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At least 487 records · Page 27

Optimization of catalyst-coated membranes for enhancing performance in proton exchange membrane electrolyzer cells

To achieve large-scale application of proton exchange membrane electrolyzer cells (PEMECs) for hydrogen production, it is highly desirable to reduce the manufacturing cost while enhancing cell performance. In the PEMPECs, a catalyst-coated membrane (CCM) is the vital component where electrochemical reactions and mass transport mainly occur. The fabrication methods and catalyst layer (CL) structure can significantly affect the cell performance. Herein, for the first time, a comparative study of CCM fabrications with decal transfer and direct spray deposition methods have been conducted by both ex-situ materials characterization and in-situ performance testing in PEMECs. It is found CCMs that are fabricated with a direct spray deposition method display enhanced cell performance compared to CCMs fabricated with a decal transfer method, mainly due to the largely reduced ohmic resistance and improved mass transport. More importantly, cell performance can be greatly enhanced by simply regulating the Nafion ionomer content at the anode CL. The optimal Nafion ionomer content of 10 wt% gives the best cell performance at 80 °C with a low cell voltage of 1.887 V at 2 A cm -2 , outperforming the commercial CCM and most other previous publications. Our study provides a valuable guidance for fabrication and optimization of CCMs with significantly enhanced performance and reduced cost for practical application of the PEMECs.

08 HYDROGEN↗

Experimentally validated high-fidelity simulations of a liquid jet in supersonic crossflow

Here, utilizing recent advancements in computational schemes for compressible, multiphase flows, this work features a parametric study of a pure liquid jet in supersonic crossflow that involves simulating the atomization process for four values of momentum-flux ratio. These simulations are validated against experimental results measured with high-speed X-ray imaging, which confirm the accuracy of the numerical approach. Also, the effect of numerical resolution on some flow behavior is investigated, revealing convergence of the jet shape and surface instability wavelength. Analysis of the resulting sprays includes statistical descriptions of the liquid distribution, liquid structures created through breakup, interfacial instabilities, and dominant flow features. As the flowrate increases, the spray penetrates further, it becomes more disperse, and less liquid impacts the wall, but the droplet size distribution changes little. The wavelength of instabilities on the windward side of the jet diverges from measured trends in subsonic crossflows. In a visualization of the time-averaged flow, counter-rotating vortices are observed along the jet core and in the wake, affecting the process of primary atomization and early droplet trajectories.

42 ENGINEERING↗

Roll-to-roll production of catalyst coated membranes for low-temperature electrolyzers

Here we demonstrate a roll-to-roll (R2R) process for direct coating of anode catalyst layers on a polymer electrolyte membrane for low-temperature water electrolysis. To develop this process, we studied catalyst ink formulation, ink-membrane interactions, and coating quality. The catalyst inks were a mixture of iridium oxide (IrO2) and Nafion in a water and alcohol dispersion medium. The type of alcohol (methanol, ethanol, propanols) and water-to-alcohol ratio were varied to determine their influence on membrane swelling, dispersion quality, and coatability. Interactions of the ink dispersion medium with the membrane were characterized using sessile-drop contact-angle measurements. These measurements show that the ratio of water to alcohol has a strong influence on how rapidly the dispersion media is absorbed by the membrane. Rheology of the catalyst inks was measured to understand the microstructure of the catalyst particles in the ink. This analysis found that 1-propanol leads to better dispersion of the IrO2 particles than ethanol. Small-scale coating samples were prepared to understand coating uniformity and formation of irregularities. Subsequently, two water/1-propanol ratios (90:10 and 75:25) were down-selected for large-scale R2R slot die coating. The R2R catalyst-coated membrane (CCM) coating process increased catalyst layer production throughput by over 500x compared to our standard lab-scale spray coating. The CCMs obtained from this process were tested as single-cell membrane electrode assemblies. They exhibited a cell voltage of 1.91 V at a current density of 2 A/cm2, which is comparable to spray-coated CCMs. In conclusion, the work presented here demonstrates a continuous, scalable manufacturing process that eliminates the need for the decal transfer step typically used in CCM production.

