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At least 451 records · Page 25

Long-Term Stability Metrics of Photoelectrochemical Water Splitting

Photoelectrochemical (PEC) water splitting, one of the most promising technologies for clean hydrogen generation, has drawn considerable attention over the past few decades. Achieving simultaneous highly efficient and stable unassisted PEC water splitting has been the “holy grail” in clean and renewable fuel generation. State-of-the-art photoelectrodes have shown relatively high efficiencies (∼10–20%). Still, their stability is limited due to photoelectrode chemical instability, electrolyte resistance, mass transfer issues, and an often unoptimized experimental setup. In this work, we present a framework and a set of protocols for conducting long-term stability experiments and further provide details on several critical factors such as light source calibration, choosing the right counter electrode, the configuration of the PEC cell, and photoelectrode sample preparation.

08 HYDROGEN↗

Radiation Chemistry Research for Improved Nuclear Fuel Cycles

Nuclear energy is a key component of a global, low-carbon energy future. One of the challenges facing large-scale deployment of nuclear power is the long-term disposition of used nuclear fuel. Due to the political and technical challenges of siting deep geologic storage facilities, reprocessing of used nuclear fuel is desirable to reduce the total volume and decay heat of waste requiring long-term storage, enabling efficient usage of geologic storage repositories. However nuclear fuel reprocessing is complicated by intense multi-component radiation fields that degrade solvent systems that are used for this purpose. Resulting radiolytic degradation can result in reduced performance over time, and generation of additional waste. Thus, an understanding of the radiation-induced chemistry of these reprocessing solvent systems is crucial to for the development of new, radiation-resistant processes for efficiently treating used nuclear fuel. Controlled irradiation experiments combined with high-performance chromatography and mass spectrometry have provided comprehensive knowledge of radiolytic degradation pathways and kinetics, which is needed to predict the effect of radiation-induced chemistry on the performance of the nuclear fuel reprocessing technology. This talk will give an overview of recent progress in research on the radiation chemistry of fuel reprocessing molecules conducted by the Idaho National Laboratory Center for Radiation Chemistry Research (CR2) in conjunction with the Molecular Mass Spectrometry and Chromatography group.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Operation Optimization Using Reinforcement Learning with Integrated Artificial Reasoning Framework

In large and complex systems, operational decision-making requires a systematic analysis with a vast amount of data from both process parameters and component status monitoring. In this paper, we present an integrated artificial reasoning approach for system state transition models that can help operational decision-making with explainable and traceable reasoning. The integrated artificial reasoning framework is a physics-based approach of defining the system structure in a Bayesian network, so we leveraged it in a Markov decision process (MDP) for finding optimal operational solutions. In our proposed framework, the MDP is implemented on a dynamic Bayesian network (DBN), which represents causalities in a system. The multilevel flow modeling was utilized in order to extract these causalities in a more efficient and objective manner. Since multilevel flow modeling is based on the fundamental energy and mass conservation laws, the target system is decomposed into several mass, energy, and information structures, which serve as the basis for a DBN. The MDP consists of the processes of finding a solution for the Bellman equation, which can be derived from the conditional probability equations of the constructed DBN. System operators can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from the component degradation process or random failures. We analyzed a simplified example system to illustrate finding an optimal operational policy with this approach.

