Cooperative Noncovalent Interactions Induce Ion Pair Separation in Diphenylsilanides
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As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.
DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.
One of the defining characteristics of a solar flare is the impulsive formation of very high temperature plasma. The properties of the thermal emission are not well understood, however, and the analysis of solar flare observations is often predicated on the assumption that the flare plasma is isothermal. The EUV Variability Experiment (EVE) on the Solar Dynamics Observatory provides spectrally resolved observations of emission lines that span a wide range of temperatures (e.g., Fe XV-Fe XXIV) and allow for thermal flare plasma to be studied in detail. In this paper we describe a method for computing the differential emission measure distribution in a flare using EVE observations and apply it to several representative events. We find that in all phases of the flare the differential emission measure distribution is broad. Comparisons of EVE spectra with calculations based on parameters derived from the Geostationary Operational Environmental Satellites soft X-ray fluxes indicate that the isothermal approximation is generally a poor representation of the thermal structure of a flare.
Highlights: • Theoretical framework to identify optimal multilayers for high x-ray reflectivity. • Perovskite oxide multilayers are proposed as soft x-ray mirrors. • High soft x-ray reflectivity up to 33% are expected in perovskite multilayers. - Abstract: We propose multilayers of perovskite and related ternary oxides with a general formula of ABO{sub 3} as high reflectivity mirrors, especially for use in water window region (2.3–4.4 nm). The high reflectivity combinations of oxide multilayers were deduced using evolutionary search algorithms such as genetic algorithms, and the calculation speed was accelerated via parallel computing methods We also propose a figure of merit for X-ray reflectivity in periodic multilayers systems, which can simplify the future efforts on identifying material combinations, and the search through this multi-dimensional parameter space. The highest reflectivity value was found to be over 33% at 3.1 nm in the water window region. The effect of interface roughness was simulated and the decrease in reflectivity was found to be modest for practically achievable roughness values. This work establishes the foundation for future experimental and theoretical studies towards achieving high reflectivity x-ray mirrors of complex oxide multilayers.
The past several years have witnessed important developments in the QCD theory of jet production and jet substructure in hadronic collisions. In the framework of soft-collinear effective theory, semi-inclusive jet functions and semi-inclusive fragmenting jet functions have allowed us to combine higher order calculations with resummation of potentially large logarithms of the jet radius, ln R. Very recently, the semi-inclusive jet functions for partons fragmenting into heavy flavor jets were computed by Dai, Kim and Leibovich. In this paper we show how the formalism can be extended to c-jet and b-jet production in heavy ion collisions. The semi-inclusive jet functions for heavy flavor jets in a QCD medium are evaluated up to the next-to-leading order in αs and first order in opacity. For phenomenological applications, we also consider the inclusion of the cold nuclear matter effects and the jet energy dissipation due to collisional interactions in matter. We present the numerical predictions for the cross sections and the corresponding nuclear modification factors in proton-nucleus and nucleus-nucleus collisions and compare our results to data from the Large Hadron Collider.
The study of macromolecular systems may require large computer simulations that are too time consuming and resource intensive to execute in full atomic detail. The integral equation coarse-graining approach by Guenza and co-workers enables the exploration of longer time and spatial scales without sacrificing thermodynamic consistency, by approximating collections of atoms using analytically-derived soft-sphere potentials. Because coarse-grained (CG) characterizations evolve polymer systems far more efficiently than the corresponding united atom (UA) descriptions, we can feasibly equilibrate a CG system to a reasonable geometry, then transform back to the UA description for a more complete equilibration. Automating the transformation between the two different representations simultaneously exploits CG efficiency and UA accuracy. By iteratively mapping back and forth between CG and UA, we can quickly guide the simulation towards a configuration that would have taken many more time steps within the UA representation alone. Accomplishing this feat requires a diligent workflow for managing input/output coordinate data between the different steps, deriving the potential at runtime, and inspecting convergence. Here in this article, we present a lightweight workflow environment that accomplishes such fast equilibration without user intervention. The workflow supports automated mapping between the CG and UA descriptions in an iterative, scalable, and customizable manner. We describe this technique, examine its feasibility, and analyze its correctness.