42 ENGINEERING↗

Development of high-performance roll-to-roll-coated gas-diffusion-electrode-based fuel cells

This study focuses on determining fabrication conditions to create high-performance roll-to-roll-coated (R2R-coated) gas-diffusion electrodes (GDEs) for proton-exchange-membrane fuel cells (PEMFCs). Here, we examine how process conditions influence the distribution of ionomer in the electrode, which is shown to be critical for high performance. Using a combination of Kelvin probe, X-ray photoelectron spectroscopy, and nano-scale X-ray computed tomography we show that formation of an ionomer-rich surface is promoted by using a higher drying rate. We show that R2R-coated GDEs have higher surface ionomer concentration than spray-coated GDEs, which enables these R2R-coated GDEs to not need an additional ionomer overlayer, as is typically the case for spray-coated GDEs. This will reduce the number of processing steps and lower material costs in a manufacturing setting. This work shows that with the appropriate selection of materials, ink formulation, and processing conditions, direct-coated GDEs are a viable pathway for fuel cell manufacturing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Long-term durability test of highly efficient membrane electrode assemblies for anion exchange membrane seawater electrolyzers

Direct seawater electrolysis faces fundamental electrochemical challenges, such as suppression of chlorine adsorption and/or evolution reactions that poison the current state-of-the-art anode catalysts and accelerate the degradation of the anion exchange membrane (AEM). The technically favored solution path for addressing these issues includes development of novel selective catalysts and implementation of limited operating conditions. Therefore, development of highly active, selective, cost-effective, and stable seawater-splitting catalysts is required for a successful commercialization of the AEM water electrolyzers (AEMWEs). In this work, we report for the first-time an extended operation for over 1000 h of advanced AEMWEs, operating directly with seawater. To fabricate the membrane electrode assemblies (MEAs), catalyst coated electrodes (CCEs) are assembled with Sustainion® X37-50 grade T anion exchange membranes. The anode CCEs are fabricated by spraying an ink prepared from nanostructured NiFe-layered double hydroxide (LDH) catalyst that are synthesized by the solvothermal method and deposited directly onto platinized titanium porous transport layers (PTLs). The cathode CCEs are prepared by spraying an ink prepared from commercial Renay-Nickel catalyst onto a nickel fiber felt. As prepared AEM electrolyzer cells operated with seawater and demonstrated better than previously reported in the literature performance of over 1000 h of operation at a constant current density of 300 mA cm –2 .

25 ENERGY STORAGE↗

Validation study of sodium pool fire modeling efforts in $\mathrm{MELCOR}$ and $\mathrm{SPHINCS}$ codes

Discharge of sodium coolant into containment from a sodium-cooled fast reactor vessel can occur in the event of a pipe leak or break. In this situation, some of the liquid sodium droplets discharged from the coolant system will react with oxygen in the air before reaching the containment. This phase of the event is normally termed the sodium spray fire phase. Unreacted sodium droplets pool on the containment floor where continued reaction with containment atmospheric oxygen occurs. This phase of the event is normally termed the sodium pool fire phase. Both phases of these sodium-oxygen reactions (or fires) are important to model because of the heat addition and aerosol generation that occur. Any fission products trapped in the sodium coolant may also be released during this progression of events, which if released from containment could pose a health risk to workers and the public. The paper describes progress of an international collaborative research in the area of the sodium fire modeling in the sodium-cooled fast reactors between the United States and Japan under the framework of the Civil Nuclear Energy Research and Development Working Group. In this collaboration between Sandia National Laboratories and Japan Atomic Energy Agency, the validation basis for and modeling capabilities of sodium spray and pool fires in MELCOR of Sandia National Laboratories and SPHINCS of Japan Atomic Energy Agency are being enhanced. Here this study documents MELCOR and SPHINCS sodium pool fire model validation exercises against the JAEA’s sodium pool fire experiments, F7-1 and F7-2. The proposed enhancement of the sodium pool fire models in MELCOR through addition of thermal hydraulic and sodium spreading models that enable a better representation of experimental results is also described.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Characterization of hot-pressed von Alpen type NASICON ceramic electrolytes

