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At least 973 records · Page 54

Phase estimation algorithm for the multibeam optical metrology

Unitary Fourier transform lies at the core of the multitudinous computational and metrological algorithms. Here we show experimentally how the unitary Fourier transform-based phase estimation protocol, used namely in quantum metrology, can be translated into the classical linear optical framework. The developed setup made of beam splitters, mirrors and phase shifters demonstrates how the classical coherence, similarly to the quantum coherence, poses a resource for obtaining information about the measurable physical quantities. Our study opens route to the reliable implementation of the small-scale unitary algorithms on path-encoded qudits, thus establishing an easily accessible platform for unitary computation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Measurement of isosteric heat of gas adsorption and Brunauer–Emmett–Teller (BET) surface area using a quartz crystal microbalance

The study of gas adsorption on a solid surface evaluates the affinity between sorbate gas and sorbent substrate and factors that contribute to this. This report presents a test platform for adsorption experiments of various gases on various solid surfaces. Controlled environmental conditions enable investigations in materials surface science and increase the consistency among adsorption data. The system utilizes a quartz crystal microbalance to perform gravimetric analysis of deposition and adsorption, enabling investigation of the interaction of gaseous molecules with solid surfaces. In this study, a quartz crystal microbalance as gas adsorption detector was integrated with an environmental chamber to create a versatile tool for gas adsorption experiments on thin films. Experimental operation of this apparatus was demonstrated via acquisition of the adsorption isotherms of cyclohexane vapor on a gold surface at 55 and 70 °C. The result indicated International Union of Pure and Applied Chemistry Type II adsorption. Consequentially, application of the Brunauer–Emmett–Teller model to the isotherm data subject to predefined criteria for linear region selection yielded a surface area of the sorbent of 0.53 cm2 at 55 °C. From the monolayer region of the isotherms, the isosteric heat of adsorption of the cyclohexane vapor on gold was calculated to be 37 kJ mol-1.

47 OTHER INSTRUMENTATION↗

Same-sided successive-shock HED instability experiments

Inertial confinement fusion (ICF) and high-energy density (HED) physics experiments experience complicated forcing for instability growth and mix due to the ubiquitous presence of multiple shocks interacting with perturbations on multiple material interfaces. One common driver of instability growth is successive shocks from the same direction. However, there is a severe lack of analytic work and modeling validation for same-sided successive shocks since they are extremely difficult to achieve with conventional (non-HED) drivers. Successive shocks access a large instability parameter space; idealized fluid theory [K. O. Mikaelian, Phys. Rev. A 31, 410 (1985)] predicts 15 different interface evolution scenarios for a sinusoidal perturbation. Growth becomes more complex for multi-mode, compressible HED systems. The Mshock campaign is the first experiment in any fluid regime to probe a wide portion of successive shock parameter space. This is enabled by our development of a hybrid direct/indirect drive platform capable of creating independently controllable successive shocks on the National Ignition Facility. These experiments have delivered the first data capable of rigorously challenging our models and their ability to accurately capture Richtmyer–Meshkov growth under successive shocks. Single-mode and two-mode experiments have successfully demonstrated the ability to access and control the various growth scenarios of the shocked interface, including re-inversion, freeze out, and continued growth. Simulations and theoretical modeling are shown to accurately capture the experimental observations in the linear growth phase, giving us confidence in our ICF/HED design codes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum phases of Rydberg atoms on a kagome lattice

Significance Programmable quantum simulators based on Rydberg atom arrays have recently emerged as versatile platforms for exploring exotic many-body phases and quantum dynamics of strongly correlated systems. In this work, we theoretically investigate the quantum phases that can be realized by arranging such Rydberg atoms on a kagome lattice. Along with an extensive analysis of the states which break lattice symmetries due to classical correlations, we identify an intriguing regime that constitutes a promising candidate for hosting a phase with long-range quantum entanglement and topological order. Our results provide a route to experimentally realizing and probing highly entangled quantum matter.

