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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Detailed Evaluation of Electric Demand Load Shifting Potential of Heat Pump Water Heaters

Future utilities will emphasize home appliances to reduce greenhouse gas emissions while providing electric load shifting and demand profile management. Heat pump water heaters (HPWH) have demonstrated the ability to cut water heating energy by more than 65% compared with conventional electric resistance waters (ERWH). Laboratory research was conducted on the load shifting potential of grid-connected heat pump water heaters (HPWH), compared to ERWHs. Testing applied different CTA-2045 command designs. Highly-controlled laboratory experiments were conducted on one ERWH and four HPWHs, including a prototype incorporating the new CTA-2045-B protocol feature allowing ‘advanced’ load up above the tank setpoint. The prototype unit with the B-protocol increased tank temperature by 15oF (8.3C) under the advanced load up providing an increase of 1.8 kWh of storage for a 50-gallon (189 liter) tank. The prototype includes a built-in mixing valve to meet anti-scalding codes. With the load-shaping ability of CTA-2045-B, utilities might be able to store excess renewable energy in connected tanks when renewable wind and solar resource production is high. Tests were performed under baseline conditions (no load shift) and under several load-shifting schemes, including load up and advanced load up, ahead of shed commands. Grid-connected HPWHs reduced peak demand by as much as 0.5 kW, depending on tank volume, time of day, control scheme, and draw profile.

heat pump water heater, Demand flexibility, load s↗
DOE OSTI2022

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multifidelity validation of digital surrogates using variable-density turbulent mixing models

In this study, ensembles of experimental data are presented and utilized to compare and validate two models used in the simulation of variable-density (Atwood = 0.22), compressible turbulent mixing. Though models of this kind (Reynolds averaged NavierStokes and large-eddy simulations) have been validated extensively with more canonical flows in previous studies, here the present approach offers novelty in the complexity of the geometry, the ensemble-based validation, and the uniformity of the computational framework on which the models are tested. Moreover, all experimental and computational tasks were completed by the authors which has led to a tightly coupled experimental configuration with its “digital twin.” The experimental divergent-shock-tube facility and its data acquisition methods are described and replicated in simulation space. A 2D Euler model which neglects the turbulent mixing at the interface is optimized to experimental data using a Gaussian process. This model then serves as the basis for both the 2D RANS and 3D LES studies that make comparisons to the mixing-layer data from the experiment. A relatively simple RANS model is shown to produce good agreement with experimental data only at late flow development times. The LES ensembles generally show good agreement with experimental data but display sensitivity to the characterization of initial conditions. Resolution-dependent behavior is also observed for certain higher-order statistics of interest. Overall, the LES model successfully captures the effects of divergent geometry, compressibility, and combined nonlinear instabilities inherent to the problem. The successful prediction of mixing width and its growth rate highlight the existence of three distinct regimes in the development of the instability, each with similarities to previously studied instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Epoxy Sealant Self-leveling and Adhesion Test Report

The Hanford tank farms have 149 single shell tanks which were built between 1943 - 1964, and 28 double-shell tanks (DSTs) which were built between 1968 – 1986 (Tank Farms, 2020) which contain radioactive and chemical mixed waste. Many of the tanks have leaked, including DST AY-102 (Waste Tank Summary Report, 2023). As a result, methods of repairing or reinforcing double-shell storage tanks are being evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

On the Representation of Hyporheic Exchange in Models for Reactive Transport in Stream and River Corridors

Efforts to include more detailed representations of biogeochemical processes in basin-scale water quality simulation tools face the challenge of how to tractably represent mass exchange between the flowing channels of streams and rivers and biogeochemical hotspots in the hyporheic zones. Multiscale models that use relatively coarse representations of the channel network with subgrid models for mass exchange and reactions in the hyporheic zone have started to emerge to address that challenge. Two such multiscale models are considered here, one based on a stochastic Lagrangian travel time representation of advective pumping and one on multirate diffusive exchange. The two models are formally equivalent to well-established integrodifferential representations for transport of non-reacting tracers in steady stream flow, which have been very successful in reproducing stream tracer tests. Despite that equivalence, the two models are based on very different model structures and produce significantly different results in reactive transport. In a simple denitrification example, denitrification is two to three times greater for the advection-based model because the multirate diffusive model has direct connections between the stream channel and transient storage zones and an assumption of mixing in the transient storage zones that prevent oxygen levels from dropping to the point where denitrification can progress uninhibited. By contrast, the advection-based model produces distinct redox zonation, allowing for denitrification to proceed uninhibited on part of the hyporheic flowpaths. These results demonstrate that conservative tracer tests alone are inadequate for constraining representation of mass transfer in models for reactive transport in streams and rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cross-national analysis of food security drivers: comparing results based on the Food Insecurity Experience Scale and Global Food Security Index

