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At least 667 records · Page 37

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗

On forced RF generation of CW magnetrons for accelerators

CW magnetrons, initially developed for industrial RF heaters, were suggested to power RF cavities of superconducting accelerators due to their higher efficiency and lower cost than traditionally used klystrons, IOTs or solid-state amplifiers. RF amplifiers driven by a master oscillator serve as coherent RF sources. CW magnetrons are regenerative RF generators with a huge regenerative gain. This causes regenerative instability with a quite large noise when a magnetron operates with the anode voltage above the threshold of self-excitation. Traditionally, an injection locking by a small signal is used for stabilization of magnetrons. In this case CW magnetrons with the injection-locked oscillations generate a high level of noise. This may preclude use of standard CW magnetrons in this operating mode in the Superconducting RF (SRF) accelerators. In this article we described a method developed for forced RF generation of CW magnetrons when the magnetron startup is provided by the injected forcing signal and the regenerative noise is suppressed. The method is most suitable for powering high Q-factor cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Annual Performance of the Second-Generation Variable-Geometry Oscillating Surge Wave Energy Converter

Recent studies in wave energy have highlighted the need for a structured innovation approach in wave energy converter (WEC) design because cost-of-energy estimates have remained high. One specific innovation being investigated by the National Renewable Energy Laboratory is WEC geometry control, which uses control surfaces in combination with an oscillating surge WEC (OSWEC) to increase device availability and power generation while limiting structural costs. This study performs the first analysis of annual performance for a novel OSWEC with geometry control to understand how the geometry control affects availability, annual power generation, and structural loadings like the power-take-off (PTO) torque or surge foundation force. Device hydrodynamic coefficients are calculated using linear potential theory for six geometry configurations. A nonideal PTO system is assumed and quadratic viscous damping losses are considered. Annual performance is evaluated and compared for three U.S. wave energy sites. The WEC geometry and PTO system are controlled on a sea-state basis to optimize for power capture while remaining under limits set on motion amplitude and structural loads. Results indicate that geometry control can increase availability up to 25 days in an average year depending on design limits, increase average power generation, and significantly reduce peak structural loads.

30 DIRECT ENERGY CONVERSION↗

A Review of Behind-the-Meter Solar Generation Modeling and Forecasting

Solar photovoltaic systems largely integrated within the distribution grid are operated 'behind-the-meter' and power generation cannot be directly monitored by most utilities. The increasing penetration of behind-the-meter solar photovoltaic systems can deter efficient network and market operations due to variability and uncertainty in net load, which is exacerbated by limited visibility and the difficulty in analyzing the hosting capacity. Risk introduced by behind-the-meter solar contributions may hinder reliable and secure grid operations due to biased system monitoring and forecasts. Accurate behind-the-meter estimations, together with capacity and specification forecasts, thus play a key role in balancing supply and demand and this article reviews the pertinent literature, identifying key characteristics and predictive methods for efficient behind-the-meter solar photovoltaic generation. Forecasting is central to methods herein. The fundamental characteristics of behind-the-meter solar forecasting, including which methods are applicable for scenario-driven use cases, are driven by the metrics most useful for system-wide performance evaluation. To this aim, the literature is reviewed with a focus on forecasting applications for aggregate, regional behind-the-meter generation useful to bulk system and utility operations. As distinguished from net load forecasting, subtleties in these coincident tasks are explored before concluding with recommendations for current practice and future implementations.

