these flexible rotors will contact the stator, building static charges due to friction, at speed, these flexible rotors will be decoupled from the stator, reducing friction and allowing faster rotation. Initial results indicate that the power output of the flexible PCB rotor does not produce more power than a rigid, acrylic disk rotor, however the current output of the prototype is boosted, and the prototype is far more compact, allowing for a higher energy density than the rigid rotor prototype.

bench testing↗

DOE OSTI2025

Efficient Floating-Point Arithmetic on Fault-Tolerant Quantum Computers

We propose a novel floating-point encoding scheme that builds on prior work involving fixed-point encodings. We encode floating-point numbers using Two's Complement fixed-point mantissas and Two's Complement integral exponents. We used our proposed approach to develop quantum algorithms for fundamental arithmetic operations, such as bit-shifting, reciprocation, multiplication, and addition. We prototyped and investigated the performance of the floating-point encoding scheme on quantum computer simulations by performing reciprocation on randomly drawn inputs and by solving first-order ordinary differential equations, while varying the number of qubits in the encoding. We observed rapid convergence to the exact solutions as we increased the number of qubits and a significant reduction in the number of ancilla qubits required for reciprocation when compared with similar approaches.

Serrallés, José Cruz [Weill Cornell Med. Coll.]↗

DOE OSTI2022

Atomically Resolved Electrically Active Intragrain Interfaces in Perovskite Semiconductors

Deciphering the atomic and electronic structures of interfaces is key to developing state-of-the-art perovskite semiconductors. However, conventional characterization techniques have limited previous studies mainly to grain-boundary interfaces, whereas the intragrain-interface microstructures and their electronic properties have been much less revealed. Herein using scanning transmission electron microscopy, we resolved the atomic-scale structural information on three prototypical intragrain interfaces, unraveling intriguing features clearly different from those from previous observations based on standalone films or nanomaterial samples. These intragrain interfaces include composition boundaries formed by heterogeneous ion distribution, stacking faults resulted from wrongly stacked crystal planes, and symmetrical twinning boundaries. The atomic-scale imaging of these intragrain interfaces enables us to build unequivocal models for the ab initio calculation of electronic properties. Our results suggest that these structure interfaces are generally electronically benign, whereas their dynamic interaction with point defects can still evoke detrimental effects. This work paves the way toward a more complete fundamental understanding of the microscopic structure-property-performance relationship in metal halide perovskites.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Optimizing Charge-coupled Device Readout Enabled by the Floating-gate Amplifier

Multiple-Amplifier Sensing (MAS) charge-coupled devices (CCDs) have recently been shown to be promising silicon detectors that meet noise sensitivity requirements for next generation Stage-5 spectroscopic surveys and potentially, future space-based imaging of extremely faint objects on missions such as the Habitable Worlds Observatory. Building upon the capability of the Skipper CCD to achieve deeply sub-electron noise floors, MAS CCDs utilize multiple floating-gate amplifiers along the serial register to increase the readout speed by a factor of the number of output nodes compared to a Skipper CCD. We introduce and experimentally demonstrate on a 16-channel prototype device new readout techniques that exploit the MAS CCD’s floating-gate amplifiers to optimize the correlated double sampling by resetting once per line instead of once per pixel. With this new mode, we find an optimal filter to subtract the noise from the signal during read out. We also take advantage of the MAS CCD’s structure to tune the read time by independently changing integration times for the signal and reference level. Together with optimal weighted averaging of the 16 outputs, these approaches enable us to reach a sub-electron noise of 0.9 e − rms pix −1 at 19 μs pix −1 for a single charge measurement per pixel—simultaneously giving a 30% faster readout time and 10% lower read noise compared to performance previously evaluated without these techniques.

Lin, Kenneth W. (ORCID:0000000189672281)↗

DOE OSTI2025

Opportunities for gas-phase science at short-wavelength free-electron lasers with undulator-based polarization control

Free-electron lasers (FELs) are the world's most brilliant light sources with rapidly evolving technological capabilities in terms of ultrabright and ultrashort pulses over a large range of photon energies. Their revolutionary and innovative developments have opened new fields of science regarding nonlinear light-matter interaction, the investigation of ultrafast processes from specific observer sites, and approaches to imaging matter with atomic resolution. A core aspect of FEL science is the study of isolated and prototypical systems in the gas phase with the possibility of addressing well-defined electronic transitions or particular atomic sites in molecules. Notably for polarization-controlled short-wavelength FELs, the gas phase offers new avenues for investigations of nonlinear and ultrafast phenomena in spin-orientated systems, for decoding the function of the chiral building blocks of life as well as steering reactions and particle emission dynamics in otherwise inaccessible ways. This roadmap comprises descriptions of technological capabilities of facilities worldwide, innovative diagnostics and instrumentation, as well as recent scientific highlights, novel methodology, and mathematical modeling. The experimental and theoretical landscape of using polarization controllable FELs for dichroic light-matter interaction in the gas phase will be discussed and comprehensively outlined to stimulate and strengthen global collaborative efforts of all disciplines. Published by the American Physical Society 2025

Ilchen, Markus↗