Kim, Junyung↗

Material Failure Mechanisms of Alkaline Zn Rechargeable Conversion Electrodes

Zinc (Zn) alkaline electrodes hold great importance and promise in the battery technology community, yet their behavior in real-world applications is still poorly understood. Here, we report a study of failure mechanisms and material evolution during cycling of 27 zinc–manganese dioxide (Zn–MnO 2 ) cells wherein the percent utilization of the Zn electroactive material is systematically varied between 1 and 16%. Cell fabrication is kept typical of the prevailing industrial cell design. The cycle life ranges from 2800 to 60, depending inversely on the Zn utilization. In all cases, the Zn material microstructure sheds the polytetrafluoroethylene (PTFE) binder and forms zinc oxide (ZnO) rods, with longer rods formed by lower current per Zn mass. Irreversible side reactions such as the hydrogen evolution reaction (HER), short circuits, or gas crossover cause the Zn anode’s charging efficiency to average 92% (as low as 86%), which in turn causes the baseload of metallic Zn to gradually disappear. Cell failure occurs after the baseload of metallic Zn is exhausted. The total lifetime discharge capacity remains constant near 12 ± 5 Ah/g Zn invariant of Zn utilization, which suggests that the aforementioned processes of Zn microstructural evolution and side-reaction destruction of baseload metallic zinc both progress linearly with cell capacity throughput. Manual reproduction of individual Zn failure mechanisms is performed in 22 fresh cells. Tight packing of the microstructure can lead to poor mass transfer, which causes supersaturation of soluble Zn and finally produces a high overvoltage during discharge. Here, the low charging current density yields poor coulombic efficiency due either to the competitive HER or soft short circuits.

25 ENERGY STORAGE↗

EMPDF : inferring the Milky Way mass with data-driven distribution function in phase space

We introduce the emPDF (empirical distribution function), a novel dynamical modelling method that infers the gravitational potential from kinematic tracers with optimal statistical efficiency under the minimal assumption of steady state. emPDF determines the best-fitting potential by maximizing the similarity between instantaneous kinematics and the time-averaged phase-space distribution function (DF), which is empirically constructed from observation upon the theoretical foundation of oPDF (Han et al. 2016). This approach eliminates the need for presumed functional forms of DFs or orbit libraries required by conventional DF- or orbit-based methods. emPDF stands out for its flexibility, efficiency, and capability in handling observational effects, making it preferable to the popular Jeans equation or other minimal assumption methods, especially for the Milky Way (MW) outer halo where tracers often have limited sample size and poor data quality. We apply emPDF to infer the MW mass profile using Gaia DR3 data of satellite galaxies and globular clusters, obtaining enclosed masses of M (,r) = 26±8, 46±8, 90±13⁠, and 149±40 x 10 10 M ⊙ at r = 30, 50, 100⁠, and 200 kpc, respectively. These are consistent with the updated constraints from simulation-informed DF fitting (Li et al. 2020). While the simulation-informed DF offers superior precision owing to the additional information extracted from simulations, emPDF is independent of such supplementary knowledge and applicable to general tracer populations. emPDF is currently implemented for tracers with complete 6D kinematics within spherical potentials, but it can potentially be extended to address more general problems.

Astrophysics of Galaxies (astro-ph.GA)↗

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The vertical structure of convective mass-flux derived from modern radar systems: Data analysis in support of cumulus parametrization (Final Report)

The project delivered against all its major aims. We first developed a new calibration technique that enabled the construction of a long-term (17 years) calibrated radar dataset for the Darwin region. We documented both the technique and the data set in publications. We then developed a corresponding long-term dataset that characterises the large-scale state of the atmosphere. Equipped with both, we examined the relationship of key convective ensemble characteristics, such as cloud number and size, with the convective environment. In addition to the stated goals, we also applied the data set to i) estimate rainfall efficiency; ii) derive a new metric for convective organisation and iii) derive a longterm data set of convective mass-flux in the Darwin region and apply it to derive estimates of entrainment and detrainment rates in a convective cloud ensemble. Most of the research has been published or submitted for publication and will therefore only briefly summarised here, with links to or copies of the respective papers supplied.

58 GEOSCIENCES↗

Considerations for Electrochemical Phosphorus Precipitation: A Figures of Merit Approach

Electrochemical phosphorus precipitation (EPP) from wastewater is a promising emerging technology for recovering valuable nutrients. While there are significant advantages of EPP compared to traditional phosphorus recovery, large gaps in reported performance exist between EPP methods and between EPP and industrial methods. Herein we discuss Figures of Merit (FOM) to normalize and report EPP performance at low-to-intermediate technology readiness levels (TRLs). Here, the appropriate use of FOM in electrochemical engineering enables better comparison between technologies, enhanced understanding of electrochemical and mass transport phenomena, and faster scale-up and adoption of nascent technologies.¬ FOM specific to EPP are discussed along with important considerations and adaptations from traditional electrochemical engineering FOM. Importantly, this FOM approach may be adapted for many different electrochemical processes and technologies, aiding in the push toward and adoption of electrification in chemical processing.

