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At least 1,549 records · Page 86

Two-color polarization spectroscopy measurements of Zeeman state-to-state collision induced transitions of nitric oxide in binary gas mixtures

We investigated collision induced transitions in the (0, 0) band of the A2Σ+–X2Π electronic transition of nitric oxide (NO) using two-color polarization spectroscopy (TCPS). Two sets of TCPS spectra for 1% NO, diluted in different buffer gases at 295 K and 1 atm, were obtained with the pump beam tuned to the R11(11.5) and OP12(1.5) transitions. The buffer gases were He, Ar, and N2. The probe was scanned while the pump beam was tuned to the line center. Theoretical TCPS spectra, calculated by solving the density matrix formulation of the time-dependent Schrödinger wave equation, were compared with the experimental spectra. A collision model based on the modified exponential-gap law was used to model the rotational level-to-rotational level collision dynamics. A model for collisional transfer from an initial to a final Zeeman state was developed based on the difference in cosine of the rotational quantum number J projection angle with the z-axis for the two Zeeman states. Rotational energy transfer rates and Zeeman state collisional dynamics were varied to obtain good agreement between theory and experiment for the two different TCPS pump transitions and for the three different buffer gases. One key finding, in agreement with quasi-classical trajectory calculations, is that the spin-rotation changing transition rate in the A2Σ+ level of NO is almost zero for rotational quantum numbers ≥8. It was necessary to set this rate to near zero to obtain agreement with the TCPS spectra.

Chemistry↗

Energy conversion and transport in molecular-scale junctions

Molecular-scale junctions (MSJs) have been considered the ideal testbed for probing physical and chemical processes at the molecular scale. Due to nanometric confinement, charge and energy transport in MSJs are governed by quantum mechanically dictated energy profiles, which can be tuned chemically or physically with atomic precision, offering rich possibilities beyond conventional semiconductor devices. While charge transport in MSJs has been extensively studied over the past two decades, understanding energy conversion and transport in MSJs has only become experimentally attainable in recent years. As demonstrated recently, by tuning the quantum interplay between the electrodes, the molecular core, and the contact interfaces, energy processes can be manipulated to achieve desired functionalities, opening new avenues for molecular electronics, energy harvesting, and sensing applications. This Review provides a comprehensive overview and critical analysis of various forms of energy conversion and transport processes in MSJs and their associated applications. We elaborate on energy-related processes mediated by the interaction between the core molecular structure in MSJs and different external stimuli, such as light, heat, electric field, magnetic field, force, and other environmental cues. Key topics covered include photovoltaics, electroluminescence, thermoelectricity, heat conduction, catalysis, spin-mediated phenomena, and vibrational effects. Furthermore, the review concludes with a discussion of existing challenges and future opportunities, aiming to facilitate in-depth future investigation of promising experimental platforms, molecular design principles, control strategies, and new application scenarios.

Charge transport↗

Hierarchical Ion Interactions in the Direct Air Capture of CO 2 at Air/Aqueous Interfaces

The direct air capture (DAC) of CO 2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly - ), an effective CO 2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly - and captured carbonaceous anions (HCO 3 - , CO 3 2 -, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.

54 ENVIRONMENTAL SCIENCES↗

Structural properties and recrystallization effects in ion beam modified B20-type FeGe films

Disordered iron germanium (FeGe) has recently garnered interest as a testbed for a variety of magnetic phenomena as well as for use in magnetic memory and logic applications. This is partially owing to its ability to host skyrmions and antiskyrmions—nanoscale whirlpools of magnetic moments that could serve as information carriers in spintronic devices. In particular, a tunable skyrmion–antiskyrmion system may be created through precise control of the defect landscape in B20-phase FeGe, motivating the development of methods to systematically tune disorder in this material and understand the ensuing structural properties. To this end, we investigate a route for modifying magnetic properties in FeGe. In particular, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au 4+ ions, which creates a dispersion of amorphized regions that may preferentially host antiskyrmions at densities controlled by the irradiation fluence. To further tune the disorder landscape, we conduct a systematic electron diffraction study with in situ annealing, demonstrating the ability to recrystallize controllable fractions of the material at temperatures ranging from ~150 to 250°C. Finally, we describe the crystallization kinetics using the Johnson–Mehl–Avrami–Kolmogorov model, finding that the growth of crystalline grains is consistent with diffusion-controlled one-to-two dimensional growth with a decreasing nucleation rate.

