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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Application of community data to surface complexation modeling framework development: Iron oxide protolysis

This study presents a comprehensive community data-driven surface complexation modeling framework for simulating potentiometric titration of mineral surfaces. Compiled community data for ferrihydrite, goethite, hematite, and magnetite are fit to produce representative protolysis constants that can reproduce potentiometric titration data collected from multiple literature sources. Using this framework, the impact of surface complexation model type and surface site density (SSD) on the fit quality and protolysis constants can be readily evaluated. For example, the non-electrostatic model yielded a poor data fit compared to diffuse double layer model and constant capacitance models due to the absence of known surface charge effects. Regardless of the choice of iron oxide mineral, pK a1 decreased with increasing SSD while the opposite tendency was observed for pK a2 . This newly developed framework demonstrates a method to reconcile community data-wide potentiometric titration data using Findable, Accessible, Interoperable, Reusable data principles to produce mineral protolysis constants that improve robustness of surface complexation models for applications in metal sorption and reactive transport modeling. The framework is readily expandable (as community data increase) and extensible (as the number of minerals increase). The framework provides a path forward for developing self-consistent, comprehensive, and updateable surface complexation databases for surface complexation and reactive transport modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Adsorption of REEs to Kaolinite via Ion Exchange and Surface Complexation as a Function of Water Chemistry

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH < 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7–8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH > 5 but does not affect adsorption at pH < 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH < ∼6 and inner-sphere surface complexation to edge sites at pH > ∼6. Equilibrium constants for surface complexation increase in the order of Yb > Dy > Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗
DOE OSTI2023

Mechanisms of Zn removal from water by amorphous geopolymer: Molecular-level insights from X-ray absorption spectroscopy, isotope fractionation, and surface complexation modeling

Porous geopolymers have attracted widespread attention as promising heavy metal adsorbents that can be synthesized from aluminosilicate solid wastes. However, the precise microstructural evidence for adsorbed heavy metals on geopolymers remains unclear due to the insensitivity of conventional characterization techniques on minerals with amorphous structure and surface disorder. Batch adsorption and column experiments coupled with X-ray absorption spectroscopy (XAS), Zn stable isotope, and surface complexation model (SCM) were employed to reveal the Zn removal mechanisms with coal fly ash porous geopolymer (CFAPG) at a molecular scale. The macroscopic kinetic and isothermal adsorption of Zn on CFAPG were well described by the pseudo-second-order model and Bi_Langmuir equation, respectively, indicating the presence of abundant heterogeneous active sites on the CFAPG surface. Further, two types of active sites on the CFAPG surface were identified by XAS coupled with Zn isotopes in batch experiments at pH <= 6.0: one is pH-dependent and associated with tetrahedral zinc coordi-nation, and the other is pH-insensitive and associated with octahedral zinc coordination; these sites were confirmed by the bidentate SCM as the variable charge site (surface complexation, >S-OH) and the permanent negative charge site (cation exchange, >X - ), respectively. Furthermore, the important contribution of surface co -precipitation besides surface complexation and cation exchange to the Zn adsorption on CFAPG was identified by XAS coupled with SCM in a flow-through column experiment at pH >6.0. These investigations provide a systemic understanding of the Zn adsorption mechanisms on CFAPG and an SCM reference for the application and prediction of geopolymers in heavy metal-contaminated water remediations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Goethite and Hematite Nucleation and Growth from Ferrihydrite: Effects of Oxyanion Surface Complexes

The presence of oxyanions, such as nitrate (NO 3 – ) and phosphate (PO 4 3– ), regulates the nucleation and growth of goethite (Gt) and hematite (Hm) during the transformation of ferrihydrite (Fh). Our previous studies showed that oxyanion surface complexes control the rate and pathway of Fh transformation to Gt and Hm. However, how oxyanion surface complexes control the mechanism of Gt and Hm nucleation and growth during the Fh transformation is still unclear. Here, we used synchrotron scattering methods and cryogenic transmission electron microscopy to investigate the effects of NO 3 – outer-sphere complexes and PO 4 3– inner-sphere complexes on the mechanism of Gt and Hm formation from Fh. Our TEM results indicated that Gt particles form through a two-step model in which Fh particles first transform to Gt nanoparticles and then crystallographically align and grow to larger particles by oriented attachment (OA). In contrast, for the formation of Hm, imaging shows that Fh particles first aggregate and then transform to Hm through interface nucleation. This is consistent with our X-ray scattering results, which demonstrate that NO 3 – outer-sphere and PO 4 3– inner-sphere complexes promote the formation of Gt and Hm, respectively. These results have implications for understanding the coupled interactions of oxyanions and iron oxy-hydroxides in Earth-surface environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Tomographic optical emission spectroscopy of atmospheric pressure plasma interacting with complex surfaces

Plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and interfacing material properties. For example, guided streamers that transition to surface ionization waves (SIWs) and propagate over structured dielectrics experience field enhancements that can lead to localized increases in ionization rates and complex 3D configurations that are difficult to analyze. Investigating these configurations requires techniques than can provide a more complete 3D picture. To help address this capability gap, a tomographic optical emission spectroscopy (tomo-OES) diagnostic system has been developed at Sandia National Laboratories that can resolve SIWs. The system includes four intensified cameras that measure the angular projections of the plasma light emission through bandpass filters. A dot calibration target co-registers each angular projection to the same voxel grid and an algebraic reconstruction technique (ART) recovers the light intensity at each voxel. An atmospheric pressure plasma jet (APPJ), provided by Peter Bruggeman, has been investigated and representative results are shown in Figure 1. Here, a bandpass filter was used to isolate emission from the N 2 second positive system (SPS) at 337.1 nm to capture the transition of the streamer to SIW on a planar dielectric surface (relative permittivity 3.3) located 3 mm below the APPJ [3]. The surface wave velocity was 3.5x10 4 (m/s), consistent with measurements made by Steven Shannon. Characterization of this APPJ will support the group effort of standing up a reproducible APPJ across institutions for applications such as liquid treatment, catalysis, and plasma aided combustion. Future work will investigate non-planar surfaces and eventually develop tomographic laser-induced fluorescence (tomo-LIF) approaches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Distance-dependent dielectric constant at the calcite/electrolyte interface: Implication for surface complexation modeling

Hypothesis: The electrical double layer formed at the mineral/electrolyte interface is often modeled using mean-field approaches based on a continuum description of the solvent whose dielectric constant is assumed to decrease monotonically with decreasing distance to the surface. In contrast, molecular simulations show that the solvent polarizability oscillates near the surface similar to the water density profile - as shown previously, for example, by Bonthuis et al. (D.J. Bonthuis, S. Gekle, R.R. Netz, Dielectric Profile of Interfacial Water and its Effect on Double-Layer Capacitance, Phys Rev Lett 107(16) (2011) 166102). Here, we showed that molecular and mesoscale pictures agree by spatially averaging the dielectric constant obtained from molecular dynamics simulations over the distances relevant to the mean-field representation. In addition, the values of capacitances used to describe the electrical double layer in Surface Complexation Models (SCMs) of the mineral/electrolyte interface can be estimated using molecularly informed spatially averaged dielectric constants and positions of hydration layers. Experiments: First, we used molecular dynamics simulations to model the calcite 101¯4/electrolyte interface. Next, by using atomistic trajectories, we calculated the distance-dependent static dielectric constant and water density in the direction normal to the. Finally, we applied spatial compartmentalization consistent with the model of parallel-plate capacitors connected in series to estimate SCM capacitances. Findings: Computationally expensive simulations are required to determine the dielectric constant profile of interfacial water near the mineral surface. On the other hand, water density profiles are readily assessable from much shorter simulation trajectories. Our simulations confirmed that dielectric and water density oscillations at the interface are correlated. Here, we parametrized linear regression models to estimate the dielectric constant directly from the local water density. This is a significant computational shortcut compared to slowly converging calculations relying on total dipole moment fluctuations. The amplitude of the interfacial dielectric constant oscillation can exceed the dielectric constant of the bulk water, suggesting an ice-like frozen state, but only if there are no electrolyte ions. The interfacial accumulation of electrolyte ions causes a decrease in the dielectric constant due to the reduction of water density and re-orientation of water dipoles in ion hydration shells. Finally, we show how to use the computed dielectric properties to estimate SCM's capacitances.