behind-the-meter↗

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗

Noninvasive liquid level sensing with laser generated ultrasonic waves

This article proposes a noninvasive liquid level sensing technique using laser-generated ultrasound waves for nuclear power plant applications. Liquid level sensors play an important role of managing the coolant system safely and stably in the plant structure. Current sensing techniques are mostly intrusive, performing inside the fluidic structure, which is disadvantageous in terms of the regular maintenance of the plant system. Furthermore, typical intrusive sensors do not perform stably under varying environmental conditions such as temperature and radiation. In this study, sensing units are attached to the outer surface of a liquid vessel to capture guided ultrasound waves in a nonintrusive manner. The signal intensity of the guided wave dissipates when the signal interacts with the internal liquid media. The sensing mechanism is mathematically expressed as an index value to correlate the liquid level with the sensor signal. For the acoustic wave generation, laser-generated ultrasound was adopted instead of using typical contact type transducers. Following the simulation validation of the proposed concept, the performance of the developed sensor was confirmed through experimental results under elevated liquid temperature conditions. Finally, the nonlinear multivariable regression exhibited the best-fit to the datasets measured under the variable liquid level and temperature conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multi-octave-spanning supercontinuum generation through high-energy laser filaments in YAG and ZnSe pumped by a 2.4 μm femtosecond Cr:ZnSe laser

Abstract We present experimental and numerical investigations of high-energy mid-infrared filamentation with multi-octave-spanning supercontinuum generation (SCG), pumped by a 2.4 μm, 250 fs Cr:ZnSe chirped-pulse laser amplifier. The SCG is demonstrated in both anomalous and normal dispersion regimes with YAG and polycrystalline ZnSe, respectively. The formation of stable and robust single filaments along with the visible-to-mid-infrared SCG is obtained with a pump energy of up to 100 μJ in a 6-mm-long YAG medium. To the best of the authors’ knowledge, this is the highest-energy multi-octave-spanning SCG from a laser filament in a solid. On the other hand, the SCG and even-harmonic generation based on random quasi-phase matching (RQPM) are simultaneously observed from the single filaments in a 6-mm-long polycrystalline ZnSe medium with a pump energy of up to 15 μJ. The numerical simulations based on unidirectional pulse propagation equation and RQPM show excellent agreement with the measured multi-octave-spanning SCG and even-harmonic generation. They also reveal the temporal structure of mid-infrared filaments, such as soliton-like self-compression in YAG and pulse broadening in ZnSe.

Optics↗

A theoretical study of the upper bound of surface elevation variance in the Phillips initial stage during wind-wave generation

The resonance mechanism in the initial of wind-wave generation proposed by Phillips is a foundation of wind-wave generation theory, but a precise theoretical quantification of wave energy growth in this initial stage has not been obtained yet after more than six decades of research. In this study, we aim to address this knowledge gap by developing an analytical approach based on a novel complex analysis method to theoretically investigate the temporal evolution of the wave energy in the Phillips initial stage. We quantitatively derive and analyse the growth behaviour of the surface wave energy and obtain an analytical solution for its upper bound. Our result highlights the crucial effects of surface tension. Because the phase velocity of gravity–capillary waves has a minimal value at a critical wavenumber, gravity–capillary waves and gravity waves (which neglect surface tension) exhibit distinct resonance curve properties and wave energy growth behaviours. For gravity waves, the resonance curve extends indefinitely; for gravity–capillary waves, it either forms a finite-length curve or does not exist, depending on the wind speed. The leading-order term of the upper-bound solution of the energy of gravity waves increases linearly over time, while for gravity–capillary waves, the term increases linearly over time under strong wind conditions but remains finite under weak wind conditions. This theoretical study provides an analytical framework for the generation of wind-waves in the Phillips initial stage, which may inspire further theoretical, numerical and experimental research.

58 GEOSCIENCES↗

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions↗

Generation of Tin-Vacancy Centers in Diamond via Shallow Ion Implantation and Subsequent Diamond Overgrowth

Group IV color centers in diamond have garnered great interest for their potential as optically active solid-state spin qubits. The future utilization of such emitters requires the development of precise site-controlled emitter generation techniques that are compatible with high-quality nanophotonic devices. This task is more challenging for color centers with large group IV impurity atoms, which are otherwise promising because of their predicted long spin coherence times without a dilution refrigerator. For example, when applied to the negatively charged tin-vacancy (SnV – ) center, conventional site-controlled color center generation methods either damage the diamond surface or yield bulk spectra with unexplained features. Here we demonstrate a novel method to generate site-controlled SnV – centers with clean bulk spectra. We shallowly implant Sn ions through a thin implantation mask and subsequently grow a layer of diamond via chemical vapor deposition. This method can be extended to other color centers and integrated with quantum nanophotonic device fabrication.