The Na-ion conducting solid electrolyte NASICON is a promising solid state electrolyte (SSE) for use in Na based electrochemical systems. The effects of particle morphology and synthesis of von Alpen type NASICON via hot-pressing were investigated. Spray dried particles were shown to improve mechanical and electrochemical properties. X-ray diffraction, scanning electron microscopy, impulse excitation measurements, Vickers hardness, and impedance spectroscopy were used to correlate relationships between phase purity, microstructure, mechanical properties, and electrochemical properties. Scanning electron microscopy showed the presence of a glass phase as between 19.08% and 28.23% area percentage and a ZrO 2 phase between 0.46% and 3.51% area percentage in the hot-pressed samples. Impulse excitation showed elastic modulus varying from 83.65 to 97.65 GPa. The first values of Poisson's ratio and shear modulus of NASICON are reported as between 0.23 and 0.26 and 33.87 to 38.79 GPa, respectively. Vickers hardness and fracture toughness measurements showed Vickers hardness ranging from 4.30 to 4.68 GPa and fracture toughness ranging from 1.05 to 1.09 MPa m ½ . Impedance spectroscopy showed grain conductivities ranging from 1.023 to 1.287 mS/cm, with grain boundary resistance percentages between 73.22 and 47.5%. Total conductivities ranged from 0.292 to 0.596 mS/cm, with 0.596 mS/cm being achieved at room temperature for the spray dried powders with lower grain boundary resistance percentages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Combining Mass Spectrometry of Picoliter Samples with a Multicompartment Electrodynamic Trap for Probing the Chemistry of Droplet Arrays

Single droplet levitation provides contactless access to the microphysical and chemical properties of micrometer-sized samples. Most applications of droplet levitation to chemical and biological systems use nondestructive optical techniques to probe droplet properties. To provide improved chemical specificity, we coupled a multicompartment quadrupole electrodynamic trap (QET) with single droplet mass spectrometry. Our QET continuously traps a monodisperse droplet population (tens to hundreds of droplets) and allows for the simultaneous sizing of a single droplet using its Mie scattering pattern. Single droplets are subsequently ejected into the ionization region of an ambient pressure inlet mass spectrometer. We optimized two complementary soft ionization techniques for picoliter aqueous droplets: (1) paper spray (PS) ionization and (2) thermal desorption glow discharge (TDGD) ionization. Both techniques detect oxygenated organic acids in single droplets, with signal-to-noise ratios >100 and detection limits on the order of 10 pg. Sensitivity and reproducibility across single droplets are driven by the droplet deposition location and spray stability in PS-MS and the ionization region humidity and analyte evaporation rate in TDGD-MS. Importantly, the analyte evaporation rate can control the TDGD-MS quantitative capability because high evaporation rates result in significant ion suppression. Additionally, this effect is mitigated by optimizing the vaporization temperature, droplet size range, and analyte volatility. We demonstrate quantitative and reproducible measurements with a droplet internal standard (<10% RSD) and compare the sensitivity of PS-MS and TDGD-MS. Finally, we demonstrate the application of QET-MS to the study of heterogeneous chemical kinetics with the reaction of gas phase O 3 and aqueous maleic acid droplets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toward Optimizing Electrospun Nanofiber Fuel Cell Catalyst Layers: Microstructure and Pt Accessibility

This work investigates how local ionomer/platinum (Pt) interactions and ionomer distribution in electrospun Pt/Vulcan nanofiber electrodes impact ionomer coverage, proton accessibility, and oxygen reduction reaction (ORR) performance in proton-exchange membrane fuel cells. Insights from various in situ electrochemical diagnostics were utilized in conjunction with ex situ microscopic characterization to understand how the electrode microstructure—both at the aggregate level and near the ionomer/platinum interface—is affected by electrospinning in comparison to ultrasonic spraying. The effect of the carrier polymer poly(acrylic acid) (PAA) concentration from 5–20 wt % (with respect to total ink solids) on the resulting nanofiber morphology is discussed. Electron microscopy observations and CO displacement measurements indicated that Pt/Vulcan nanofibers prepared with a higher PAA concentration (15 wt %) were conformally coated with a film of ionomer on the exterior of the fiber, which resulted in an overall lower ionomer coverage on both Pt and carbon throughout the fiber diameter. In contrast, 10 wt % PAA leads to a uniform intrafiber distribution of the ionomer within the fibers, increasing the overall ionomer coverage and proton accessibility under both wet and dry conditions. These differences in the local ionomer coverage on Pt between 10 and 15 wt % PAA were also attributed to differences in the adsorption/interaction affinities between PAA and the ionomer onto the catalyst surface in the ink using zeta potential measurements. Additional fuel cell electrochemical tests on the electrospun electrodes show improvements in ORR kinetics and high-current-density H 2 /air performance compared to the ultrasonically sprayed electrodes.

