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At least 793 records · Page 44

Correlated nanoelectronics and the second quantum revolution

The growing field of correlated nanoelectronics exists at the intersection of two established fields: correlated oxide electronics and semiconductor nanoelectronics. The development of quantum technologies that exploit quantum coherence and entanglement for the purposes of computation, simulation, and sensing will require complex material properties to be controlled at nanoscale dimensions. Heterostructures and nanostructures formed at the interface between LaAlO 3 and SrTiO 3 exhibit striking behavior that arises from the ability to program the conductive behavior at extreme nanoscale dimensions. The active electronic layer, SrTiO 3 , exhibits a wide range of gate-tunable phenomena such as ferroelectricity, ferroelasticity, magnetism, superconductivity, and spin–orbit coupling, all of which can be controlled at the nanoscale using two reversible methods: conductive atomic force microscope lithography and ultra-low-voltage electron beam lithography. Mesoscopic devices such as single-electron transistors and quasi-one-dimensional electron waveguides can be “sketched” using these techniques, and the properties of these devices differ significantly from those created from traditional semiconductors, such as Si or GaAs. The strongly correlated nature of the SrTiO 3 system is evident from superconducting behavior as well as a state in which electrons are paired outside the superconducting state. A highly exotic phase was discovered in which a degenerate quantum liquid is formed from bound states of n = 2, 3, 4, … electrons. Further development of correlated nanoelectronics based on the LaAlO 3 /SrTiO 3 system can potentially lead to a general platform for quantum simulation as well as a pathway for the development of highly entangled states of multiple photons.

36 MATERIALS SCIENCE↗

The multichannel i -propyl + O2 reaction system: A model of secondary alkyl radical oxidation

The i-propyl + O2 reaction mechanism has been investigated by definitive quantum chemical methods to establish this system as a benchmark for the combustion of secondary alkyl radicals. Focal point analyses extrapolating to the ab initio limit were performed based on explicit computations with electron correlation treatments through coupled cluster single, double, triple, and quadruple excitations and basis sets up to cc-pV5Z. The rigorous coupled cluster single, double, and triple excitations/cc-pVTZ level of theory was used to fully optimize all reaction species and transition states, thus, removing some substantial flaws in reference geometries existing in the literature. The vital i-propylperoxy radical (MIN1) and its concerted elimination transition state (TS1) were found 34.8 and 4.4 kcal mol−1 below the reactants, respectively. Two β-hydrogen transfer transition states (TS2, TS2′) lie above the reactants by (1.4, 2.5) kcal mol−1 and display large Born–Oppenheimer diagonal corrections indicative of nearby surface crossings. An α-hydrogen transfer transition state (TS5) is discovered 5.7 kcal mol−1 above the reactants that bifurcates into equivalent α-peroxy radical hanging wells (MIN3) prior to a highly exothermic dissociation into acetone + OH. The reverse TS5 → MIN1 intrinsic reaction path also displays fascinating features, including another bifurcation and a conical intersection of potential energy surfaces. An exhaustive conformational search of two hydroperoxypropyl (QOOH) intermediates (MIN2 and MIN3) of the i-propyl + O2 system located nine rotamers within 0.9 kcal mol−1 of the corresponding lowest-energy minima.

Chemistry↗

Melting curves of ice polymorphs in the vicinity of the liquid–liquid critical point

The possible existence of a liquid–liquid critical point in deeply supercooled water has been a subject of debate due to the challenges associated with providing definitive experimental evidence. The pioneering work by Mishima and Stanley [Nature 392, 164–168 (1998)] sought to shed light on this problem by studying the melting curves of different ice polymorphs and their metastable continuation in the vicinity of the expected liquid–liquid transition and its associated critical point. Based on the continuous or discontinuous changes in the slope of the melting curves, Mishima [Phys. Rev. Lett. 85, 334 (2000)] suggested that the liquid–liquid critical point lies between the melting curves of ice III and ice V. Herein we explore this conjecture using molecular dynamics simulations with a machine learning model based on ab initio quantum-mechanical calculations. We study the melting curves of ices III, IV, V, VI, and XIII and find that all of them are supercritical and do not intersect the liquid–liquid transition locus. We also find a pronounced, yet continuous, change in the slope of the melting lines upon crossing of the liquid locus of maximum compressibility. Finally, we analyze the literature in light of our findings and conclude that the scenario in which the melting curves are supercritical is favored by the most recent computational and experimental evidence. Although the preponderance of evidence is consistent with the existence of a second critical point in water, the behavior of ice polymorph melting lines does not provide strong evidence in support of this viewpoint, according to our calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of helicon waves with phase contrast imaging on DIII-D – A theoretical feasibility study