Abstract The second UN Sustainable Development Goal establishes food security as a priority for governments, multilateral organizations, and NGOs. These institutions track national-level food security performance with an array of metrics and weigh intervention options considering the leverage of many possible drivers. We studied the relationships between several candidate drivers and two response variables based on prominent measures of national food security: the 2019 Global Food Security Index (GFSI) and the Food Insecurity Experience Scale’s (FIES) estimate of the percentage of a nation’s population experiencing food security or mild food insecurity (FI ). We compared the contributions of explanatory variables in regressions predicting both response variables, and we further tested the stability of our results to changes in explanatory variable selection and in the countries included in regression model training and testing. At the cross-national level, the quantity and quality of a nation’s agricultural land were not predictive of either food security metric. We found mixed evidence that per-capita cereal production, per-hectare cereal yield, an aggregate governance metric, logistics performance, and extent of paid employment work were predictive of national food security. Household spending as measured by per-capita final consumption expenditure (HFCE) was consistently the strongest driver among those studied, alone explaining a median of 92% and 70% of variation (based on out-of-sample R 2 ) in GFSI and FI , respectively. The relative strength of HFCE as a predictor was observed for both response variables and was independent of the countries used for model training, the transformations applied to the explanatory variables prior to model training, and the variable selection technique used to specify multivariate regressions. The results of this cross-national analysis reinforce previous research supportive of a causal mechanism where, in the absence of exceptional local factors, an increase in income drives increase in food security. However, the strength of this effect varies depending on the countries included in regression model fitting. We demonstrate that using multiple response metrics, repeated random sampling of input data, and iterative variable selection facilitates a convergence of evidence approach to analyzing food security drivers.

42 ENGINEERING↗
DOE OSTI2026

Topology-driven compressive behavior of Inconel 718 lattice structures with Z-strut reinforcement fabricated by laser powder bed fusion

This study investigates the compressive deformation behavior and mechanical performance of Inconel 718 lattice structures fabricated by laser powder bed fusion (LPBF). Four unit-cell topologies—BCC, FCC, BCCZ, and FCCZ—were designed with a unit-cell size of 3 mm and fabricated under identical process conditions to isolate the effect of topology. Measured relative densities ranged from 14.65% to 17.72%. Compressive testing showed that Z-strut-reinforced topologies (BCCZ: 54.6 MPa; FCCZ: 80.2 MPa) exhibited higher strength than their unreinforced counterparts, which may be associated with mixed-mode deformation behavior enabled by the vertically aligned Z-struts. Finite element simulations and Digital Image Correlation (DIC) analysis support the observation of a transition from node-dominated deformation in BCC/FCC to mixed-mode deformation in BCCZ/FCCZ. These findings suggest that unit-cell topology is a key design variable for tailoring deformation mechanisms in LPBF lattice structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of Synthetic Parameters on Structure and Electrochemistry of High-Entropy Layered Oxide LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2