25 ENERGY STORAGE↗

Spinel Cu–Mn–Cr Oxide Nanoparticle-Pigmented Solar Selective Coatings Maintaining >94% Efficiency at 750 °C

High-temperature concentrating solar power (CSP) system is capable of harvesting and storing solar energy as heat towards cost-effective dispatchable solar electricity. Solar selective coating is a critical component to boost its efficiency by maximizing solar absorptance and minimizing thermal emittance losses. However, maintaining a high solar-thermal conversion efficiency >90% for long-term operation at ≥750 ºC remains a significant challenge. Herein, we report spray-coated spinel Cu-Mn-Cr oxide nanoparticle-pigmented solar selective coatings on Inconel tube sections maintaining ≥94% efficiency at 750 ºC and ≥92.5% at 800 ºC under 1000x solar concentration after 60 simulated day-night thermal cycles in air, each cycle comprising 12h at 750 ºC/800 ºC and 12h cooling to 25 ºC. The solar spectral selectivity is intrinsic to the band-to-band and d-d transitions of non-stoichiometric spinel Cu-Mn-Cr oxide nanoparticles. Furthermore, this feature offers a large fabrication tolerance in nanoparticle volume fraction and coating thickness, facilitating low-cost and scalable spray-coated high-efficiency solar selective absorbers for high-temperature CSP systems.

14 SOLAR ENERGY↗

Biopolymer-Templated Titania Film Formation for Nanostructured Coatings Revealed by Machine Learning-Supported Time-Resolved Analysis

This study presents a machine learning approach to derive the film formation of biopolymer-templated titania nanostructures during spray deposition, in combination with in situ grazing-incidence small-angle X-ray scattering (GISAXS). A neural network trained on synthetic GISAXS data directly predicts domain-size distributions from experimental two-dimensional scattering patterns, capturing the full kinetics of nanostructure evolution with high temporal resolution. The predictions reveal hierarchical size distributions and periodic growth features, consistent with layer-by-layer spray deposition and validated by complementary scanning electron microscopy (SEM) imaging. Quantitative comparison with conventional parametric GISAXS fits shows good qualitative agreement, with systematic differences explained by domain-shape assumptions and resolved by applying a geometric scaling factor. Simulated SEM-like surfaces derived from neural network outputs reproduce the porous, foam-like nanoscale morphology observed experimentally, reinforcing the method’s credibility. This integrated approach enables real-time, nondestructive, statistically averaged monitoring of bulk nanostructure development in functional coatings, offering a scalable methodology to accelerate the characterization and process control of sustainably manufactured nanostructured titania films for energy-related applications such as photocatalysis and photovoltaics.

Heger, JulianEliah↗

Tunable Semiconducting Behavior and Linear-Nonlinear Optical Properties of Ag–Sn Dual-Doped Nanocrystalline CdO Thin Films for Optoelectronics