74 ATOMIC AND MOLECULAR PHYSICS↗

Physics of Ultra-High Energy Density Relativistic Plasmas from Ordered Nanostructures

This award funded a four-year program at Colorado State University on the physics of ultra-high energy density plasmas generated by focusing femtosecond, >1021 Wcm-2 laser pulses onto ordered nanowire arrays. We used the ALEPH petawatt-class Ti:Sa laser with its high contrast 400 nm second harmonic beamline to irradiate arrays of Ni and TiO2 nanowires made by template assisted electrodeposition and atomic layer deposition over a wide range of average densities. We met two of the three original project goals: radial ion acceleration via doppler shifted K shell emission, and time and spectrally resolved K shell measurements. The main experimental advance was integrating the Lawrence Livermore National Laboratory (LLNL) TREX ultrafast x-ray streak camera with a suite of spherically bent quartz Bragg crystal spectrometers built using Princeton Plasma Physics Laboratory (PPPL) methodology. This is the first TREX-on-bent-quartz setup fielded at a femtosecond, >1021 Wcm-2 facility. It is now a permanent diagnostic at ALEPH and is offered to the LaserNetUS user community. The program produced three peer reviewed journal articles that acknowledge this award. The platform will continue at the upgraded CSU ATLAS facility, where the ALEPH laser is being upgraded to 2 PW.

Hollinger, Reed [Colorado State University]↗

Bayesian tensorized neural networks with automatic rank selection

Tensor decomposition is an effective approach to compress over-parameterized neural networks and to enable their deployment on resource-constrained hardware platforms. However, directly applying tensor compression in the training process is a challenging task due to the difficulty of choosing a proper tensor rank. In order to address this challenge, this paper proposes a low-rank Bayesian tensorized neural network. Our Bayesian method performs automatic model compression via an adaptive tensor rank determination. We also present approaches for posterior density calculation and maximum a posteriori (MAP) estimation for the end-to-end training of our tensorized neural network. Here, we provide experimental validation on a two-layer fully connected neural network, a 6-layer CNN and a 110-layer residual neural network where our work produces 7.4x to 137x more compact neural networks directly from the training while achieving high prediction accuracy.

Low-rank tensor↗

An automatically curated first-principles database of ferroelectrics

Ferroelectric materials have technological applications in information storage and electronic devices. The ferroelectric polar phase can be controlled with external fields, chemical substitution and size-effects in bulk and ultrathin film form, providing a platform for future technologies and for exploratory research. In this work, we integrate spin-polarized density functional theory (DFT) calculations, crystal structure databases, symmetry tools, workflow software, and a custom analysis toolkit to build a library of known, previously-proposed, and newly-proposed ferroelectric materials. With our automated workflow, we screen over 67,000 candidate materials from the Materials Project database to generate a dataset of 255 ferroelectric candidates, and propose 126 new ferroelectric materials. We benchmark our results against experimental data and previous first-principles results. The data provided includes atomic structures, output files, and DFT values of band gaps, energies, and the spontaneous polarization for each ferroelectric candidate. Finally, we contribute our workflow and analysis code to the open-source python packages atomate and pymatgen so others can conduct analogous symmetry driven searches for ferroelectrics and related phenomena.

36 MATERIALS SCIENCE↗

Sub-keV design for the National Ignition Facility’s soft x-ray Opacity Spectrometer (OpSpec) and expansion plans for time-resolved measurements

When compared with the National Ignition Facility’s (NIF) original soft x-ray opacity spectrometer, which used a convex cylindrical design, an elliptically shaped design has helped to increase the signal-to-noise ratio and eliminated nearly all reflections from alternate crystal planes. The success of the elliptical geometry in the opacity experiments has driven a new elliptical geometry crystal with a spectral range covering 520–1100 eV. When coupled with the primary elliptical geometry, which spans 1000–2100 eV, the new sub-keV elliptical geometry helps to cover the full iron L-shell and major oxygen transitions important to solar opacity experimentation. The new design has been built and tested by using a Henke x-ray source and shows the desired spectral coverage. Additional plans are underway to expand these opacity measurements into a mode of time-resolved detection, ~1 ns gated, but considerations for the detector size and photometrics mean a crystal geometry redesign. Here, the new low-energy geometry, including preliminary results from the NIF opacity experiments, is presented along with the expansion plans into a time-resolved platform.