A DIII-D high-beta H-mode discharge, with I p = 850 kA, B t = 2.1 T n e = 4 10 19 m –3 , has been designed to validate full wave modeling of helicon waves by optimizing the expected response of the Phase Contrast Imaging diagnostic. Helicon waves have been predicted to have high current drive efficiency off-axis without facing the accessibility issues of lower-hybrid waves. To test these predictions experimentally, DIII-D has recently commissioned a high-power helicon antenna. To confidently predict the behavior of helicon waves in future devices, measurements of their fundamental properties and validation against models will be essential. Phase contrast imaging (PCI) is an absolutely calibrated internal reference interferometer able to measure density fluctuations with radial wavenumbers k R between 1.5 cm –1 and 20 cm –1 . For helicon waves 2 cm –1 < k R < 10 cm –1 is expected, allowing PCI to measure their envelope and wavenumber spectrum. This makes PCI a powerful tool for the validation of state-of-the-art models, like the AORSA full wave code. AORSA is used to compute the density perturbations measured by the PCI with 2D calculations corresponding to 11 different toroidal mode numbers combined to resolve the trajectory of the helicon wave in 3D. This is necessary because the waves travel 120 degrees toroidally from the antenna to the PCI. Here, a cold plasma finite element model (CPFEM) [4] is used to predict propagation through the scrape-off layer. The result of the CPFEM model is connected to AORSA by creating an artificial Gaussian antenna on the last closed flux surface. PCI shows best results for waves with small vertical wavenumbers k z . Modeling the helicon waves for several past DIII-D experiments shows that k z is minimized if the intersection of the helicon and the PCI laser beams occurs in the midplane. For such an optimized scenario the predicted signal level is two orders of magnitude larger than the background density fluctuations arising from broadband turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Physics and applications of dusty plasmas: The Perspectives 2023

Dusty plasmas are electrically quasi-neutral media that, along with electrons, ions, neutral gas, radiation, and electric and/or magnetic fields, also contain solid or liquid particles with sizes ranging from a few nanometers to a few micrometers. These media can be found in many natural environments as well as in various laboratory setups and industrial applications. As a separate branch of plasma physics, the field of dusty plasma physics was born in the beginning of 1990s at the intersection of the interests of the communities investigating astrophysical and technological plasmas. An additional boost to the development of the field was given by the discovery of plasma crystals leading to a series of microgravity experiments of which the purpose was to investigate generic phenomena in condensed matter physics using strongly coupled complex (dusty) plasmas as model systems. Finally, the field has gained an increasing amount of attention due to its inevitable connection to the development of novel applications ranging from the synthesis of functional nanoparticles to nuclear fusion and from particle sensing and diagnostics to nano-contamination control. The purpose of the present perspectives paper is to identify promising new developments and research directions for the field. As such, dusty plasmas are considered in their entire variety: from classical low-pressure noble-gas dusty discharges to atmospheric pressure plasmas with aerosols and from rarefied astrophysical plasmas to dense plasmas in nuclear fusion devices. Both fundamental and application aspects are covered.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Consistent and reproducible computation of the glass transition temperature from molecular dynamics simulations

In many fields, from semiconductors for opto-electronic applications to ionic liquids (ILs) for separations, the glass transition temperature (Tg) of a material is a useful gauge for its potential use in practical settings. As a result, there is a great deal of interest in predicting Tg using molecular simulations. However, the uncertainty and variation in the trend shift method, a common approach in simulations to predict Tg, can be high. This is due to the need for human intervention in defining a fitting range for linear fits of density with temperature assumed for the liquid and glass phases across the simulated cooling. The definition of such fitting ranges then defines the estimate for the Tg as the intersection of linear fits. We eliminate this need for human intervention by leveraging the Shapiro–Wilk normality test and proposing an algorithm to define the fitting ranges and, consequently, Tg. Through this integration, we incorporate into our automated methodology that residuals must be normally distributed around zero for any fit, a requirement that must be met for any regression problem. Consequently, fitting ranges for realizing linear fits for each phase are statistically defined rather than visually inferred, obtaining an estimate for Tg without any human intervention. The method is also capable of finding multiple linear regimes across density vs temperature curves. We compare the predictions of our proposed method across multiple IL and semiconductor molecular dynamics simulation results from the literature and compare other proposed methods for automatically detecting Tg from density–temperature data. We believe that our proposed method would allow for more consistent predictions of Tg. We make this methodology available and open source through GitHub.