Here, this study explored a high-entropy layered oxide (HELO), LiNi 0.2 Co 0.2 Mn 0.2 Al 0.2 Fe 0.2 O 2 , prepared by coprecipitation followed by heat treatment. Coprecipitation yielded a kinetically favored product, and the subsequent heat treatment under various temperatures and times allowed tuning the material toward more thermodynamically favored structures. Refinement of X-ray powder diffraction (XRD) revealed that after 450 °C treatment, ~12% of the Ni 2+ in the structure was located within the lithium cation layer. After heat treatment at 600, 700, and 800 °C, there was a continued decrease of Ni 2+ in the lithium cation layer to 9.3, 6.3, and 3.7%, respectively. Longer heat treatment times at 800 °C decreased the level to 2.5%. Electrochemical behavior was evaluated by cyclic voltammetry, galvanostatic cycling, rate capability testing, and electrochemical impedance spectroscopy, where increased loaded voltage, functional capacity, rate capability, and decreased impedance were observed for samples treated at higher temperatures with lower cation mixing. X-ray absorption near edge spectroscopy (XANES) data indicated that the redox activity of Ni and Co was dominant in the electrochemistry, while the participation of Mn or Fe was minimal. The level of Ni oxidation state change between charge and discharge related to the heat treatment temperature where the samples with high cation mixing showed lower capacity consistent with some Ni 3+ in the transition metal layer inaccessible for electron transfer. Longer heat treatment times at 800 °C did not continue to provide a benefit in electrochemical function even with some additional reduction in cation mixing.

25 ENERGY STORAGE↗
DOE OSTI2020

Correlating Mechanical Sensitivity with Spin Transition in the Explosive Spin Crossover Complex [Fe(Htrz) 3 ] n [ClO 4 ] 2 n

Spin crossover complexes are known to undergo bond length, volume, and enthalpy changes during spin transition. In an explosive spin crossover complex, these changes could affect the mechanical and initiation sensitivity of the explosive and lead to the development of a new class of sensitivity switchable materials. To explore this relationship, the well-known spin crossover compound [Fe(Htrz) 3 ] n [ClO 4 ] 2n (1) was re-evaluated for its explosive properties, and its mechanical impact sensitivity was correlated to spin transition. A variable temperature impact test was developed and used to evaluate the impact sensitivity of 1 in the low spin (LS, S = 0), thermally accessed high spin (HS, S = 2), and mixed LS and HS states. For comparison, the structurally similar Ni compound, [Ni(Htrz) 3 ] n [ClO 4 ] 2n (2), which does not undergo a spin transition at accessible temperatures, was synthesized and characterized, and its explosive properties and variable temperature impact sensitivity measured. These results reveal a correlation between impact sensitivity and spin transition, where 1 exhibits lower impact sensitivity in the LS state and increases in sensitivity upon transition to the HS state. Here, density functional theory was used to predict structural changes that occur upon spin transition that correlate to the change in sensitivity. This demonstrates, for the first time, an explosive spin crossover compound (ExSCO) that exhibits switchable impact sensitivity with a fully reversible internal switching mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Fully Additively Manufactured Wetted Foam Capsules for Inertial Confinement Fusion

In the pursuit of realizing reliable clean energy generation via inertial confinement fusion (ICF), wetted foam (WF) capsule targets have long been coveted due to their potential to simplify the target fielding process and suppress hydrodynamic instabilities and material mixing that limit achievable energy output, yet producing and deploying a WF target has proven challenging. Here, in this work, we demonstrate the design, fabrication, metrology, and testing of fully additively manufactured (AM) foam-lined capsules using two-photon polymerization (2PP) for ICF. We successfully fielded an AM polymeric foam capsule with a 3-mm outer diameter, a nominally 15-µm-thick solid outer layer, a 120-µm-thick inner foam layer, and a 250-µm outer diameter copper fill tube on the National Ignition Facility for a polar direct-drive shot, and we showcase deuterium wetting of the capsule foam layer inside an ignition target proofing station. Our exploration showed that 2PP can produce fieldable targets with complex geometries and potentially shorten the design iteration turnaround time and the overall target fabrication time.

Target↗
DOE OSTI2022

Cortical Proteins and Individual Differences in Cognitive Resilience in Older Adults