58 GEOSCIENCES↗
DOE OSTI2024

Machine learning surrogates for surface complexation model of uranium sorption to oxides

Abstract The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

High-Entropy Surface Complex Stabilized LiCoO 2 Cathode

In this study, elevating the charge voltage of LiCoO 2 increases the energy density of batteries, which is highly enticing in energy storage implementation ranging from portable electronics to e-vehicles. However, hybrid redox reactions at high voltages facilitate oxygen evolution, electrolyte decomposition and irreversible phase change, and accordingly lead to rapid battery capacity decay. Here significantly improved high-voltage cycling stability of Mg-Al-Eu co-doped LiCoO 2 is demonstrated. It is found that element co-doping induces a near-surface high-entropy zone, including an innately thin disordered rock-salt shell and a dopant segregation surface. The high-entropy complex can effectively suppress oxygen evolution and near-surface structure deconstruction. The phase change reversibility between O3 and H1-3 and thermal stability of the cathode are greatly enhanced as well. As a result, the co-doped LiCoO 2 exhibits a remarkable cycling performance, retaining 86.3% and 72.0% of initial capacity over 800 and 2000 cycles, respectively, with a high cut-off voltage of 4.6 V. The feasible co-doping approach broadens the perspective for the development of stable lithium-ion batteries with high operating voltages.

25 ENERGY STORAGE↗
DOE OSTI2025

Complex surface topographic changes from explosive experiments at the Dry Alluvium Geology site, southern Nevada, United States

Understanding the surface topographic change that results from underground explosions is important for global security. Current techniques to relate the surface change to underground explosion characteristics usually involve assuming the earth has homogenous properties, leading to highly variable interpretations. Here we use an unoccupied aerial platform and a digital single lens reflex camera along with 200+ ground control points surveyed with a real-time kinematic global navigation satellite system to measure the surface topographic change resulting from two underground explosions at the Dry Alluvium Geology site in Yucca Flat, Nevada National Security Site, southern Nevada, United States. We find areas of 5–7 cm of subsidence that are not directly above the explosion source but rather 200–300 m away. For experiment DAG2, this zone is located south and west of the explosion, while for DAG4, there is a zone of subsidence located northeast of the explosion. In addition, late-time measurements show as much as 5 cm of horizontal change without measurable associated vertical change in the weeks following DAG4 but not DAG2. These indicate that the deformation resulting from underground chemical explosions can be very complex and bear little to no resemblance to predictions using half-space models. It is likely the tectonic environment plays a significant role in controlling the surface change, but the details are not fully understood.

58 GEOSCIENCES↗
DOE OSTI2024

Adsorption of Neodymium, Dysprosium, and Ytterbium to Goethite under Varying Aqueous Chemistry Conditions

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (<5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (>5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple-layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. An SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. Furthermore, this predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗
DOE OSTI2024

Adsorption of neodymium, dysprosium, and ytterbium to goethite under varying aqueous chemistry conditions [dataset]

The adsorption of rare earth elements (REEs) to iron oxides can regulate the mobility of REEs in the environment and is heavily influenced by water chemistry. This study utilized batch experiments to examine the adsorption of Nd, Dy, and Yb to goethite under varying pH, electrolyte (type and concentration), and concentrations of dissolved inorganic carbon and citrate. REE adsorption was strongly influenced by pH, with an increase from essentially no adsorption at pH 3.0 to nearly complete adsorption at pH 6.5 and higher. Citrate enhanced the adsorption of REEs at low pH (< 5.0), likely by forming goethite-REE-citrate ternary surface complexes. However, citrate inhibited the adsorption of REEs at higher pH (> 5.0) by forming aqueous REE-citrate complexes. Ionic strength had a small influence on REE adsorption, and the presence of dissolved inorganic carbon had no discernible effect. Equilibrium adsorption was interpreted with a triple layer surface complexation model (SCM). The selection of surface complexation reactions was guided by extended X-ray absorption fine structure spectra. A SCM with a single bidentate inner-sphere surface complexation reaction for Nd and two inner-sphere surface complexation reactions (one monodentate and one bidentate reaction) for Dy and Yb effectively simulated adsorption across a broad range of conditions in the absence of citrate. Accounting for the effects of citrate on REE adsorption required the addition of up to two ternary REE-citrate-goethite surface complexes. The SCM can enable predictions of REE transport in subsurface environments that have goethite as an important adsorbent mineral. This predictive capability could contribute to identifying potential REE sources and facilitating efficient extraction of REEs.

