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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ampere-level co-electrosynthesis of formate from CO 2 reduction paired with formaldehyde dehydrogenation reactions

Current catalysts face challenges with low formate selectivity at high current densities during the CO 2 electroreduction. Here, we showcase a versatile strategy to enhance the formate production on p-block metal-based catalysts by incorporating noble metal atoms on their surface, refining oxygen affinity, and tuning adsorption of the critical oxygen-bound *OCHO intermediate. The formate yield is observed to afford a volcano-like dependence on the *OCHO binding strength across a series of modified catalysts. The rhodium-dispersed indium oxide (Rh/In 2 O 3 ) catalyst exhibits impressive performances, achieving Faradaic efficiencies (FEs) of formate exceeding 90% across a broad current density range of 0.20 to 1.21 A cm −2 . In situ Raman spectroscopy and theoretical calculations reveal that the oxophilic Rh site facilitates *OCHO formation by optimizing its adsorption energy, placing Rh/In 2 O 3 near the volcano-shaped apex. A bipolar electrosynthesis system, coupling the CO 2 reduction at the cathode with the formaldehyde oxidative dehydrogenation at the anode, further boosts the FE of formate to nearly 190% with pure hydrogen generation under an ampere-level current density and a low cell voltage of 2.5 V in a membrane electrode assembly cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Towards isolated attosecond electron bunches using ultrashort-pulse laser-solid interactions

We investigate MeV-level attosecond electron bunches from ultrashort-pulse laser-solid interactions through similarities between experimental and simulated electron energy spectra. We show measurements of the bunch duration and temporal structure from particle-in-cell simulations. The experimental observation of such bunches favors specular reflection direction when focusing the laser pulse onto a subwavelength boundary of thick overdense plasmas at grazing incidence. Particle-in-cell simulation further reveals that the attosecond duration is a result of ultra-thin (~tenth of a micron) gaps of zero electromagnetic energy density in the modulated reflected radiation, while the bunching (locally peaked electron concentration) comes from the highly-directional electron angular distribution acquired by the electrons in a grazing incidence setup. To isolate a single electron bunch, we perform simulations using 1-cycle laser pulses and analyze the effect of carrier-envelop phase with particle tracking. The duration of the electron bunch can be further decreased by increasing the laser intensity and the focal spot size, while its direction can be changed by tuning the preplasma density gradient.

High-harmonic generation↗
DOE OSTI2021

Metastable Dion-Jacobson 2D structure enables efficient and stable perovskite solar cells

The performance of three-dimensional (3D) organic-inorganic halide perovskite solar cells (PSCs) can be enhanced through surface treatment with 2D layered perovskites that have efficient charge transport. We maximized hole transport across the layers of a metastable Dion-Jacobson (DJ) 2D perovskite that tuned the orientational arrangements of asymmetric bulky organic molecules. The reduced energy barrier for hole transport increased out-of-plane transport rates by a factor of 4 to 5, and the power conversion efficiency (PCE) for the 2D PSC was 4.9%. With the metastable DJ 2D surface layer, the PCE of three common 3D PSCs was enhanced by approximately 12 to 16% and could reach approximately 24.7%. For a triple-cation–mixed-halide PSC, 90% of the initial PCE was retained after 1000 hours of 1-sun operation at ~40°C in nitrogen.

14 SOLAR ENERGY↗
DOE OSTI2021

Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach

Neuromorphic systems allow for extremely efficient hardware implementations for neural networks (NNs). In recent years, several algorithms have been presented to train spiking NNs (SNNs) for neuromorphic hardware. However, SNNs often provide lower accuracy than their artificial NNs (ANNs) counterparts or require computationally expensive and slow training/inference methods. To close this gap, designers typically rely on reconfiguring SNNs through adjustments in the neuron/synapse model or training algorithm itself. Nevertheless, these steps incur significant design time, while still lacking the desired improvement in terms of training/inference times (latency). Designing SNNs that can mimic the accuracy of ANNs with reasonable training times is an exigent challenge in neuromorphic computing. In this work, we present an alternative approach that looks at such designs as an optimization problem rather than algorithm or architecture redesign. We develop a versatile multiobjective hyperparameter optimization (HPO) for automatically tuning HPs of two state-of-the-art SNN training algorithms, SLAYER and HYBRID. We emphasize that, to the best of our knowledge, this is the first work trying to improve SNNs’ computational efficiency, accuracy, and training time using an efficient HPO. We demonstrate significant performance improvements for SNNs on several datasets without the need to redesign or invent new training algorithms/architectures. Our approach results in more accurate networks with lower latency and, in turn, higher energy efficiency than previous implementations. In particular, we demonstrate improvement in accuracy and more than 5× reduction in the training/inference time for the SLAYER algorithm on the DVS Gesture dataset. In the case of HYBRID, we demonstrate 30% reduction in timesteps while surpassing the accuracy of the state-of-the-art networks on CIFAR10. Further, our analysis suggests that even a seemingly minor change in HPs could change the accuracy by 5 - 6×.