47 OTHER INSTRUMENTATION↗

Robust multiresonant nonlocal metasurfaces by rational design

Abstract Dielectric metasurfaces supporting optical resonances have become a promising platform for quantum and nonlinear optics. However, resonant metasurfaces remain limited in their capacity to independently control the behavior of many distinct resonances despite efforts in computational optimization and inverse design. In this work, we overcome longstanding limitations by introducing a generalized rational design paradigm based on symmetry. Specifically, we use symmetry-broken metasurfaces with periodic “quadromer” lattices comprised of four nanostructures per unit cell to enable extensive control of multiple optical resonances. The rationally designed metasurfaces are readily fabricable, and we experimentally demonstrate metasurfaces that support up to four high Q-factor resonances with deliberately chosen free-space polarizations, spectral separations, and mode profiles. Our design paradigm may unlock new applications for multiresonant metasurfaces in quantum and nonlinear optics, optical sensing, and augmented reality displays.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

Signatures of the exciton gas phase and its condensation in monolayer 1T-ZrTe 2

The excitonic insulator (EI) is a Bose-Einstein condensation (BEC) of excitons bound by electron-hole interaction in a solid, which could support high-temperature BEC transition. The material realization of EI has been challenged by the difficulty of distinguishing it from a conventional charge density wave (CDW) state. In the BEC limit, the preformed exciton gas phase is a hallmark to distinguish EI from conventional CDW, yet direct experimental evidence has been lacking. Here we report a distinct correlated phase beyond the 2×2 CDW ground state emerging in monolayer 1T-ZrTe 2 and its investigation by angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). The results show novel band- and energy-dependent folding behavior in a two-step process, which is the signatures of an exciton gas phase prior to its condensation into the final CDW state. Our findings provide a versatile two-dimensional platform that allows tuning of the excitonic effect.

36 MATERIALS SCIENCE↗

Thermally reconfigurable monoclinic nematic colloidal fluids

Fundamental relationships are believed to exist between the symmetries of building blocks and the condensed matter phases that they form. For example, constituent molecular and colloidal rods and disks impart their uniaxial symmetry onto nematic liquid crystals, such as those used in displays. Low-symmetry organizations could form in mixtures of rods and disks, but entropy tends to phase-separate them at the molecular and colloidal scales, whereas strong elasticity-mediated interactions drive the formation of chains and crystals in nematic colloids. To have a structure with few or no symmetry operations apart from trivial ones has so far been demonstrated to be a property of solids alone, but not of their fully fluid condensed matter counterparts, even though such symmetries have been considered theoretically and observed in magnetic colloids. In this work, we show that dispersing highly anisotropic charged colloidal disks in a nematic host composed of molecular rods provides a platform for observing many low-symmetry phases. Depending on the temperature, concentration and surface charge of the disks, we find nematic, smectic and columnar organizations with symmetries ranging from uniaxial to orthorhombic and monoclinic. With increasing temperature, we observe unusual transitions from less- to more-ordered states and re-entrant phases. Most importantly, we demonstrate the presence of reconfigurable monoclinic colloidal nematic order, as well as the possibility of thermal and magnetic control of low-symmetry self-assembly. Our experimental findings are supported by theoretical modelling of the colloidal interactions between disks in the nematic host and may provide a route towards realizing many low-symmetry condensed matter phases in systems with building blocks of dissimilar shapes and sizes, as well as their technological applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hyperfine interactions for small systems including transition-metal elements using self-interaction corrected density-functional theory

The interactions between the electronic magnetic moment and the nuclear spin moment, i.e., magnetic hyperfine (HF) interactions, play an important role in understanding electronic properties of magnetic systems and in realizing platforms for quantum information science applications. We investigate the HF interactions for atomic systems and small molecules, including Ti or Mn, by using Fermi–Löwdin orbital (FLO) based self-interaction corrected (SIC) density-functional theory. We calculate the Fermi contact (FC) and spin-dipole terms for the systems within the local density approximation (LDA) in the FLO-SIC method and compare them with the corresponding values without SIC within the LDA and generalized-gradient approximation (GGA), as well as experimental data. For the moderately heavy atomic systems (atomic number Z ≤ 25), we find that the mean absolute error of the FLO-SIC FC term is about 27 MHz (percentage error is 6.4%), while that of the LDA and GGA results is almost double that. Therefore, in this case, the FLO-SIC results are in better agreement with the experimental data. For the non-transition-metal molecules, the FLO-SIC FC term has the mean absolute error of 68 MHz, which is comparable to both the LDA and GGA results without SIC. For the seven transition-metal-based molecules, the FLO-SIC mean absolute error is 59 MHz, whereas the corresponding LDA and GGA errors are 101 and 82 MHz, respectively. Therefore, for the transition-metal-based molecules, the FLO-SIC FC term agrees better with experiment than the LDA and GGA results. We observe that the FC term from the FLO-SIC calculation is not necessarily larger than that from the LDA or GGA for all the considered systems due to the core spin polarization, in contrast to the expectation that SIC would increase the spin density near atomic nuclei, leading to larger FC terms.