36 MATERIALS SCIENCE↗

PhysBERT: A text embedding model for physics scientific literature

The specialized language and complex concepts in physics pose significant challenges for information extraction through Natural Language Processing (NLP). Central to effective NLP applications is the text embedding model, which converts text into dense vector representations for efficient information retrieval and semantic analysis. In this work, we introduce PhysBERT, the first physics-specific text embedding model. Pre-trained on a curated corpus of 1.2 × 106 arXiv physics papers and fine-tuned with supervised data, PhysBERT outperforms leading general-purpose models on physics-specific tasks, including the effectiveness in fine-tuning for specific physics subdomains.

Hellert, Thorsten (ORCID:0000000227970926)↗

Reward based optimization of resonance-enhanced piezoresponse spectroscopy

Dynamic spectroscopies in scanning probe microscopy (SPM) are critical for probing material properties, such as force interactions, mechanical properties, polarization switching, electrochemical reactions, and ionic dynamics. However, the practical implementation of these measurements is constrained by the need to balance imaging time and data quality. Signal to noise requirements favor long acquisition times and high frequencies to improve signal fidelity. However, these are limited on the low end by contact resonant frequency and photodiode sensitivity and on the high end by the time needed to acquire high-resolution spectra or the propensity for sample degradation under high field excitation over long times. The interdependence of key parameters such as instrument settings, acquisition times, and sampling rates makes manual tuning labor-intensive and highly dependent on user expertise, often yielding operator-dependent results. These limitations are prominent in techniques like dual amplitude resonance tracking in piezoresponse force microscopy that utilize multiple concurrent feedback loops for topography and resonance frequency tracking. Here, a reward-driven workflow is proposed that automates the tuning process, adapting experimental conditions in real time to optimize data quality. Furthermore, this approach significantly reduces the complexity and time required for manual adjustments and can be extended to other SPM spectroscopic methods, enhancing overall efficiency and reproducibility.

47 OTHER INSTRUMENTATION↗

Molecular surface programming of rectifying junctions between InAs colloidal quantum dot solids

Heavy-metal-free III–V colloidal quantum dots (CQDs) show promise in optoelectronics: Recent advancements in the synthesis of large-diameter indium arsenide (InAs) CQDs provide access to short-wave infrared (IR) wavelengths for three-dimensional ranging and imaging. In early studies, however, we were unable to achieve a rectifying photodiode using CQDs and molybdenum oxide/polymer hole transport layers, as the shallow valence bandedge (5.0 eV) was misaligned with the ionization potentials of the widely used transport layers. This occurred when increasing CQD diameter to decrease the bandgap below 1.1 eV. Here, we develop a rectifying junction among InAs CQD layers, where we use molecular surface modifiers to tune the energy levels of InAs CQDs electrostatically. Previously developed bifunctional dithiol ligands, established for II-VI and IV-VI CQDs, exhibit slow reaction kinetics with III-V surfaces, causing the exchange to fail. Here, we study carboxylate and thiolate binding groups, united with electron-donating free end groups, that shift upward the valence bandedge of InAs CQDs, producing valence band energies as shallow as 4.8 eV. Photophysical studies combined with density functional theory show that carboxylate-based passivants participate in strong bidentate bridging with both In and As on the CQD surface. The tuned CQD layer incorporated into a photodiode structure achieves improved performance with EQE (external quantum efficiency) of 35% (>1 μm) and dark current density < 400 nA cm -2 , a >25% increase in EQE and >90% reduced dark current density compared to the reference device. This work represents an advance over previous III-V CQD short-wavelength IR photodetectors (EQE < 5%, dark current > 10,000 nA cm -2 ).