58 GEOSCIENCES↗
DOE OSTI2025

Machine‐Learning‐Driven Exploration of Surface Reconstructions of Reduced Rutile TiO 2

Abstract Titanium dioxide (TiO 2 ) is widely used as a catalyst support due to its stability, tunable electronic properties, and surface oxygen vacancies, which are crucial for catalytic processes such as the reverse water‐gas shift (RWGS) reaction. Reduced TiO 2 surfaces undergo complex surface reconstructions that endow unique properties but are computationally challenging to describe. In this study, we utilize machine‐learning interatomic potentials (MLIPs) integrated with an active‐learning workflow to efficiently explore reduced rutile TiO 2 surfaces. This approach enabled the prediction of a phase diagram as a function of oxygen chemical potential, revealing a variety of reconstructed phases, including a previously unreported subsurface shear plane structure. We further investigate the electronic properties of these surfaces and validate our results by comparing experimental and theoretical high‐resolution transmission electron microscopy (HRTEM). Our findings provide new insights into how extreme surface reductions influence the structural and electronic properties of TiO 2 , with potential implications for catalyst design.

Lee, Yonghyuk [Chemistry and Biochemistry Universi↗
DOE OSTI2025

Machine‐Learning‐Driven Exploration of Surface Reconstructions of Reduced Rutile TiO 2

Titanium dioxide (TiO 2 ) is widely used as a catalyst support due to its stability, tunable electronic properties, and surface oxygen vacancies, which are crucial for catalytic processes such as the reverse water-gas shift (RWGS) reaction. Reduced TiO 2 surfaces undergo complex surface reconstructions that endow unique properties but are computationally challenging to describe. In this study, we utilize machine-learning interatomic potentials (MLIPs) integrated with an active-learning workflow to efficiently explore reduced rutile TiO 2 surfaces. This approach enabled the prediction of a phase diagram as a function of oxygen chemical potential, revealing a variety of reconstructed phases, including a previously unreported subsurface shear plane structure. We further investigate the electronic properties of these surfaces and validate our results by comparing experimental and theoretical high-resolution transmission electron microscopy (HRTEM). Our findings provide new insights into how extreme surface reductions influence the structural and electronic properties of TiO 2 , with potential implications for catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗
DOE OSTI2025

Adsorption of Rare Earth Elements to Kaolinite [dataset]

Rare earth elements (REEs) are critical components of modern technology behind renewable energy, transportation, and electronics but have a limited current supply. A substantial portion of global REE production relies on ion adsorption deposits. A high abundance of kaolinite in REE enrichment zones within these deposits suggests that kaolinite controls the subsurface migration of REEs. This study aimed to improve the current understanding of REE binding to kaolinite under varying water chemistry conditions. We conducted batch experiments with kaolinite (KGa-2) and three REEs (Nd, Dy, and Yb) at varying pH, electrolyte concentration, dissolved inorganic carbon (DIC), low molecular weight organic acids (citric and oxalic acids), and total REE concentration conditions. Increasing electrolyte concentration inhibits REE adsorption at pH 7, suggesting that ion exchange contributes to adsorption at these pH values. DIC affects adsorption above pH 7−8 by forming strong aqueous complexes with heavy REEs. Citric acid decreases REE adsorption via aqueous complexation of REEs at pH 5 but does not affect adsorption at pH 5. The surface complexation model captures the main adsorption trends with two mechanisms: ion exchange on basal planes at pH ∼6 and inner-sphere surface complexation to edge sites at pH ∼6. Equilibrium constants for surface complexation increase in the order of Yb Dy Nd, indicating a higher strength of adsorption for heavy REEs. This study demonstrates how water chemistry conditions control the adsorption mechanisms that may determine the mobility of REEs in subsurface environments rich in kaolinite.

58 GEOSCIENCES↗