Chemistry↗

Observation of a Flat and Extended Surface State in a Topological Semimetal

A flat band structure in momentum space is considered key for the realization of novel phenomena. A topological flat band, also known as a drumhead state, is an ideal platform to drive new exotic topological quantum phases. Using angle-resolved photoemission spectroscopy experiments, we reveal the emergence of a highly localized surface state in a topological semimetal BaAl4 and provide its full energy and momentum space topology. We find that the observed surface state is localized in momentum, inside a square-shaped bulk Dirac nodal loop, and in energy, leading to a flat band and a peak in the density of state. These results imply this class of materials as an experimental realization of drumhead surface states and provide an important reference for future studies of the fundamental physics of correlated quantum effects in topological materials.

36 MATERIALS SCIENCE↗

Dirac Fermion Cloning, Moiré Flat Bands, and Magic Lattice Constants in Epitaxial Monolayer Graphene

Tuning interactions between Dirac states in graphene has attracted enormous interest because it can modify the electronic spectrum of the 2D material, enhance electron correlations, and give rise to novel condensed-matter phases such as superconductors, Mott insulators, Wigner crystals, and quantum anomalous Hall insulators. Previous works predominantly focus on the flat band dispersion of coupled Dirac states from different twisted graphene layers. Here in this work, a new route to realizing flat band physics in monolayer graphene under a periodic modulation from substrates is proposed. Graphene/SiC heterostructure is taken as a prototypical example and it is demonstrated experimentally that the substrate modulation leads to Dirac fermion cloning and, consequently, the proximity of the two Dirac cones of monolayer graphene in momentum space. Theoretical modeling captures the cloning mechanism of the Dirac states and indicates that moiré flat bands can emerge at certain magic lattice constants of the substrate, specifically when the period of modulation becomes nearly commensurate with the ($\sqrt{3}$ x $\sqrt{3}$) R30° supercell of graphene. Our results show that epitaxial single monolayer graphene on suitable substrates is a promising platform for exploring exotic many-body quantum phases arising from interactions between Dirac electrons.

36 MATERIALS SCIENCE↗

Towards a Standard Process Management Infrastructure for Workflows Using Python

Orchestrating the execution of ensembles of processes lies at the core of scientific workflow engines on large scale parallel platforms. This is usually handled using platform-specific command line tools, with limited process management control and potential strain on system resources. The PMIx standard provides a uniform interface to system resources. The low level C implementation of PMIx has hampered its use in workflow engines, leading to the development of Python binding that has yet to gain traction. In this paper, we present our work to harden the PMIx Python client, demonstrating its usability using a prototype Python driver to orchestrate the execution of an ensemble of processes. We present experimental results using the prototype on the Summit supercomputer at Oak Ridge National Laboratory. This work lays the foundation for wider adoption of PMIx for workflow engines, and encourages wider support of more PMIx functionality in vendor provided system software stacks.

Elwasif, Wael↗

Deploying synthetic coevolution and machine learning to engineer protein-protein interactions

Fine-tuning of protein-protein interactions occurs naturally through coevolution, but this process is difficult to recapitulate in the laboratory. We describe a platform for synthetic protein-protein coevolution that can isolate matched pairs of interacting muteins from complex libraries. This large dataset of coevolved complexes drove a systems-level analysis of molecular recognition between Z domain–affibody pairs spanning a wide range of structures, affinities, cross-reactivities, and orthogonalities, and captured a broad spectrum of coevolutionary networks. Furthermore, we harnessed pretrained protein language models to expand, in silico, the amino acid diversity of our coevolution screen, predicting remodeled interfaces beyond the reach of the experimental library. Further, the integration of these approaches provides a means of simulating protein coevolution and generating protein complexes with diverse molecular recognition properties for biotechnology and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry

Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