Parsa, Maryam↗
DOE OSTI2024

Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach

Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage DeepHyper’s advanced search algorithms for multiobjective optimization, streamlining the development of neural networks tailored for ocean modeling. The focus is on optimizing Fourier neural operators (FNOs), a data-driven model capable of simulating complex ocean behaviors. Selecting the correct model and tuning the hyperparameters are challenging tasks, requiring much effort to ensure model accuracy. DeepHyper allows efficient exploration of hyperparameters associated with data preprocessing, FNO architecture-related hyperparameters, and various model training strategies. We aim to obtain an optimal set of hyperparameters leading to the most performant model. Moreover, on top of the commonly used mean squared error for model training, we propose adopting the negative anomaly correlation coefficient as the additional loss term to improve model performance and investigate the potential trade-off between the two terms. The numerical experiments show that the optimal set of hyperparameters enhanced model performance in single timestepping forecasting and greatly exceeded the baseline configuration in the autoregressive rollout for long-horizon forecasting up to 30 days. Utilizing DeepHyper, we demonstrate an approach to enhance the use of FNO in ocean dynamics forecasting, offering a scalable solution with improved precision.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A differentiable, physics-informed ecosystem modeling and learning framework for large-scale inverse problems: demonstration with photosynthesis simulations

Photosynthesis plays an important role in carbon, nitrogen, and water cycles. Ecosystem models for photosynthesis are characterized by many parameters that are obtained from limited in situ measurements and applied to the same plant types. Previous site-by-site calibration approaches could not leverage big data and faced issues like overfitting or parameter non-uniqueness. Here we developed an end-to-end programmatically differentiable (meaning gradients of outputs to variables used in the model can be obtained efficiently and accurately) version of the photosynthesis process representation within the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) model. As a genre of physics-informed machine learning (ML), differentiable models couple physics-based formulations to neural networks (NNs) that learn parameterizations (and potentially processes) from observations, here photosynthesis rates. We first demonstrated that the framework was able to correctly recover multiple assumed parameter values concurrently using synthetic training data. Then, using a real-world dataset consisting of many different plant functional types (PFTs), we learned parameters that performed substantially better and greatly reduced biases compared to literature values. Further, the framework allowed us to gain insights at a large scale. Our results showed that the carboxylation rate at 25 °C (V c,max25 ) was more impactful than a factor representing water limitation, although tuning both was helpful in addressing biases with the default values. This framework could potentially enable substantial improvement in our capability to learn parameters and reduce biases for ecosystem modeling at large scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding Changes in Cloud Simulations from E3SM Version 1 to Version 2

This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (CLUBB), microphysical parameterization (MG2), and deep convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds (Sc) and clouds with optical depth larger than 3.6 over the stratocumulus to cumulus transition regimes, where Shortwave Cloud Radiative Effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning made in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to improved SWCRE and Longwave Cloud Radiative Effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the Southern Ocean (SO). They have a relatively smaller impact on clouds than do the CLUBB and ZM tunings. This study offers additional insights about clouds simulated in E3SMv2 by utilizing multiple data sets and the COSP diagnostic tool as well as through sensitivity tests. The improved understanding will benefit the future E3SM developments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Understanding changes in cloud simulations from E3SM version 1 to version 2