Chemistry↗

When in-memory computing meets spiking neural networks—A perspective on device-circuit-system-and-algorithm co-design

This review explores the intersection of bio-plausible artificial intelligence in the form of spiking neural networks (SNNs) with the analog in-memory computing (IMC) domain, highlighting their collective potential for low-power edge computing environments. Through detailed investigation at the device, circuit, and system levels, we highlight the pivotal synergies between SNNs and IMC architectures. Additionally, we emphasize the critical need for comprehensive system-level analyses, considering the inter-dependencies among algorithms, devices, circuit, and system parameters, crucial for optimal performance. An in-depth analysis leads to the identification of key system-level bottlenecks arising from device limitations, which can be addressed using SNN-specific algorithm–hardware co-design techniques. This review underscores the imperative for holistic device to system design-space co-exploration, highlighting the critical aspects of hardware and algorithm research endeavors for low-power neuromorphic solutions.

Physics↗

Imaging the photochemistry of cyclobutanone using ultrafast electron diffraction: Experimental results

We investigated the ultrafast structural dynamics of cyclobutanone following photoexcitation at λ = 200 nm using gas-phase megaelectronvolt ultrafast electron diffraction. Our investigation complements the simulation studies of the same process within this special issue. It provides information about both electronic state population and structural dynamics through well-separable inelastic and elastic electron scattering signatures. We observe the depopulation of the photoexcited S 2 state of cyclobutanone with n3s Rydberg character through its inelastic electron scattering signature with a time constant of (0.29 ± 0.2) ps toward the S 1 state. The S 1 state population undergoes ring-opening via a Norrish Type-I reaction, likely while passing through a conical intersection with S 0 . The corresponding structural changes can be tracked by elastic electron scattering signatures. These changes appear with a delay of (0.14 ± 0.05) ps with respect to the initial photoexcitation, which is less than the S 2 depopulation time constant. This behavior provides evidence for the ballistic nature of the ring-opening once the S 1 state is reached. The resulting biradical species react further within (1.2 ± 0.2) ps via two rival fragmentation channels yielding ketene and ethylene, or propene and carbon monoxide. Furthermore, our study showcases the value of both gas-phase ultrafast diffraction studies as an experimental benchmark for nonadiabatic dynamics simulation methods and the limits in the interpretation of such experimental data without comparison with such simulations.

Carbon monoxide↗

On transport of electrons in a magnetized plasma sheath

Electron trajectories are analyzed in the plasma sheath region in a magnetic field that intersects the surface at a shallow angle. Depending on the size of the Debye width relative to the electron gyroradius, λ D /ρ e , an electron either drifts in the sheath electric field or follows a sequence of reflections (“bouncing”) on the surface before reversing its parallel velocity. For thin sheath, λ D /ρ e ≪ 1, the conservation of the electron magnetic moment can be violated, depending on the ratio of the electron perpendicular and parallel velocities V ⊥ /V || and the magnetic field pitch angle with respect to the surface. Small-scale waviness of the surface can strongly amplify this effect, leading to violation of the magnetic moment conservation even for λ D /ρ e ≳ 1, which opens a channel of anomalous radial transport for electrons in plasma devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

X-ray diffraction strains in laser-ablated aluminum, nickel, sodium, and invar: Pressures to 475 GPa

Dynamically compressed materials in longitudinal waves are described by two physical models: hydrostatic pressure, with equal, normal, principal stresses or material uniaxially strained in the wave propagation direction. These models are disparate, so experimental comparisons and evaluations are important. Polycrystalline material in a state of hydrostatic pressure will have no eccentricity of x-ray-diffracted Debye–Scherrer rings. A general three-dimensional solution of Bragg diffracted x rays based on principal crystallographic strains in the compression wave was found. The distortion of x-ray diffraction beams has been used for strain measurements; the analysis developed incorporates a strained reciprocal lattice and the incident x-ray beam. Strain-distorted Polanyi surfaces form an annulus of compression with an ellipsoid of revolution in reciprocal space, which is intersected by Ewald's sphere for Bragg diffraction. The in situ measurements for strain describe nanosecond diffraction evaluated using two planes, (hkl) and (h′k′l′), both in the same crystallographic phase. Diffraction from Al, Ni, Na, and Invar quantifies the compression axial strains in these materials: The compression axial ratios are 0.65, 1.05, 0.88, and 1.58 at pressures of 291, 402, 409, and 367 GPa for the respective materials. Crystal structure transformations with homogeneous pressurized stresses, mandating equal normal strains, should not be anticipated to agree with heterogeneous, uniaxially strained, and sheared crystalline phases. Measurements support in-plane strains increasing with pressure, p , in fcc and hcp aluminum as ε 22 = −0.21 p /TPa.