Wearable thermoregulatory technologies have attracted widespread attention because of their potential for impacting individual physiological comfort and for reducing building energy consumption. Within this context, the study of materials and systems that can merge the advantageous characteristics of both active and passive operating modes has proven particularly attractive. Accordingly, our laboratory has drawn inspiration from the appearance-changing skin of Loliginidae (inshore squids) for the introduction of a unique class of dynamic thermoregulatory composite materials with outstanding figures of merit. Herein, we demonstrate a straightforward approach for experimentally controlling and computationally predicting the adaptive infrared properties of such bioinspired composites, thereby enabling the development and validation of robust structure–function relationships for the composites. Our findings may help unlock the potential of not only the described materials but also comparable systems for applications as varied as thermoregulatory wearables, food packaging, infrared camouflage, soft robotics, and biomedical sensing.
Purpose: To compare and analyze two novel algorithms for the assessment of modulation transfer functions (MTFs) of computed tomography (CT) systems using a simple acrylic cylindrical phantom Method and Materials: Images of the acrylic cylindrical phantom were acquired by a GE LightSpeed 16 RT (GE Healthcare, Milwaukee, WI) using 120 kVp, 330 mA, 2.5 mm slice thickness, 10 cm field-of view (FOV), four reconstruction kernels (e.g. standard, soft, detail, bone, and lung). Two different algorithms were used to analyze images for MTF assessment. First, Richard et al. suggested a task-based MTF assessment method through an edge spread function (ESF) which described pixel intensities as a function of distance from the center. The MTF was obtained as the absolute value of Fourier transform of the differentiated ESF. Second, Ohkubo et al. devised an effective method to determine the point spread function (PSF) of CT system accompanied with verification. The line spread function (LSF), which was the one-dimensional integration of the PSF, was used to obtain the MTF. We validated the reliability of two above-mentioned methods through the comparison with a conventional method using a thin tungsten wire phantom. Results: The measured MTFs by two methods were mostly similar each other for standard, soft, and detail kernels. In 0.6 lp/mm, the MTF difference between two methods were 0.012(standard), 0.004(soft), and 0.037(detail). They also coincided with the MTF by the conventional method well. However, there were considerable distinctions for bone and lung kernels containing edge enhancement that might cause undershoots near the peak of the LSF. Conclusions: We compared two novel methods to assess task-based MTFs for clinical CT systems especially using a simple acrylic cylindrical phantom with high-convenience and low-cost, and validated them against a conventional method. This work can provide a practical solution to users for the quality assurance of CT.
Narrow-line Seyfert 1 galaxies (NLS1s) with very small broadline widths (say, FWHM(H{beta}) {approx}<1200 km s{sup -1}) represent the extreme type of Seyfert 1 galaxies that have small black hole masses (M{sub BH}) and/or high Eddington ratios (L/L{sub Edd}). Here, we study the X-ray properties of a homogeneously and optically selected sample of 13 such objects, termed as very narrow line Seyfert 1 galaxies, using archival XMM-Newton data. It is found that the Fe K{alpha} emission line is at most weak in these objects. A soft X-ray excess is ubiquitous, with the thermal temperatures falling within a strict range of 0.1-0.2 keV. Our result highlights the puzzling independence of the thermal temperature by extending the relations to even smaller FWHM(H{beta}), i.e., smaller M{sub BH} ({approx}10{sup 6} M{sub sun}) and/or higher L/L{sub Edd}. The excess emission can be modeled by a range of viable models, though the disk reflection and Comptonization models generally give somewhat better fits over the smeared absorption and the p-free models. At the Eddington ratios around unity and above, the X-ray spectral slopes in the 2-10 keV band are systematically flatter than the predictions of the relationship with L/L{sub Edd} suggested previously. Short timescale (1-2 hr) X-ray variability is common, which, together with the variability amplitude computed for some of the objects, is supportive of the scenario that NLS1s are indeed active galactic nuclei with relatively small M{sub BH}.