42 ENGINEERING↗

High Current Cycling in a Superconcentrated Ionic Liquid Electrolyte to Promote Uniform Li Morphology and a Uniform LiF-Rich Solid Electrolyte Interphase

High-energy-density systems with fast charging rates and suppressed dendrite growth are critical for the implementation of efficient and safe next-generation advanced battery technologies such as those based on Li metal. However, there are few studies that investigate reliable cycling of Li metal electrodes under high-rate conditions. in this work, by employing a superconcentrated ionic liquid (IL) electrolyte, we highlight the effect of Li salt concentration and applied current density on the resulting Li deposit morphology and solid electrolyte interphase (SEI) characteristics, demonstrating exceptional deposition/dissolution rates and efficiency in these systems. Operation at higher current densities enhanced the cycling efficiency, e.g., from 64 ± 3% at 1 mA cm –2 up to 96 ± 1% at 20 mA cm –2 (overpotential <±0.2 V), while resulting in lower electrode resistance and dendrite-free Li morphology. A maximum current density of 50 mA cm –2 resulted in 88 ± 3% cycling efficiency, displaying tolerance for high overpotentials at the Ni working electrode (0.5 V). X-ray photoelectron microscopy (XPS), time-of-flight secondary-ion mass spectroscopy (ToF-SIMS), and scanning electron microscopy (SEM) surface measurements revealed that the formation of a stable SEI, rich in LiF and deficient in organic carbon species, coupled with nondendritic and compact Li morphologies enabled enhanced cycling efficiency at higher currents. Reduced dendrite formation at high current is further highlighted by the use of a highly porous separator in coin cell cycling (1 mAh cm –2 at 50 °C), sustaining 500 cycles at 10 mA cm –2 .

25 ENERGY STORAGE↗

In-gas-jet laser spectroscopy with S 3 -LEB

The Super Separator Spectrometer-Low Energy Branch (S 3 -LEB) is a low-energy radioactive ion beam experiment under commissioning as part of the GANIL-SPIRAL2 facility. It will be used for the production and study of exotic nuclei by in-gas laser ionization and spectroscopy (IGLIS), decay spectroscopy, and mass spectrometry. Here, we report recent results from the off-line commissioning of S 3 -LEB, including first laser spectroscopy measurements in both the gas cell and the supersonic gas jet, the determination of the transport efficiency of laser ions from the gas cell through the RFQ chain, and time-of-flight measurements with the multi-reflection time-of-flight mass spectrometer PILGRIM. The measurements were performed using erbium, introduced by evaporation from a heated filament in the gas environment. The reported laser spectroscopy results include a characterization of the pressure broadening in the gas cell, proof-of-principle isotope shift measurements, and hyperfine-structure measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

TOI-1235 b: A Keystone Super-Earth for Testing Radius Valley Emergence Models around Early M Dwarfs

Small planets on close-in orbits tend to exhibit envelope mass fractions of either effectively zero or up to a few percent depending on their size and orbital period. Models of thermally driven atmospheric mass loss and of terrestrial planet formation in a gas-poor environment make distinct predictions regarding the location of this rocky/nonrocky transition in period–radius space. Here we present the confirmation of TOI-1235 b (P = 3.44 days, r{sub p}=1.738{sub −0.076}{sup +0.087} R{sub ⊕}), a planet whose size and period are intermediate between the competing model predictions, thus making the system an important test case for emergence models of the rocky/nonrocky transition around early M dwarfs (R {sub s} = 0.630 ± 0.015 R{sub ⊙}, M {sub s} = 0.640 ± 0.016 M{sub ⊙}). We confirm the TESS planet discovery using reconnaissance spectroscopy, ground-based photometry, high-resolution imaging, and a set of 38 precise radial velocities (RVs) from HARPS-N and HIRES. We measure a planet mass of 6.91{sub −0.85}{sup +0.75} M{sub ⊕}, which implies an iron core mass fraction of 20{sub −12}{sup +15}% in the absence of a gaseous envelope. The bulk composition of TOI-1235 b is therefore consistent with being Earth-like, and we constrain an H/He envelope mass fraction to be <0.5% at 90% confidence. Our results are consistent with model predictions from thermally driven atmospheric mass loss but not with gas-poor formation, suggesting that the former class of processes remains efficient at sculpting close-in planets around early M dwarfs. Our RV analysis also reveals a strong periodicity close to the first harmonic of the photometrically determined stellar rotation period that we treat as stellar activity, despite other lines of evidence favoring a planetary origin (P=21.8{sub −0.8}{sup +0.9} days, m{sub p}sin i=13.0{sub −5.3}{sup +3.8} M{sub ⊕}) that cannot be firmly ruled out by our data.