36 MATERIALS SCIENCE↗

Controlling laser-dressed resonance line shape using attosecond extreme-ultraviolet pulse with a spectral minimum

High-harmonic generation from a gas target exhibits sharp spectral features and rapid phase variation near the Cooper minimum. By applying spectral filtering, shaped isolated attosecond pulses can be generated where the pulse is split into two in the time domain. Using such shaped extreme-ultraviolet (XUV) pulses, we theoretically study attosecond transient absorption (ATA) spectra of helium 2s2p autoionizing state which is resonantly coupled to the 2s 2 dark state by a time-delayed infrared laser. Our simulations show that the asymmetric 2s2p Fano line shape can be readily tuned into symmetric Lorentzian within the time delay of a few tens of attoseconds. Such efficient control is due to the destructive interference in the generation of the 2s2p state when it is excited by a strongly shaped XUV pulse. This is to be compared to prior experiments where tuning the line shape of a Fano resonance would take tens of femtoseconds. We also show that the predicted ATA spectral line shape can be observed experimentally after propagation in a gas medium. Our results suggest that strongly shaped attosecond XUV pulses offer the opportunity for controlling and probing fine features of narrow resonances on the few-ten attoseconds timescale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Photoenzymatic Csp 3 –Csp 3 bond formation via enzyme-templated radical–radical coupling

Cross-couplings are essential reactions in modern chemical synthesis, enabling the rapid construction of complex molecules from simple precursors. Transition metal catalysts are prized for these transformations because their reactivity and selectivity can be tuned via judicious selection of the metal and ligand. Although enzymes offer analogous opportunities for tuning via protein engineering, their application to cross-coupling remains limited, as nature relies on alternative paradigms for building molecular complexity. Here, we report the cross-coupling of alkyl halides and benzylic carboxylic acids using an engineered flavin-dependent lactate monooxygenase—a photoenzyme. The enzyme achieves this feat by exploiting the redox versatility of the flavin cofactor. Stoichiometric experiments, ultrafast spectroscopy, and computational studies support a mechanism in which photoexcited flavin quinone initiates the reaction via oxidative decarboxylation to generate a benzylic radical. The resulting flavin semiquinone can reduce the alkyl halide to form a second organic radical within the protein active site, which rapidly engages in C(sp 3 )–C(sp 3 ) bond formation. A variant was engineered to control the stereochemical outcome of this radical–radical coupling event, highlighting the ability of the protein to alter the energetic barrier for a mechanistic step that is traditionally understood to be near barrierless. This work demonstrates that the scope for nonnative reaction mechanisms in biocatalysis far exceeds previously established bounds and has potential to solve a variety of reactivity challenges in cross-coupling chemistry.

biocatalysis↗

The Sensitivity of Variational Bayesian Neural Network Performance to Hyperparameters

In scientific applications, predictive modeling is often of limited use without accurate uncertainty quantification (UQ) to indicate when a model may be extrapolating or when more data needs to be collected. Bayesian Neural Networks (BNNs) produce predictive uncertainty by propagating uncertainty in neural network (NN) weights and offer the promise of obtaining not only an accurate predictive model but also accurate UQ. However, in practice, obtaining accurate UQ with BNNs is difficult due in part to the approximations used for model training (such as those made in variational inference) and in part to the need to choose a suitable set of hyperparameters; these hyperparameters outnumber those needed for traditional NNs and often have opaque effects on the results. We aim to shed light on the effects of hyperparameter choices for variational BNNs by performing a global sensitivity analysis of variational BNN performance under varying hyperparameter settings. Our results indicate that many of the hyperparameters interact with each other to affect both predictive accuracy and UQ. For improved usage of variational BNNs in real-world applications, we suggest that thorough hyperparameter tuning, including tuning of prior hyperparameters and loss function parameters, is essential for accurate UQ in variational BNNs.

97 MATHEMATICS AND COMPUTING↗

Optimization and supervised machine learning methods for fitting numerical physics models without derivatives

Here, we address the calibration of a computationally expensive nuclear physics model for which derivative information with respect to the fit parameters is not readily available. Of particular interest is the performance of optimization-based training algorithms when dozens, rather than millions or more, of training data are available and when the expense of the model places limitations on the number of concurrent model evaluations that can be performed. As a case study, we consider the Fayans energy density functional model, which has characteristics similar to many model fitting and calibration problems in nuclear physics. We analyze hyperparameter tuning considerations and variability associated with stochastic optimization algorithms and illustrate considerations for tuning in different computational settings.