Purpose: The lack of electron density information in magnetic resonance images (MRI) poses a major challenge for MRI-based radiotherapy treatment planning (RTP). In this study the authors convert MRI intensity values into Hounsfield units (HUs) in the male pelvis and thus enable accurate MRI-based RTP for prostate cancer patients with varying tissue anatomy and body fat contents. Methods: T{sub 1}/T{sub 2}*-weighted MRI intensity values and standard computed tomography (CT) image HUs in the male pelvis were analyzed using image data of 10 prostate cancer patients. The collected data were utilized to generate a dual model HU conversion technique from MRI intensity values of the single image set separately within and outside of contoured pelvic bones. Within the bone segment local MRI intensity values were converted to HUs by applying a second-order polynomial model. This model was tuned for each patient by two patient-specific adjustments: MR signal normalization to correct shifts in absolute intensity level and application of a cutoff value to accurately represent low density bony tissue HUs. For soft tissues, such as fat and muscle, located outside of the bone contours, a threshold-based segmentation method without requirements for any patient-specific adjustments was introduced to convert MRI intensity values into HUs. The dual model HU conversion technique was implemented by constructing pseudo-CT images for 10 other prostate cancer patients. The feasibility of these images for RTP was evaluated by comparing HUs in the generated pseudo-CT images with those in standard CT images, and by determining deviations in MRI-based dose distributions compared to those in CT images with 7-field intensity modulated radiation therapy (IMRT) with the anisotropic analytical algorithm and 360° volumetric-modulated arc therapy (VMAT) with the Voxel Monte Carlo algorithm. Results: The average HU differences between the constructed pseudo-CT images and standard CT images of each test patient ranged from −2 to 5 HUs and from 22 to 78 HUs in soft and bony tissues, respectively. The average local absolute value differences were 11 HUs in soft tissues and 99 HUs in bones. The planning target volume doses (volumes 95%, 50%, 5%) in the pseudo-CT images were within 0.8% compared to those in CT images in all of the 20 treatment plans. The average deviation was 0.3%. With all the test patients over 94% (IMRT) and 92% (VMAT) of dose points within body (lower than 10% of maximum dose suppressed) passed the 1 mm and 1% 2D gamma index criterion. The statistical tests (t- and F-tests) showed significantly improved (p ≤ 0.05) HU and dose calculation accuracies with the soft tissue conversion method instead of homogeneous representation of these tissues in MRI-based RTP images. Conclusions: This study indicates that it is possible to construct high quality pseudo-CT images by converting the intensity values of a single MRI series into HUs in the male pelvis, and to use these images for accurate MRI-based prostate RTP dose calculations.
Microelectromechanical systems remain an area of significant interest in fundamental and applied research due to their wide ranging applications. Most device designs, however, are largely 2D and constrained to only a few simple geometries. Achieving tunable resonant frequencies or broad operational bandwidths requires complex components and/or fabrication processes. The work presented here reports unusual classes of 3D micromechanical systems in the form of vibratory platforms assembled by controlled compressive buckling. Such 3D structures can be fabricated across a broad range of length scales and from various materials, including soft polymers, monocrystalline silicon, and their composites, resulting in a wide scope of achievable resonant frequencies and mechanical behaviors. Platforms designed with multistable mechanical responses and vibrationally decoupled constituent elements offer improved bandwidth and frequency tunability. Furthermore, the resonant frequencies can be controlled through deformations of an underlying elastomeric substrate. Systematic experimental and computational studies include structures with diverse geometries, ranging from tables, cages, rings, ring-crosses, ring-disks, two-floor ribbons, flowers, umbrellas, triple-cantilever platforms, and asymmetric circular helices, to multilayer constructions. These concepts form the foundations for engineering designs that complement those supported by conventional, micro-electromechanical systems, with capabilities that could be useful in systems for biosensing, energy harvesting, and others.