79 ASTRONOMY AND ASTROPHYSICS↗

Uranium Holdup Monitoring with Compton Imaging as Function of Depth and Mass

Material Control and Accountability (MC&A) programs track masses of materials flowing through production processes, where some material remains in process equipment as holdup. Quantification of these masses using gamma emissions typically involves usage of a well characterized radiation detector and assumptions of geometric configuration to constrain detection efficiencies, where the Generalized Geometry Holdup (GGH) method is often used. Uncertainties on the order of ±50% are observed, where the difficulties arise based on the asymmetric and gradient distributions of material that do not fall within the bounds of GGH. Gamma imagers provide a possible means to improve this geometric knowledge. This work describes the process used in creating a series of mass standards to aid the development of imaging algorithms for quantification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The dark matter halo masses of elliptical galaxies as a function of observationally robust quantities

Context. The assembly history of the stellar component of a massive elliptical galaxy is closely related to that of its dark matter halo. Measuring how the properties of galaxies correlate with their halo mass can therefore help to understand their evolution. Aims. We investigate how the dark matter halo mass of elliptical galaxies varies as a function of their properties, using weak gravitational lensing observations. To minimise the chances of biases, we focus on the following galaxy properties that can be determined robustly: the surface brightness profile and the colour. Methods. We selected 2409 central massive elliptical galaxies (log M*/M ⊙ ≳ 11.4) from the Sloan Digital Sky Survey spectroscopic sample. We first measured their surface brightness profile and colours by fitting Sérsic models to photometric data from the Kilo-Degree Survey (KiDS). We fitted their halo mass distribution as a function of redshift, rest-frame r-band luminosity, half-light radius, and rest-frame u - g colour, using KiDS weak lensing measurements and a Bayesian hierarchical approach. For the sake of robustness with respect to assumptions on the large-radii behaviour of the surface brightness, we repeated the analysis replacing the total luminosity and half-light radius with the luminosity within a 10 kpc aperture, L r, 10 , and the light-weighted surface brightness slope, Γ 10 . Results. We did not detect any correlation between the halo mass and either the half-light radius or colour at fixed redshift and luminosity. Using the robust surface brightness parameterisation, we found that the halo mass correlates weakly with L r,10 and anti-correlates with Γ 10 . At fixed redshift, L r, 10 and Γ 10 , the difference in the average halo mass between galaxies at the 84th percentile and 16th percentile of the colour distribution is 0.00 ± 0.11 dex. Conclusion. Our results indicate that the average star formation efficiency of massive elliptical galaxies has little dependence on their final size or colour. This suggests that the origin of the diversity in the size and colour distribution of these objects lies with properties other than the halo mass.

79 ASTRONOMY AND ASTROPHYSICS↗

Selective Detection of Diglycolamide Diastereomers By Metal-Ligand Cluster Formation