Semiconductor-based thin films have a great impact on determining the anticipated optoelectronic device construction and the advancement of cutting-edge applications. Herein, Ag and Sn dual-doped nanocrystalline transparent conducting CdO thin films were prepared on glass substrates using a cost-effective spray coating method, and their structural, morphological, optical, and semiconducting behaviors were investigated. The successful incorporation of Ag and Sn resulted in the polycrystalline nature of the deposited films without the additional peaks, as verified by X-ray diffraction (XRD) analysis. The XRD report also revealed the enhanced crystallinity (65%) at the higher doping level (3 wt % Ag and Sn-doped CdO film). All the deposited CdO films exhibited homogeneous, spherical, or round-shaped grains, with agglomeration revealed by scanning electron microscopy analysis. UV–visible spectroscopy was utilized to determine the linear and nonlinear optical properties of the deposited CdO thin films, and a reduction in the band gap from 3.891 to 3.772 eV was observed. A significant enhancement in the first- and third-order nonlinear susceptibility and nonlinear refractive index of the doped CdO films was also observed with increasing doping concentration. Hall effect data were collected at room temperature to investigate the electrical properties of all of the CdO films. The charge carrier concentration of CdO thin films was increased from 142.08 × 10 18 to 169.10 × 10 18 cm –3 , and the highest conductivity was found to be 192 s/cm on doping 3 wt % Ag–Sn. All the CdO thin films exhibited n-type conductivity, while an incredible n-type to p-type charge carrier transition was noticed at a higher doping level (3 wt % Ag–Sn). The findings of the current work are expected to advance the synthesis of semiconductor thin films through cost-effective spray coating methods for optoelectronic device applications.

deposition↗

Minimizing Oxygen Permeability in Chitin/Cellulose Nanomaterial Coatings by Tuning Chitin Deacetylation

The demand for packaging materials with low gas permeabilities is increasing, but commonly used petroleum-derived single-use plastics are not renewable, biodegradable, or easy to recycle. Nanomaterials composed of chitin and cellulose, which are abundant in nature, have high crystallinities and low oxygen permeabilities (OP), providing a viable alternative. In this work, we explore how deacetylation conditions of crab shell chitin can be used to tune the charge and size of resulting chitin nanowhiskers (ChNWs) and the resulting OP of layered film structures. Three deacetylation factors, the concentration of sodium hydroxide (%NaOH), temperature (T), and reaction time, were explored using a three-factor three-level Taguchi design with an orthogonal array. Furthermore, the resulting ChNW suspensions were sequentially spray-coated with suspensions of cellulose nanocrystals (CNCs) onto cellulose acetate (CA) films to form a multilayer structure. We show that ChNWs prepared under more aggressive deacetylation conditions inside the original orthogonal array (higher %NaOH, T, and time) had shorter lengths but the surface charge was significantly influenced only by more aggressive deacetylation outside of the original design conditions. With only ~10% decrease in the ultimate tensile strength and no significant loss in failure strain, the ChNW-CNC coating resulted in ~20% decrease in WVTR in comparison to uncoated CA films. The optimization of process conditions resulted in CA-ChNW-CNC films with a 91-99% decrease in OP (132-16.7 cm 3 ∙μm/m 2 /day/kPa versus 1553 cm3∙μm/m2/day/kPa for uncoated CA).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ejection of Dust From the Ocean as a Potential Source of Marine Ice Nucleating Particles

Oceans are, generally, relatively weak sources of ice nucleating particles (INPs). Thus, dust transported from terrestrial regions can dominate atmospheric INP concentrations even in remote marine regions. Studies of ocean-emitted INPs have focused upon sea spray aerosols containing biogenic species. Even though large concentrations of dust are transported over marine regions, resuspended dust has never been explicitly considered as another possible source of ocean-emitted INPs. Current models assume that deposited dust is not re-emitted from surface waters. Our laboratory studies of aerosol particles produced from coastal seawater and synthetic seawater doped with dust show that dust can indeed be ejected from water during bubble bursting. INP concentration measurements show these ejected dust particles retain ice nucleating activity. Doping synthetic seawater to simulate a strong dust deposition event produced INPs active at temperatures colder than -13 °C and INP concentrations one to two orders of magnitude greater than either lab sea spray or marine boundary layer measurements. The relevance of these laboratory findings is highlighted by single particle composition measurements along the Californian coast where at least 9% of dust particles were mixed with sea salt. Additionally, global modeling studies show that resuspension of dust from the ocean could exert the most impact over the Southern Ocean, where ocean-emitted INPs are thought to dominate atmospheric INP populations. More work characterizing the factors governing the resuspension of dust particles is required to understand the potential impact upon clouds.