36 MATERIALS SCIENCE↗

Unraveling Nonequilibrium Generation of Atomic Nitrogen and Hydrogen in Plasma-Aided Ammonia Synthesis

In this study, nonequilibrium generation of atomic nitrogen and hydrogen governing ammonia production both in the gas phase and on the catalyst surface is critical to plasma-aided ammonia synthesis. Here, this work studies the nonequilibrium generation of atomic nitrogen and hydrogen with a focus on the kinetic role of vibrational energy transfer of hydrogen molecules in plasma-aided ammonia synthesis. By combining two-photon absorption laser-induced fluorescence measurements and plasma kinetic modeling, we found that plasma not only generates ammonia but also produces critical H, N, and NH radicals via both electron impact and vibrational energy transfer excitations. The vibrational energy transfer from the excited hydrogen H 2 (v = 1) to higher vibrational levels H 2 (v = 2–3) via the V–V exchange (H 2 (v)–H 2 (v)) and V–V' exchange (N 2 (v)–H 2 (v)) significantly enhances the H and NH production and then promotes the coupling between N and NH for ammonia synthesis both in the gas phase and on the catalyst surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemically Generated Liquid Sulfur Droplets at Room and Subzero Temperatures

The liquid phase of sulfur has been observed at room temperature, resulting from the electrochemical oxidation of polysulfides, a process occurring on the electrodes and influenced by the electrode materials. However, such electrode-dependent behavior of liquid sulfur has constrained its use in battery applications, driving research for alternative processes. This paper introduces an approach to generating liquid sulfur at both room and subzero temperatures through chemical reactions independent of the substrate material. We demonstrate that using a redox mediator, polysulfides can be chemically oxidized into liquid sulfur droplets in the electrolyte close to but away from the electrode. This pathway can generate liquid sulfur at room and subzero temperatures of −15 °C, 130 °C below sulfur’s melting temperature (115 °C). The chemically generated liquid sulfur further enriches the lithium–sulfur-electrolyte material systems, potentially creating opportunities for high-energy lithium–sulfur and other metal–sulfur batteries.

liquid sulfur↗

Assessing Clouds Using Satellite Observations Through Three Generations of Global Atmosphere Models

Abstract Clouds are parameterized in climate models using quantities on the model grid‐scale to approximate the cloud cover and impact on radiation. Because of the complexity of processes involved with clouds, these parameterizations are one of the key challenges in climate modeling. Differences in parameterizations of clouds are among the main contributors to the spread in climate sensitivity across models. In this work, the clouds in three generations of an atmosphere model lineage are evaluated against satellite observations. Satellite simulators are used within the model to provide an appropriate comparison with individual satellite products. In some respects, especially the top‐of‐atmosphere cloud radiative effect, the models show generational improvements. The most recent generation, represented by two distinct branches of development, exhibits some regional regressions in the cloud representation; in particular the southern ocean shows a positive bias in cloud cover. The two branches of model development show how choices during model development, both structural and parametric, lead to different cloud climatologies. Several evaluation strategies are used to quantify the spatial errors in terms of the large‐scale circulation and the cloud structure. The Earth mover's distance is proposed as a useful error metric for the passive satellite data products that provide cloud‐top pressure‐optical depth histograms. The cloud errors identified here may contribute to the high climate sensitivity in the Community Earth System Model, version 2 and in the Energy Exascale Earth System Model, version 1.