Introduction (120 words): Differentiation of isomers using mass spectrometry is a challenge, as these species tend to produce ions of identical mass-to-charge ratio. Therefore, separation with mass spectrometry must rely on chemical differences between isomeric species. Separation of stereoisomers is especially challenging, as these species often have very similar chemistry. However, recent investigations of the solvent extraction behavior of diastereomers of diglycolamide molecules have shown that different stereoisomers can have significantly different lanthanide extraction efficiencies. These studies showed that the R,S stereoisomer of 2,2'-oxybis(N,N-dioctylpropanamide efficiently extracts lanthanides, while the S,S stereoisomer does not. Thus, gas-phase metal complexation may provide a pathway for differentiating these species using mass spectrometry. Methods (120 words): Europium, samarium, and holmium clusters with the R,S, and the S,S diastereomers of 2,2'-oxybis(N,N-didecylpropanamide (trivially tetradecyl diglycolamide, or mTDDGA) were generated in gas-phase using the electrospray ionization source of a Bruker (Billerica, MA, USA) micrOTOF-Q II quadrupole time-of-flight mass spectrometer. Solutions of aqueous lanthanide nitrate and diglycolamide ligands in 2-propanol were added to 50%:50% by volume acetonitrile:2-propanol to generate the spray solutions. Ligand concentration was maintained at approximately 6 µM, while lanthanide concentration was maintained at either 6 µM or 30 µM . High resolution, high mass accuracy spectra were recorded using the time-of-flight. Mass accuracy was ensured using external calibration with Agilent (Santa Clara, CA, USA) ESI-L Low Concentration tuning mix. Preliminary data (300 words): Electrospray of solutions containing only R,S-mTDDGA or S,S-m-TDDGA yield abundant peaks at m/z= 721.7, corresponding to [mTDDGA+H]+1, m/z = 743.7, corresponding to [mTDDGA+Na]+1, and m/z = 1464.4, corresponding to the sodium-bound dimer, [Na(mTDDGA)2]+1. Spray of solutions containing 6 µM europium (Eu) with 3 µM R,S-mTDDGA produced an abundant cluster ion with an isotopic envelope centered at m/z=772.0, corresponding to [Eu(R,S-mTDDGA)3]3+. Europium-containing cluster ions with isotopic envelopes apexing at m/z = 1012.3 and 1189.0 correspond to the [Eu(R,S-mTDDGA)4]3+ and [Eu(R,S-mTDDGA)5]3+ cluster ions, respectively. Protonated and sodiated R,S-mTDDGA are present as well, along with the sodium-bound dimer. In contrast, spray of solutions containing 6 µM europium (Eu) with 3 µM S,S-mTDDGA diastereomer yielded only protonated and sodiated ligand ions; no Eu- S,S-mTDDGA ions were present. This mirrors the solution-phase behavior, where the S,S diestereomer extracts lanthanides with significantly less efficiency than the R,S diestereomer. Experiments with holmium and samarium yielded the same results. Increasing the lanthanide concentration to 30 µM resulted in limited formation of lanthanide-S,S-mTDDGA clusters. However, the abundance of the [Ln(S,S-mTDDGA)3]3+ clusters remained low compared to the abundance of the protonated and sodiated ligand. Additionally, the abundance of the [Ln(R,S-mTDDGA)3]3+ cluster ion was significantly higher than that of the protonated and sodiated ligand in experiments with spray solutions containing 30 µM lanthanide with R,S-mTDDA, supporting the hypothesis that R,S-mTDDGA has a higher intrinsic affinity for the lanthanides than S,S-mTDDGA. Thus, the intrinsic complexation with lanthanides appears to offer a route to differentiate diglycolamide diestereomers in the gas-phase. Novelty (20): Stereoisomers can be differentiated in the gas phase by exploitation of differences in metal complexation chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Non-radiative luminescence decay with self-trapped hole migration in strontium titanate: Interplay between optical and transport properties

A novel model for the non-radiative decay of self-trapped excitons (STEs) in the advanced functional oxide SrTiO3 is proposed and supported by experimental observations. The study is based on the initial ionoluminescence stage for STE emission at 2.5 eV, and its dependence on temperature and electronic excitation rate under energetic heavy-ion irradiation. For all temperatures, this initial stage reaches rapidly a quasi-steady level, and then decreases as induced-structural damage increases. The quasi-steady luminescence exhibits a linear dependence on the excitation rate, suggesting a constant efficiency for STEs formation. An activation energy of 55 meV, essentially independent of the incident ion mass and energy of projectile-ion, is deduced from an Arrhenius-type relationship with irradiation temperature. This energy is in good agreement with experimental values, measured for non-radiative STE decay under ns-laser pulse excitation, and reasonably consistent with density functional theory calculations for migration of self-trapped holes (STHs) described by a small-polaron adiabatic hopping model. A new mechanism dealing with a non-radiative contribution to the STE transition is discussed, consisting of STH migration through thermally-activated hopping and annihilation with the STE-electron. Luminescence kinetics from the chromium intrinsic impurity strongly supports this model, being consistent with the annihilation of Cr 3+ centers through recombination with migrating STHs.