Background and objectives: Cognitive resilience is a well-recognized concept, but knowledge gaps about its underlying mechanisms have made it difficult to develop instruments that identify older adults with high or low resilience. We tested whether aggregating cortical peptides associated with cognitive resilience into an index can identify adults with higher or lower cognitive resilience. Methods: We used data from 1,192 older decedents, including annual clinical testing, indices of 10 Alzheimer disease (AD) and related dementia (ADRD) pathologies, and 226 proteotypic peptides measured in the dorsal lateral prefrontal cortex. We used linear mixed-effects models to identify peptides that were related to cognitive resilience (i.e., cognitive decline not explained by ADRD pathologies [false discovery rate <0.05]). We aggregated the expression levels of these resilience peptides into a person-specific cognitive resilience index and examined its association with AD clinical and pathologic phenotypes. Results: We constructed a resilience index from 52 of 226 peptides related to cognitive resilience. A higher index was associated with slower cognitive decline (estimate 0.05, SE 0.003, p < 0.001) and slower motor decline (estimate 0.005, SE 0.001, p < 0.001). Most resilience peptides (70%) were specific to cognitive decline, but 30% also provided resilience for motor decline. A higher index was also related to a lower burden of AD pathologies (odds ratio [OR] 0.41, SE 0.01, p < 0.001) and modified the association of AD pathology with cognition in that a higher index modified the negative effects of AD pathology on AD dementia proximate to death (OR 0.70, SE 0.14, p = 0.010). Up to 90% of cognitive resilience peptides were related to AD pathologic phenotypes. Discussion: Cortical proteins may provide some degree of cognitive resilience. These multifunctional proteins also seem to provide resilience to other AD clinical phenotypes and have independent associations with ADRD pathologies. Resilience proteins may be high-value therapeutic targets for drug discovery of interventions that maintain brain health in aging adults via multiple pathways.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) sea spray organic aerosol emissions – implementation in a global climate model and impacts on clouds

Sea spray aerosol is one of the major sources of atmospheric particulate matter globally. It has increasingly been recognized that organic matter derived from ocean biological precursors contributes significantly to the composition of submicron sea spray and may modify sea spray aerosol impacts on clouds and climate. This paper describes the implementation of the OCEANFILMS (Organic Compounds from Ecosystems to Aerosols: Natural Films and Interfaces via Langmuir Molecular Surfactants) parameterization for sea spray organic aerosol emissions in a global Earth system model, the Energy Exascale Earth System Model (E3SM). OCEANFILMS is a physically based model that links sea spray chemistry with ocean biogeochemistry using a Langmuir partitioning approach. We describe the implementation details of OCEANFILMS within E3SM, compare simulated aerosol fields with observations, and investigate impacts on simulated clouds and climate. Four sensitivity cases are tested, in which organic emissions either strictly add to or strictly replace sea salt emissions (in mass and number) and are either fully internally or fully externally mixed with sea salt. The simulation with internally mixed, added organics agrees reasonably well with observed seasonal cycles of organic matter in marine aerosol and has been selected as the default configuration of the E3SM. In this configuration, sea spray organic aerosol contributes an additional source of cloud condensation nuclei, adding up to 30 cm -3 to Southern Ocean boundary-layer cloud condensation nuclei concentrations (supersaturation = 0.1 %). The addition of this new aerosol source strengthens shortwave radiative cooling by clouds by -0.36 W m -2 in the global annual mean and contributes more than -3.5 W m -2 to summertime zonal mean cloud forcing in the Southern Ocean, with maximum zonal mean impacts of about -4 W m -2 around 50–60°S. This is consistent with a previous top-down, satellite-based empirical estimate of the radiative forcing by sea spray organic aerosol over the Southern Ocean. Through its mechanistic approach, OCEANFILMS offers a path towards improved understanding of the feedbacks between ocean biology, sea spray organic matter, and climate.

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

Fracture toughness evaluation for Zr-4 clad tubing structure with pellet inserts

Applying fracture mechanics approach to spent nuclear fuel (SNF) system reliability investigation is warranted due to the inherent flaws and hydride structures existed in a SNF system after nuclear reactor operation. However, none of the existing fracture toughness data deal with fuel cladding specific geometry or spent fuel material conditions, such as cladding structure with the pellet-inserts and the associated pellet clad mechanical interactions induced mixed-mode damage mechanisms. Thus, the development of an intrinsic fracture mechanics approach that is suitable for SNF materials is needed. Due to thin wall and small dimension of clad tubing structure, the spiral notch torsion test (SNTT) method of small specimen approach was used to estimate the clad tubing structure fracture toughness. The estimated fracture toughness for Zr-4 cladding with alumina-pellet inserts are presented in this report. For SNTT samples with a short or medium crack length, between 5.4-mm and 8-mm, the estimate JIQ upon fracture initiation for the baseline Zr-4 cladding is at 50 kJ/m2 with 2-sigma uncertainty of 3.26 kJ/m2, and the associated KIQ is at 67.46 MPa√m. For SNTT samples with a long crack length, around 13-mm, the crack initialization is deviated from that of the Mode-I tensile fracture and appears to be a mixed-mode fracture of Mode I – tensile stress and Mode III – out of plane shear stress; the estimated JMQ is at 18.9 kJ/m2, the associated KMQ is at 41.4 MPa√m.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comparing (stochastic-selection) ab initio multiple spawning with trajectory surface hopping for the photodynamics of cyclopropanone, fulvene, and dithiane