Abstract. This study documents clouds simulated by the Energy Exascale Earth System Model (E3SM) version 2 (E3SMv2) and attempts to understand what causes the model behavior change in clouds relative to E3SMv1. This is done by analyzing the last 30-year (1985–2014) data from the 165-year historical simulations using E3SMv1 and v2 and four sensitivity tests to isolate the impact of changes in model parameter choices in its turbulence, shallow convection, and cloud macrophysics parameterization (Cloud Layers Unified By Binormals, CLUBB); microphysical parameterization (MG2); and deep-convection scheme (ZM), as well as model physics changes in convective triggering. It is shown that E3SMv2 significantly improves the simulation of subtropical coastal stratocumulus clouds and clouds with optical depth larger than 3.6 over the stratocumulus-to-cumulus transition regimes, where the shortwave cloud radiative effect (SWCRE) is also improved, and the Southern Ocean (SO) while seeing an overall slight degradation in low clouds over other tropical and subtropical oceans. The better performance in E3SMv1 over those regions is partially due to error compensation between its simulated optically thin and intermediate low clouds for which E3SMv2 actually improves simulation of optically intermediate low clouds. Sensitivity tests indicate that the changes in low clouds are primarily due to the tuning done in CLUBB. The impact of the ZM tuning is mainly on optically intermediate and thick high clouds, contributing to an improved SWCRE and longwave cloud radiative effect (LWCRE). The impact of the MG2 tuning and the new convective trigger is primarily on the high latitudes and the SO. They have a relatively smaller impact on clouds than CLUBB tuning and ZM tuning do. This study offers additional insights into clouds simulated in E3SMv2 by utilizing multiple data sets and the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) diagnostic tool as well as sensitivity tests. The improved understanding will benefit future E3SM developments.

58 GEOSCIENCES↗
DOE OSTI2026

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Mass–metallicity and star formation rate in galaxies: A complex relation tuned to stellar age

In this work we study the stellar mass–metallicity relation (MZR) of an extended sample of star-forming galaxies in the local Universe and its possible dependence on the star formation rate (SFR). We selected a sample of approximately 195 000 Sloan Digital Sky Survey (SDSS) star-forming galaxies up to z = 0.22 with the aim of analysing the behaviour of the MZR with respect to SFR whilst taking into account the age of their stellar populations. For the first time, with this sample, we obtained aperture corrected oxygen and nitrogen-to-oxygen abundances (O/H and N/O, respectively) and SFR using the empirical prescriptions from the Calar Alto Legacy Integral Field Area (CALIFA) survey. To perform this study we also make use of the stellar mass of the galaxies and the parameter Dn(4000) as a proxy for the age of the stellar population. We derive a robust MZR locus, which is found to be fully consistent with the ‘anchoring’ points of a selected set of well-studied nearby galaxies for which the chemical abundance has been derived using the direct method. We observe a complex relation between MZR and SFR across the whole range of galaxy mass and metallicity, where the slope changes seen in the O/H–SFR plane present a pattern that seems to be tuned to the stellar age of the galaxies, and therefore stellar age has to be taken into account in the stellar mass–metallicity–SFR relation. In order to provide an answer to the question of whether or not the MZR depends on the SFR, it is essential to take into account the age of the stellar populations of galaxies. A strong dependence of the MZR on SFR is observed mainly for star-forming galaxies with strong SFR values and low D n (4000). The youngest galaxies of our SDSS sample show the highest SFR measured for their stellar mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

OC6 Phase Ia: CFD Simulations of the Free-Decay Motion of the DeepCwind Semisubmersible

Currently, the design of floating offshore wind systems is primarily based on mid-fidelity models with empirical drag forces. The tuning of the model coefficients requires data from either experiments or high-fidelity simulations. As part of the OC6 (Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is a project under the International Energy Agency Wind Task 30 framework) project, the present investigation explores the latter option. A verification and validation study of computational fluid dynamics (CFD) models of the DeepCwind semisubmersible undergoing free-decay motion is performed. Several institutions provided CFD results for validation against the OC6 experimental campaign. The objective is to evaluate whether the CFD setups of the participants can provide valid estimates of the hydrodynamic damping coefficients needed by mid-fidelity models. The linear and quadratic damping coefficients and the equivalent damping ratio are chosen as metrics for validation. Large numerical uncertainties are estimated for the linear and quadratic damping coefficients; however, the equivalent damping ratios are more consistently predicted with lower uncertainty. Some difference is observed between the experimental and CFD surge-decay motion, which is caused by mechanical damping not considered in the simulations that likely originated from the mooring setup, including a Coulomb-friction-type force. Overall, the simulations and the experiment show reasonable agreement, thus demonstrating the feasibility of using CFD simulations to tune mid-fidelity models.