luminescence↗

Towards fast-charging high-energy lithium-ion batteries: From nano- to micro-structuring perspectives

Electric vehicles (EVs) have been playing an indispensable role in reducing greenhouse gas emissions for our modern society. However, current EVs are difficult to meet people’s diverse travel needs, especially in long endurance and fast-charging capacities. At the heart of this issue is the physicochemical limit of current lithium-ion batteries (LIBs), which are the core parts for powering the vehicles. Hence, LIBs with simultaneous high energy and power are critically required to further promote the development of EVs. Here, in this review, we first summarize the key electrochemical processes in electrochemical reactions which lead to the corresponding overpotentials in or between multiple battery components. Furthermore, numerical simulations are employed to quantitatively analyze the effects of versatile electrode parameters on electrochemical properties in high-energy NMC811//graphite systems. On the basis of the in-depth understandings from simulation, recent experimental efforts on designing electroactive materials and electrode architectures across multiple length scales are discussed. Among them, nano-structuring can promote local mass transport and stabilize the interfaces at the particle level, while micro-structuring can establish efficient pathways for charge carriers at the electrode level. Finally, we conclude that a tight feedback loop among structure engineering, characterization and simulation should be followed to speed up the understanding of the deficiencies existing in current electrode designs as well as point out the possible electrode optimization routes for next-generation fast-charging LIBs.

25 ENERGY STORAGE↗

A numerical method for simulating variable density flows in membrane desalination systems

Here, we present a novel method for simulating unsteady, variable density, fluid flows in membrane desalination systems. By assuming the density varies only with concentration and temperature, the scheme decouples the solution of the governing equations into two sequential blocks. The first solves the governing equations for the temperature and concentration fields, which are used to compute all thermophysical properties. The second block solves the conservation of mass and momentum equations for the velocity and pressure. We show that this is computationally more efficient than schemes that iterate over the full coupled equations in one block. We verify that the method achieves second-order spatial-temporal accuracy, and we use the method to investigate buoyancy-driven convection in a desalination process called vacuum membrane distillation. Specifically, we show that with gravity properly oriented, variations in temperature and concentration can trigger a double-diffusive instability that enhances mixing and improves water recovery. We also show that the instability can be strengthened by providing external heating.

97 MATHEMATICS AND COMPUTING↗

Nonlinear sparse Bayesian learning for physics-based models

This paper addresses the issue of overfitting while calibrating unknown parameters of over-parameterized physics-based models with noisy and incomplete observations. Here, a semi-analytical Bayesian framework of nonlinear sparse Bayesian learning (NSBL) is proposed to identify sparsity among model parameters during Bayesian inversion. NSBL offers significant advantages over machine learning algorithm of sparse Bayesian learning (SBL) for physics-based models, such as 1) the likelihood function or the posterior parameter distribution is not required to be Gaussian, and 2) prior parameter knowledge is incorporated into sparse learning (i.e. not all parameters are treated as questionable). NSBL employs the concept of automatic relevance determination (ARD) to facilitate sparsity among questionable parameters through parameterized prior distributions. The analytical tractability of NSBL is enabled by employing Gaussian ARD priors and by building a Gaussian mixture-model approximation of the posterior parameter distribution that excludes the contribution of ARD priors. Subsequently, type-II maximum likelihood is executed using Newton's method whereby the evidence and its gradient and Hessian information are computed in a semi-analytical fashion. We show numerically and analytically that SBL is a special case of NSBL for linear regression models. Subsequently, a linear regression example involving multimodality in both parameter posterior pdf and model evidence is considered to demonstrate the performance of NSBL in cases where SBL is inapplicable. Next, NSBL is applied to identify sparsity among the damping coefficients of a mass-spring-damper model of a shear building frame. These numerical studies demonstrate the robustness and efficiency of NSBL in alleviating overfitting during Bayesian inversion of nonlinear physics-based models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