Alloys↗

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Machine Learning for Mapping Multipactor Susceptibility in RF Systems: Capabilities and Generalization Constraints

Multipactor is a surface-driven electron avalanche phenomenon that degrades the performance and reliability of radio-frequency (RF) systems in particle accelerator and vacuum electronics applications. Multipactor behavior in a given device structure is conventionally assessed through susceptibility charts, which provide a parameter-space characterization of the instability. In this work, we assess the capabilities of machine-learning (ML) models to learn and predict such susceptibility charts and analyze the constraints governing their generalization across materials. Using a simulation-derived dataset spanning six distinct secondary-electron-yield material profiles in a canonical two-surface planar geometry, we train supervised regression models and artificial neural networks to predict the time-averaged electron growth rate, δavg, across the relevant parameter space. Model performance is evaluated using metrics that explicitly probe the structure of susceptibility charts, including Intersection over Union, Structural Similarity Index, and correlation analysis. Tree-based ensemble models outperform neural-network models in reconstructing susceptibility regions and in generalizing across material domains. Principal-component analysis reveals disjoint material feature distributions, indicating that the piecewise mode structure of multipactor susceptibility is difficult to represent with a single global model and that generalization is constrained by data coverage rather than by model complexity. An exhaustive reduced-coverage study further shows that sparse material-space coverage can yield mean performance in the same general range but producing large variability in the susceptibility-region overlap. These results clarify the capabilities of ML-based surrogate models for parameter-space characterization of multipactor discharge. They also provide guidance for their appropriate use in RF system design.

43 PARTICLE ACCELERATORS↗

Bivalent recognition of fatty acyl-CoA by a human integral membrane palmitoyltransferase

S-acylation, also known as palmitoylation, is the most abundant form of protein lipidation in humans. This reversible posttranslational modification, which targets thousands of proteins, is catalyzed by 23 members of the DHHC family of integral membrane enzymes. DHHC enzymes use fatty acyl-CoA as the ubiquitous fatty acyl donor and become autoacylated at a catalytic cysteine; this intermediate subsequently transfers the fatty acyl group to a cysteine in the target protein. Protein S-acylation intersects with almost all areas of human physiology, and several DHHC enzymes are considered as possible therapeutic targets against diseases such as cancer. These efforts would greatly benefit from a detailed understanding of the molecular basis for this crucial enzymatic reaction. Here, in this study, we combine X-ray crystallography with all-atom molecular dynamics simulations to elucidate the structure of the precatalytic complex of human DHHC20 in complex with palmitoyl CoA. The resulting structure reveals that the fatty acyl chain inserts into a hydrophobic pocket within the transmembrane spanning region of the protein, whereas the CoA headgroup is recognized by the cytosolic domain through polar and ionic interactions. Biochemical experiments corroborate the predictions from our structural model. We show, using both computational and experimental analyses, that palmitoyl CoA acts as a bivalent ligand where the interaction of the DHHC enzyme with both the fatty acyl chain and the CoA headgroup is important for catalytic chemistry to proceed. This bivalency explains how, in the presence of high concentrations of free CoA under physiological conditions, DHHC enzymes can efficiently use palmitoyl CoA as a substrate for autoacylation.

59 BASIC BIOLOGICAL SCIENCES↗

Photoisomerization transition state manipulation by entangled two-photon absorption

Significance Entangled two-photon absorption has attracted considerable interest due to its potential applications for low–photon flux spectroscopy and microscopy. The entanglement parameters in the twin-photon state can be exploited to control two-photon excitation processes. Here we demonstrate that photon entanglement provides a powerful novel control knob for the nuclear wave packets in an optically dark electronic state. We show that the transition states in the trans–cis photoisomerization of azobenzene, initiated by an entangled two-photon absorption process, can be manipulated significantly by entangled light. These effects can be monitored experimentally by coherent stimulated X-ray Raman signals which reveal electronic coherences during the passage through conical intersections.