54 ENVIRONMENTAL SCIENCES↗

High-strength 3D printed poly(lactic acid) composites reinforced by shear-aligned polymer-grafted cellulose nanofibrils

This work demonstrates the application of pilot-scale surface functionalization of cellulose nanofibrils (CNFs) by aqueous grafting-through polymerization and subsequent spray drying in 3D printed poly(lactic acid) (PLA) composites. Grafted-CNF composites attain an ultimate tensile strength of 88 ± 3 MPa and a tensile modulus of elasticity of 7.8 ± 1.3 GPa in the printing direction at 20 wt% reinforcement loading. These increases, 42% and 139% over neat PLA, respectively, represent the strongest reported 3D printed CNF/PLA composite to date in the literature. The mechanisms behind these improvements are investigated by comparisons to neat PLA and unmodified spray-dried CNF/PLA controls using melt rheology, dynamic mechanical analysis, and assessment of the reinforcement dispersion. These experiments reveal that improved network formation and shear-induced alignment of the grafted CNFs facilitate the remarkable tensile properties of the printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Antifungal symbiotic peptide NCR044 exhibits unique structure and multifaceted mechanisms of action that confer plant protection

In the indeterminate nodules of a model legume Medicago truncatula, ~700 nodule-specific cysteine-rich (NCR) peptides with conserved cysteine signature are expressed. NCR peptides are highly diverse in sequence, and some of these cationic peptides exhibit antimicrobial activity in vitro and in vivo. However, there is a lack of knowledge regarding their structural architecture, antifungal activity, and modes of action against plant fungal pathogens. Here, the three-dimensional NMR structure of the 36-amino acid NCR044 peptide was solved. This unique structure was largely disordered and highly dynamic with one four-residue α-helix and one three-residue antiparallel β-sheet stabilized by two disulfide bonds. NCR044 peptide also exhibited potent fungicidal activity against multiple plant fungal pathogens, including Botrytis cinerea and three Fusarium spp. It inhibited germination in quiescent spores of B. cinerea. In germlings, it breached the fungal plasma membrane and induced reactive oxygen species. It bound to multiple bioactive phosphoinositides in vitro. Time-lapse confocal and superresolution microscopy revealed strong fungal cell wall binding, penetration of the cell membrane at discrete foci, followed by gradual loss of turgor, subsequent accumulation in the cytoplasm, and elevated levels in nucleoli of germlings. Spray-applied NCR044 significantly reduced gray mold disease symptoms caused by the fungal pathogen B. cinerea in tomato and tobacco plants, and postharvest products. Our work illustrates the antifungal activity of a structurally unique NCR peptide against plant fungal pathogens and paves the way for future development of this class of peptides as a spray-on fungistat/fungicide.

59 BASIC BIOLOGICAL SCIENCES↗

Insights from high-fidelity modeling of industrial rotary bell atomization

The global automotive industry sprayed over 2.6 billion liters of paint in 2018, much of which through electrostatic rotary bell atomization, a highly complex process involving the fluid mechanics of rapidly rotating thin films tearing apart into micrometer-thin filaments and droplets. Coating operations account for 65% of the energy usage in a typical automotive assembly plant, representing 10,000s of gigawatt-hours each year in the United States alone. Optimization of these processes would allow for improved robustness, reduced material waste, increased throughput, and significantly reduced energy usage. Here, we introduce a high-fidelity mathematical and algorithmic framework to analyze rotary bell atomization dynamics at industrially relevant conditions. Our approach couples laboratory experiment with the development of robust non-Newtonian fluid models; devises high-order accurate numerical methods to compute the coupled bell, paint, and gas dynamics; and efficiently exploits high-performance supercomputing architectures. These advances have yielded insight into key dynamics, including i) parametric trends in film, sheeting, and filament characteristics as a function of fluid rheology, delivery rates, and bell speed; ii) the impact of nonuniform film thicknesses on atomization performance; and iii) an understanding of spray composition via primary and secondary atomization. These findings result in coating design principles that are poised to improve energy- and cost-efficiency in a wide array of industrial and manufacturing settings.

97 MATHEMATICS AND COMPUTING↗

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