17 WIND ENERGY↗
DOE OSTI2021

Effects of Ink Formulation on Construction of Catalyst Layers for High-Performance Polymer Electrolyte Membrane Fuel Cells

Rational design of catalyst layers in a membrane electrode assembly (MEA) is crucial for achieving high-performance polymer electrolyte membrane fuel cells. Establishing a clear understanding of the property (catalyst ink)–structure (catalyst layer)–performance (MEA) relationship lays the foundation for this rational design. Here, a synergistic approach was taken to correlate the ink formulation, the microstructure of catalyst layers, and the resulting MEA performance to establish such a property–structure–performance relationship. The solvent composition (n-PA/H 2 O mixtures) demonstrated a strong influence on the performance of the MEA fabricated with an 830-EW (Aquivion) ionomer, especially polarization losses of cell activation and mass transport. The performance differences were studied in terms of how the solvent composition affects the catalyst/ionomer interface, ionomer network, and pore structure of the resulting catalyst layers. The ionomer aggregates mainly covered the surface of catalyst aggregates acting as oxygen reduction reaction active sites, and the aggregate sizes of the ionomer and catalyst (revealed by ultrasmall angle X-ray scattering and cryo-transmission electron microscopy) were dictated by tuning the solvent composition, which in turn determined the catalyst/ionomer interface (available active sites). In n-PA/H 2 O mixtures with 50~90 wt % H 2 O, the catalyst agglomerates could be effectively broken up into small aggregates, leading to enhanced kinetic activities. The boiling point of the mixed solvents determined the pore structure of ultimate catalyst layers, as evidenced by mercury porosimetry and scanning electron microscopy. For mixed solvents with a higher boiling point, the catalyst–ionomer aggregates in the ink tend to agglomerate during the solvent evaporation process and finally form larger catalyst–ionomer aggregates in the ultimate catalyst layer, resulting in more secondary pores and thus lower mass transport resistance. Both the enlarged catalyst/ionomer interface and appropriate pore structure were achieved with the catalyst layer fabricated from an n-PA/H 2 O mixture with 90 wt % H 2 O, leading to the best MEA performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Measurement of three-dimensional inclusive muon-neutrino charged-current cross sections on argon with the MicroBooNE detector

We report the measurement of the triple-differential cross section d 3 σ/dE vis d cos(θ μ )dP μ for inclusive muon-neutrino charged-current scattering on argon. This measurement utilizes data from 6.4 x 10 20 protons on target of exposure collected using the MicroBooNE liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam with a mean neutrino energy of approximately 0.8 GeV. The mapping from reconstructed kinematics to truth quantities is validated within uncertainties by comparing the distribution of reconstructed hadronic energy in data to that of the model prediction in different muon scattering angle bins after applying a conditional constraint from the muon momentum distribution in data. The success of this validation provides confidence that the energy transfer in the MicroBooNE detector is well-modeled within simulation uncertainties, enabling a reliable unfolding to a triple-differential cross section defined at the nominal neutrino flux over muon momentum, muon scattering angle, and visible neutrino energy. This validation not only supports accurate cross-section extraction, but also establishes a critical foundation for tuning interaction models used in future neutrino oscillation measurements. The unfolded measurement covers an extensive phase space, providing a wealth of information useful for future liquid argon time projection chamber experiments measuring neutrino oscillations. Comparisons against a number of commonly used model predictions are included and their performance in different parts of the available phase-space is discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Role of Alkali-Metal Cations in Electronic Structure and Halide Segregation of Hybrid Perovskites

The ability to control or prevent phase segregation in perovskites is crucial to realizing stable and tunable mixed-halide optoelectronic devices. Here, we systematically examine the impact of alkali-metal-cation (Cs + and K + ) concentration on the band structure, chemical composition, phase segregation, and polycrystalline microstructure on formamidinium-dominated mixed-halide mixed-cation perovskite films. It was found that the incorporation of Cs + and K + cations decreases the work function and the core levels of all components shift toward higher binding energy consistent with n-doping the perovskite film, which facilitates electron transfer to the electron transport layer TiO 2 . A concentration-dependent film structure was observed by X-ray photoemission spectroscopy and grazing incidence wide-angle X-ray scattering where the halides and cations are distributed evenly across perovskite films at low metallic cation concentration (5%). A high metal-cation ratio (20%) leads to halide segregation within the perovskite film and the surface becomes bromide-poor, whereas the bromide and metal cations diffuse more deeply within the film. These differences in electronic properties, element distribution, and film morphology were reflected in the device performance where the power conversion efficiency of low-metallic-cation concentration (5% of Cs + and K + ) perovskite solar cells is ≈5% higher than the high-concentration ones (20%). This study provides valuable chemical and physical insight into the underlying trade-offs in the careful tuning of electrical properties and film structure to optimize multication and mixed-halide hybrid perovskites.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Water as a gas separation membrane