Viscoplastic deformation of shale is frequently observed in many subsurface applications. Many studies have suggested that this viscoplastic behavior is anisotropic—specifically, transversely isotropic—and closely linked to the layered composite structure at the microscale. In this work, we develop a two-scale constitutive model for shale in which anisotropic viscoplastic behavior naturally emerges from semianalytical homogenization of a bilayer microstructure. The microstructure is modeled as a composite of soft layers, representing a ductile matrix formed by clay and organics, and hard layers, corresponding to a brittle matrix composed of stiff minerals. This layered microstructure renders the macroscopic behavior anisotropic, even when the individual layers are modeled with isotropic constitutive laws. Using a common correlation between clay and organic content and magnitude of creep, we apply a viscoplastic modified Cam-Clay plasticity model to the soft layers, while treating the hard layers as a linear elastic material to minimize the number of calibration parameters. We then describe the implementation of the proposed model in a standard material update subroutine. The model is validated with laboratory creep data on samples from three gas shale formations. We also demonstrate the computational behavior of the proposed model through simulation of time-dependent borehole closure in a shale formation with different bedding plane directions.
Soft gravitons produced by the expansion of de Sitter can be viewed as the Nambu-Goldstone bosons of spontaneously broken asymptotic symmetries of the de Sitter spacetime. We explicitly construct the associated charges, and show that acting with the charges on the vacuum creates a new state equivalent to a change in the local coordinates induced by the soft graviton. While the effect remains unobservable within the domain of a single observer where the symmetry is unbroken, this change is physical when comparing different asymptotic observers, or between a transformed and un-transformed initial state, consistent with the scale-dependent statistical anisotropies previously derived using semiclassical relations. We then compute the overlap, (0| 0'), between the unperturbed de Sitter vacuum |0), and the state | 0') obtained by acting N times with the charge. We show that when N→ M {sub p} {sup 2}/ H {sup 2} this overlap receives order one corrections and 0(0| 0')→ , which corresponds to an infrared perturbative breakdown after a time t {sub dS} ∼ M {sub p} {sup 2}/ H {sup 3} has elapsed, consistent with earlier arguments in the literature arguing for a perturbative breakdown on this timescale. We also discuss the generalization to inflation, and rederive the 3-point and one-loop consistency relations.
Through-section residual stresses in an asymmetric, thin-walled tapered bearing component were non-destructively studied via neutron diffraction after soft machining, heat treatment and hard turning. Two-dimensional area maps revealed non-uniform distributions of stress fields in both the thinnest and thickest sections of the component, indicating that the entire processing sequence plays a vital role — not only in distortion, but in the final stress state as well. Here, a computational model was developed to further understand the extent of the distortion induced in bearing components as a result of process variables in the manufacturing sequence.
Purpose: To correlate computed tomography (CT) imaging features of spinal metastases with pain relief after radiotherapy (RT). Methods and Materials: Thirty-three patients receiving computed tomography (CT)-simulated RT for spinal metastases in an outpatient palliative RT clinic from January 2007 to October 2008 were retrospectively reviewed. Forty spinal metastases were evaluated. Pain response was rated using the International Bone Metastases Consensus Working Party endpoints. Three musculoskeletal radiologists and two orthopaedic surgeons evaluated CT features, including osseous and soft tissue tumor extent, presence of a pathologic fracture, severity of vertebral height loss, and presence of kyphosis. Results: The mean patient age was 69 years; 24 were men and 9 were women. The mean worst pain score was 7/10, and the mean total daily oral morphine equivalent was 77.3 mg. Treatment doses included 8 Gy in one fraction (22/33), 20 Gy in five fractions (10/33), and 20 Gy in eight fractions (1/33). The CT imaging appearance of spinal metastases included vertebral body involvement (40/40), pedicle involvement (23/40), and lamina involvement (18/40). Soft tissue component (10/40) and nerve root compression (9/40) were less common. Pathologic fractures existed in 11/40 lesions, with resultant vertebral body height loss in 10/40 and kyphosis in 2/40 lesions. At months 1, 2, and 3 after RT, 18%, 69%, and 70% of patients experienced pain relief. Pain response was observed with various CT imaging features. Conclusions: Pain response after RT did not differ in patients with and without pathologic fracture, kyphosis, or any other CT features related to extent of tumor involvement. All patients with painful spinal metastases may benefit from palliative RT.