97 MATHEMATICS AND COMPUTING↗

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

Emergence of ferrimagnetism in Li-intercalated NiPS 3

AbstractIntercalation has become a powerful approach to tune the intrinsic properties and introduce novel phenomena in layered materials. Intercalating van der Waals (vdW) magnetic materials is a promising route to engineer the low-dimensional magnetism. Recently, metal thiophosphates, MPX 3 , has been widely studied because their magnetic orders are highly tunable and persist down to the two-dimensional limit. In this work, we used electrochemical technique to intercalate Li into NiPS 3 single crystals and found the emergence of ferrimagnetism at low temperature in Li-intercalated NiPS 3 . Such tuning of magnetic properties highlights the effectiveness of intercalation, providing a novel strategy to manipulate the magnetism in vdW magnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Utilization of coupled eigenmodes in Akiyama atomic force microscopy probes for bimodal multifrequency sensing

Akiyama atomic force microscopy probes represent a unique means of combining several of the desirable properties of tuning fork and cantilever probe designs. As a hybridized mechanical resonator, the vibrational characteristics of Akiyama probes result from a complex coupling between the intrinsic vibrational eigenmodes of its constituent tuning fork and bridging cantilever components. Here, through a combination of finite element analysis modeling and experimental measurements of the thermal vibrations of Akiyama probes, we identify a complex series of vibrational eigenmodes and measure their frequencies, quality factors, and spring constants. We then demonstrate the viability of Akiyama probes to perform bimodal multi-frequency force sensing by performing a multimodal measurement of a surface's nanoscale photothermal response using photo-induced force microscopy imaging techniques. Further performing a parametric search over alternative Akiyama probe geometries, we propose two modified probe designs to enhance the capability of Akiyama probes to perform sensitive bimodal multifrequency force sensing measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗

Multilayer film coating for laser ion source target for increase of low charge state production

The use of Laser Ion Source for accelerator facilities has the advantage to tune the characteristic of the produced beams by changing the laser parameters using the same primary target. The advantageous and innovative opportunity to manipulate the characteristic of charge state distributions by the use of composed target, may open new possibilities for the ion sources. In this experiment we characterize and study the plasma produced by the laser ablation of coated targets at constant laser parameters. The performed investigation has the double purpose to have a better understanding of penetration depth of laser in composed materials and understand how to tune the charge states by adding coating films. Finally, the obtained results showed that for particular thickness of coating, the low charge states were produced with higher yield than in the case of pure material.

43 PARTICLE ACCELERATORS↗

An Update to the National Renewable Energy Laboratory Baseline Wind Turbine Controller

The National Renewable Energy Laboratory's 5-MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the 5-MW wind turbine uses a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into fast-paced development cycles, as systems engineering tools such as Wind-Plant Integrated System Design & Engineering Model (WISDEM ®) [1] are employed, and as a greater focus on controls co-design practices is encouraged, demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5-MW controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process while maintaining or improving the performance of the legacy NREL 5-MW controller.

17 WIND ENERGY↗

Self-consistent PIC simulations of ultimate space charge compensation with electron lenses

Further progress of fundamental particle physics requires high intensity and high brightness of accelerated proton and ion beams. This goal is essential for the FAIR hadron beams at GSI, for the neutrino production at the facilities such as Fermilab and JPARC, and for the Large Hadron Collider luminosity at CERN. One of the most formidable obstacles toward that goal is the beam's own space charge, whose forces cause beam emittance growth, losses and lifetime degradation. Typically, such effects become intolerable when the space charge tune-shift parameter Δ QSC exceeds ~ - (0.25–0.5). To reduce these detrimental effects, it was suggested to use electron lenses to compensate the space charge forces. Furthermore, this paper reports on detailed particle-in-cell space charge and electron lens compensation simulations for extremely intense proton bunches whose space charge tune-shift parameter exceeds -1.0. Different scenarios were evaluated based on reduction in the emittance growth and particle loss at a 4σ aperture. Further, we investigate phenomena and issues related to the focusing lattice errors, importance of the transverse and longitudinal matching of the electron beam profiles to the proton ones, and vary the strength and the number of the electron lenses distributed around a circular machine to optimize the reduction of harmful space charge effects.

43 PARTICLE ACCELERATORS↗