54 ENVIRONMENTAL SCIENCES↗

Impact of bioenergy feedstock carbon farming on sustainable aviation fuel viability in the United States

Biomass-derived sustainable aviation fuel holds significant potential for decarbonizing the aviation sector. Its long-term viability depends on crop choice, longevity of soil organic carbon (SOC) sequestration, and the biomass-to-biojet fuel conversion efficiency. We explored the impact of fuel price and SOC value on viable biojet fuel production scale by integrating an agroecosystem model with a field-to-biojet fuel production process model for 1,4-dimethylcyclooctane (DMCO), a representative high-performance biojet fuel molecule, from Miscanthus, sorghum, and switchgrass. Assigning monetary value to SOC sequestration results in substantially different outcomes than an increased fuel selling price. If SOC accumulation is valued at $185/ton CO 2 , planting Miscanthus for conversion to DMCO would be economically cost-competitive across 66% of croplands across the continental United States (US) by 2050 if conventional jet fuel remains at $0.74/L (in 2020 US dollars). Cutting the SOC sequestration value in half reduces the viable area to 54% of cropland, and eliminating any payment for SOC shrinks the viable area to 16%. If future biojet fuel prices increase to $1.24/L-Jet A-equivalent, 48 to 58% of the total cultivated land in the United States could support a more diverse set of feedstocks including Miscanthus, sorghum, or switchgrass. Among these options, only 8–14% of the area would be suitable exclusively for Miscanthus cultivation. These findings highlight the intersection of natural solutions for carbon removal and the use of deep-rooted feedstocks for biofuels and biomanufacturing. The results underscore the need to establish clear and consistent values for SOC sequestration to enable the future bioeconomy.

09 BIOMASS FUELS↗

Audible enclaves crafted by nonlinear self-bending ultrasonic beams

Delivering audible content to a targeted listener without disturbing others is paramount in audio engineering. However, achieving this goal has long been challenging due to the diffraction of low-frequency (long-wavelength) audio waves in linear acoustics. Here, we introduce an approach for creating remote audio spots, dubbed audible enclaves, by harnessing the local nonlinear interaction of two self-bending ultrasonic beams with distinct spectra. The self-bending ultrasonic beams created by acoustic metasurfaces, though inaudible, can bypass obstacles such as human heads. At their intersection behind obstacles, highly localized audible enclaves are formed due to the local nonlinear interactions. Additionally, we demonstrate the ultrabroadband capabilities of our metasurface-based implementation both numerically and experimentally, spanning from 125 Hz to 4 kHz (6 octave bands), covering the majority of the audible frequency range. The practicality of our proposed technique is underscored by its compact implementation size (0.16 m, equivalent to 0.06 wavelengths at 125 Hz), as well as its robust performance under wideband transient audio signal excitation and in a common room with reverberations. Our proposed audible enclaves hold significant potential for various applications in advanced audio engineering, including private speech communications, immersive spatial audio reproduction, and high-resolution sound/quiet zone control.

Science & Technology - Other Topics↗

What is quantum biology?

Quantum biology is the field at the intersection of quantum-related physics and the biology of living systems. The goal of the field is to determine if quantum phenomena underpin biological function at the macroscale. Such results, supported by compelling experimental evidence, will be important because they will show how quantum effects can have functional relevance, even in very complex and nominally classical systems. Here, we attempt to define the scope of quantum biology with a forward-facing view to help focus the research agenda. To that end, we propose open questions fundamental to consolidating the field of quantum biology. These open questions highlight the importance of developing suitable probes at the quantum scale, the possibility that classical biological machinery might simply mimic quantum systems, and of elucidating the ways quantum function can be amplified to the macroscale.

coherence↗

Analytic gradients for compressed multistate pair-density functional theory

Photochemical reactions often involve states that are closely coupled due to near degeneracies, for example by proximity to conical intersections. Therefore, a multistate method is used to accurately describe these states; for example, ordinary perturbation theory is replaced by quasidegenerate perturbation theory. Multiconfiguration pair-density functional theory (MC-PDFT) provides an efficient way to approximate the full dynamical correlation energy of strongly correlated systems, and we recently proposed compressed multistate pair-density functional theory (CMS-PDFT) to treat closely coupled states. In the present paper, we report the implementation of analytic gradients for CMS-PDFT in both OpenMolcas and PySCF, and here we illustrate the use of these gradients by applying the method to the excited states of formaldehyde and phenol.

74 ATOMIC AND MOLECULAR PHYSICS↗