Ab Initio Multiple Spawning (AIMS) simulates the excited-state dynamics of molecular systems by representing nuclear wavepackets in a basis of coupled traveling Gaussian functions, called trajectory basis functions (TBFs). New TBFs are spawned when nuclear wavepackets enter regions of strong nonadiabaticity, permitting the description of non-Born–Oppenheimer processes. The spawning algorithm is simultaneously the blessing and the curse of the AIMS method: it allows for an accurate description of the transfer of nuclear amplitude between different electronic states, but it also dramatically increases the computational cost of the AIMS dynamics as all TBFs are coupled. Recently, a strategy coined stochastic-selection AIMS (SSAIMS) was devised to limit the ever-growing number of TBFs and tested on simple molecules. In this work, we use the photodynamics of three different molecules—cyclopropanone, fulvene, and 1,2-dithiane—to investigate (i) the potential of SSAIMS to reproduce reference AIMS results for challenging nonadiabatic dynamics, (ii) the compromise achieved by SSAIMS in obtaining accurate results while using the smallest average number of TBFs as possible, and (iii) the performance of SSAIMS in comparison to the mixed quantum/classical method trajectory surface hopping (TSH)—both in terms of its accuracy and computational cost. We show that SSAIMS can accurately reproduce the AIMS results for the three molecules considered at a much cheaper computational cost, often close to that of TSH. We deduce from these tests that an overlap-based criterion for the stochastic-selection process leads to the best agreement with the reference AIMS dynamics for the smallest average number of TBFs.

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

ExoReL{sup R}: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as Wide-Field InfraRed Survey Telescope, Habitable Exoplanet Imaging Mission, and Large Ultra-Violet/Optical/InfraRed Surveyor will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations, we introduce ExoReL{sup R} (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically nonuniform volume mixing ratio (VMR) profile of water and ammonia, and uses it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply ExoReL{sup R} on three test cases: two exoplanets (υ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the signal-to-noise ratio of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model to give a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the nonuniform VMR profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Strategically Modified Ligand Incorporating Mixed Phosphonate and Carboxylate Groups to Enhance Performance in All-Iron Redox Flow Batteries

Iron redox flow batteries (Fe-RFBs) hold significant promise for achieving cost-effectiveness and utilizing abundant materials for stationary energy storage applications. Here, a design of a novel Fe complex utilizing a nitrogenous phosphonate/carboxylate mixed ligand, N,N-Bis(phosphonomethyl)glycine (BMPG), is presented to achieve high performance Fe anolyte. Compared to its all-phosphonate form, nitrilotri(methylphosphonic acid) (NTMPA), the new complex Fe(BPMG) 2 demonstrates a negatively shifted redox potential, resulting in ≈0.07 V (≈10%) increase in battery output voltage. Full battery testing paired with ferrocyanide catholyte demonstrates stable cycling (capacity degradation <0.0001%/cycle) over 730 consecutive charge/discharge cycles with Coulombic Efficiency of 100% at a current density of 20 mA cm -2 under near neutral pH (≈8). Of particular interest, density functional theory (DFT) studies and operando Raman measurements provide strong evidence supporting a molecular structure in BPMG, which reveals the mixed phosphonate/carboxylate groups in BPMG maintain the octahedral coordination of the Fe ion center with phosphonates exclusively, while leaving the carboxylate unbound for both Fe(II) and Fe(III) complexes. This structural similarity between BPMG-based Fe(II) and Fe(III) complexes effectively mitigates the slow redox reaction kinetics observed in Fe(NTMPA) 2 anolyte, where significant ligand reorientation occurs between Fe(II) and Fe(III) complexes.

25 ENERGY STORAGE↗
DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