Efficient gas separation membranes are essential for carbon capture, biogas upgrading, and hydrogen purification. Inspired by how plants absorb CO 2 through water, we present a membrane platform that uses liquid water as the selective layer. Hydrophilic sub-100-nm pores stabilize water through strong capillary forces, enabling operation at feed pressures above 72 bar under dry and humid conditions. Selectivity is governed by gas solubility in water, while permeance is tuned by adjusting the water layer thickness. Reducing this thickness below 200 nm yields CO 2 permeances up to 11,600 gas permeation units with CO 2 :N 2 , CO 2 :CH 4 , and CO 2 :H 2 selectivities of 40, 26, and 31, respectively, surpassing the performance of state-of-the-art membranes. Operation is sustained for over a week without water loss, and performance scales using commercially available porous polymer supports under mixed-gas crossflow conditions. Water’s dissolution-based transport avoids saturation and reaction-rate limits, enabling a robust, high-performance, and environmentally benign gas separation platform.

08 HYDROGEN↗
DOE OSTI2021

Mitigating contamination in LSS surveys: a comparison of methods

ABSTRACT Future large-scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogues will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-Cℓ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra, which reduced power spectrum errors from $\Delta \chi ^2_{\rm C_\ell }\simeq 10$ to ≃ 1 in simulated analyses. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Widely tunable, heterogeneously integrated quantum-dot O-band lasers on silicon

Heterogeneously integrated lasers in the O-band are a key component in realizing low-power optical interconnects for data centers and high-performance computing. Quantum-dot-based materials have been particularly appealing for light generation due to their ultralow lasing thresholds, small linewidth enhancement factor, and low sensitivity to reflections. Here, we present widely tunable quantum-dot lasers heterogeneously integrated on silicon-on-insulator substrate. The tuning mechanism is based on Vernier dual-ring geometry, and a 47 nm tuning range with 52 dB side-mode suppression ratio is observed. These parameters show an increase to 52 nm and 58 dB, respectively, when an additional wavelength filter in the form of a Mach–Zehnder interferometer is added to the cavity. The Lorentzian linewidth of the lasers is measured as low as 5.3 kHz.

Malik, Aditya (ORCID:0000000334487577)↗
DOE OSTI2022

Designing a Particle Flow Control Apparatus

Flow control within a particle-based Concentrated Solar Power (CSP) system is essential in determining the heat transfer coefficient, and therefore, the power generation capability of these systems. There are three areas where particle flow control is significant: the receivers, storage tanks, and particle-sCO2 heat exchangers. The focus of this work is on designing a new mechanism to control the flow in the particle-sCO2 heat exchangers due to the simplicity and potential cost savings when compared to the other areas of interest. The goal is for this new design to have quicker response times in terms of particle flowrate than a slide gate or flow control valve, which are designs currently used. The design resembles that of a chuck mechanism within a drill where a rotation of the sleeve elicits movement of the jaws both vertically and horizontally to close the outlet area of the nozzle. Additionally, this design will utilize the current actuator that is already used within these heat exchangers to reduce the complexity of implementation. The jaws are designed to be closed at an angle of 76˚ which is just slightly steeper than the hopper leading to the mechanism. Furthermore, this design can be tuned to limit particle bridging and other particle flow phenomena that result in blockages. The prototypes were 3D printed out of polylactic acid (PLA) and scaled up to 100%, 200%, and 400% to be able to observe the velocity profiles of the mechanism more clearly. Experiments are performed with this prototype to compare the inlet and outlet mass flow rates at different configurations of the jaws. The particles used in these experiments are 0.3mm HSP 40/70 that are commonly used in particle-based CSP systems.

14 SOLAR ENERGY↗