54 ENVIRONMENTAL SCIENCES↗

Two-colour dissipative solitons and breathers in microresonator second-harmonic generation

Frequency conversion of dissipative solitons associated with the generation of broadband optical frequency combs having a tooth spacing of hundreds of giga-hertz is a topical challenge holding the key to practical applications in precision spectroscopy and data processing. The work in this direction is underpinned by fundamental problems in nonlinear and quantum optics. Here, we present the dissipative two-colour bright-bright and dark-dark solitons in a quasi-phase-matched microresonator pumped for the second-harmonic generation in the near-infrared spectral range. We also found the breather states associated with the pulse front motion and collisions. The soliton regime is found to be typical in slightly phase-mismatched resonators, while the phase-matched ones reveal broader but incoherent spectra and higher-order harmonic generation. Soliton and breather effects reported here exist for the negative tilt of the resonance line, which is possible only via the dominant contribution of second-order nonlinearity.

42 ENGINEERING↗

Twisted moiré photonic crystal enabled optical vortex generation through bound states in the continuum

The twisted stacking of two layered crystals has led to the emerging moiré physics as well as intriguing chiral phenomena such as chiral phonon and photon generation. In this work, we identified and theoretically formulated a non-trivial twist-enabled coupling mechanism in twisted bilayer photonic crystal (TBPC), which connects the bound state in the continuum (BIC) mode to the free space through the twist-enabled channel. Moreover, the radiation from TBPC hosts an optical vortex in the far field with both odd and even topological orders. We quantitatively analyzed the twist-enabled coupling between the BIC mode and other non-local modes in the photonic crystals, giving rise to radiation carrying orbital angular momentum. The optical vortex generation is robust against geometric disturbance, making TBPC a promising platform for well-defined vortex generation. As a result, TBPCs not only provide a new approach to manipulating the angular momentum of photons, but may also enable novel applications in integrated optical information processing and optical tweezers. Our work broadens the field of moiré photonics and paves the way toward the novel application of moiré physics.

42 ENGINEERING↗

The interplay of DNA repair context with target sequence predictably biases Cas9-generated mutations

Abstract Repair of double-stranded breaks generated by CRISPR/Cas9 is highly dependent on the flanking DNA sequence. To learn about interactions between DNA repair and target sequence, we measure frequencies of over 236,000 distinct Cas9-generated mutational outcomes at over 2800 synthetic target sequences in 18 DNA repair deficient mouse embryonic stem cells lines. We classify the outcomes in an unbiased way, finding a specialised role forPrkdc(DNA-PKcs protein) andPolmin creating 1 bp insertions matching the nucleotide on the protospacer-adjacent motif side of the break, a variable involvement ofNbnandPolqin the creation of different deletion outcomes, and uni-directional deletions dependent on both end-protection and end-resection. Using our dataset, we build predictive models of the mutagenic outcomes of Cas9 scission that outperform the current standards. This work improves our understanding of DNA repair gene function, and provides avenues for more precise modulation of Cas9-generated mutations.

Science & Technology - Other Topics↗

Milliwatt-level UV generation using sidewall poled lithium niobate

Integrated coherent sources of ultra-violet (UV) light are essential for a wide range of applications, from ion-based quantum computing and optical clocks to gas sensing and microscopy. Recently, approaches that use frequency upconversion have received considerable attention. Among these, the integrated thin-film lithium niobate (TFLN) photonic platform shows particular promise. However, to date, the high propagation losses and lack of reliable techniques for consistent poling of cm-long waveguides with small poling periods have impeded progress. Here, we present a sidewall poled lithium niobate (SPLN) waveguide approach that overcomes these obstacles and results in a two-orders-of-magnitude increase in generated UV power. We demonstrate SPLN waveguides featuring record-low propagation losses of 2.3 dB/cm, complete domain inversion across the waveguide cross-section, and an optimum 50% duty cycle, resulting in a record-high normalized conversion efficiency of 5050%W$^{−1}$cm$^{−2}$, and 4.2 mW of generated on-chip power at 390 nm wavelength. This advancement makes the TFLN platform a viable option for high-quality on-chip UV generation, benefiting emerging applications.

Franken, C. A.A. [Harvard U.; Twente U., Enschede]↗