In the Alcator C-Mod tokamak, relativistic runaway electron (RE) generation can occur during the flattop current phase of low density, diverted plasma discharges. Due to the high toroidal magnetic field (B0 = 5.4 T), RE synchrotron radiation is measured by a wide-view camera in the visible wavelength range (~400-900 nm). In this paper, a statistical analysis of over one thousand camera images is performed to investigate the plasma conditions under which synchrotron emission is observed in C-Mod. In addition, the spatiotemporal evolution of REs during one particular discharge is explored in detail via a thorough analysis of the distortion-corrected synchrotron images. To accurately predict RE energies, the kinetic solver CODE [Landreman et al 2014 Comput. Phys. Commun. 185 847-855] is used to evolve the electron momentum-space distribution at six locations throughout the plasma: the magnetic axis and flux surfaces q = 1, 4/3, 3/2, 2, and 3. These results, along with the experimentally-measured magnetic topology and camera geometry, are input into the synthetic diagnostic SOFT [Hoppe et al 2018 Nucl. Fusion 58 026032] to simulate synchrotron emission and detection. Interesting spatial structure near the surface q = 2 is found to coincide with the onset of a locked mode and increased MHD activity. Furthermore, the RE density profile evolution is fit by comparing experimental to synthetic images, providing important insight into RE spatiotemporal dynamics.
Understanding the role of oxygen vacancy–induced atomic and electronic structural changes to complex metal oxides during water-splitting processes is paramount to advancing the field of solar thermochemical hydrogen production (STCH). The formulation and confirmation of a mechanism for these types of chemical reactions necessitate a multifaceted experimental approach, featuring advanced structural characterization methods. Synchrotron X-ray techniques are essential to the rapidly advancing field of STCH in part due to properties such as high brilliance, high coherence, and variable energy that provide sensitivity, resolution, and rapid data acquisition times required for the characterization of complex metal oxides during water-splitting cycles. X-ray diffraction (XRD) is commonly used for determining the structures and phase purity of new materials synthesized by solid-state techniques and monitoring the structural integrity of oxides during water-splitting processes (e.g., oxygen vacancy–induced lattice expansion). X-ray absorption spectroscopy (XAS) is an element-specific technique and is sensitive to local atomic and electronic changes encountered around metal coordination centers during redox. While in operando measurements are desirable, the experimental conditions required for such measurements (high temperatures, controlled oxygen partial pressures, and H 2 O) practically necessitate in situ measurements that do not meet all operating conditions or ex situ measurements. Here, we highlight the application of synchrotron X-ray scattering and spectroscopic techniques using both in situ and ex situ measurements, emphasizing the advantages and limitations of each method as they relate to water-splitting processes. The best practices are discussed for preparing quenched states of reduction and performing synchrotron measurements, which focus on XRD and XAS at soft (e.g., oxygen K-edge, transition metal L-edges, and lanthanide M-edges) and hard (e.g., transition metal K-edges and lanthanide L-edges) X-ray energies. The X-ray absorption spectra of these complex oxides are a convolution of multiple contributions with accurate interpretation being contingent on computational methods. The state-of-the-art methods are discussed that enable peak positions and intensities to be related to material electronic and structural properties. Through careful experimental design, these studies can elucidate complex structure–property relationships as they pertain to nonstoichiometric water splitting. A survey of modern approaches for the evaluation of water-splitting materials at synchrotron sources under various experimental conditions is provided, and available software for data analysis is discussed.