Search NASA⌕ Search

SEARCH · Search NASA

Results for “frequency selective surfaces”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Investigation of the reaction mechanism of the hydrodeoxygenation of propionic acid over a Rh(1 1 1) surface: A first principles study

Microkinetic models based on first principles calculations have been used to study the vapor and liquid phase hydrodeoxygenation of propionic acid on a Rh(111) surface. Calculations suggest that both decarboxylation and decarbonylation do not occur at an appreciable rate under all reaction environments. Propanol and propionaldehyde are the main products on this surface and they are produced at similar rates in both vapor and liquid phase environments. While a condensed phase can shift the reaction rate, the dominant pathways and selectivity towards the various products are hardly affected. At 473 K, the turnover frequency is increased by about a factor of 1.5 in liquid water relative to the gas phase. In liquid 1,4-dioxane, the turnover frequency is also slightly increased relative to the gas phase. Here, given the uncertainty in Rh cavity radius in the liquid phase calculations, computations with different cavity radii have been performed. With larger Rh cavity radius, the promotional effect of the solvents on the turnover frequency becomes more significant, while practically no changes are observed for a smaller cavity radius.

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

Spectroscopic Probe Molecule Selection Using Quantum Theory, First-Principles Calculations, and Machine Learning

Probe molecule vibrational spectra have a long history of being used to characterize materials including metals, oxides, metal-organic frameworks, and even human proteins. Furthermore, recent advances in machine learning have enabled computationally generated spectra to aid in detailed characterization of complex surfaces with probe molecules. Despite widespread use of probe molecules, the science of probe molecule selection is underdeveloped. Here, we develop physical concepts, including orbital interaction energy and the energy overlap integral, to explain and predict the ability of probe molecules to discriminate structural descriptors. We resolve the crystal orbital overlap population (COOP) to specific molecular orbitals and quantify their bonding character, which directly influences vibrational frequencies. Using only a single adsorbate calculation from density function theory (DFT), we compute the interaction energy of individual adsorbate molecular orbitals with adsorption site atomic orbitals across many different sites. Combining the molecular orbital resolved COOP and changes in orbital interaction energy enables probe molecule selection for improved discrimination of various sites. We demonstrate these concepts by comparing the predicted effectiveness of carbon monoxide (CO), nitric oxide (NO), and ethylene (C 2 H 4 ) to probe Pt adsorption sites. Finally, using a previously developed machine learning framework, we show that models trained on hundreds of thousand C 2 H 4 spectra, computed from DFT, which regress surface binding-type and generalized coordination number (GCN), outperform those trained using CO and NO spectra. Lastly, a python package, pDOS_overlap, for implementing the electron density based analysis on any combination of adsorbates and materials, is also made available.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Discovery of a Hybrid System for Photocatalytic CO 2 Reduction via Attachment of a Molecular Cobalt-Quaterpyridine Complex to a Crystalline Carbon Nitride

While recent reports have demonstrated the attachment of molecular catalysts to amorphous, graphitic carbon nitrides (g-CN) for light-driven CO 2 reduction, approaches to the utilization of crystalline carbon nitrides have remained undiscovered. Herein, a functional hybrid photocatalyst system has been found using a crystalline carbon nitride semiconductor, poly(triazine imide) lithium chloride (PTI-LiCl), with a surface-attached CoCl 2 (qpy-Ph-COOH) catalyst for CO 2 reduction. The molecular catalyst attaches to PTI-LiCl at concentrations from 0.10 to 4.30 wt % and exhibits ∼96% selectivity for CO production in a CO 2 -saturated, aqueous 0.5 M KHCO 3 solution. Optimal loadings were found to be within 0.42–1.04 wt % with rates between 1,400 and 1,550 μmol CO/g·h at an irradiance of 172 mW/cm 2 (λ = 390 nm) and apparent quantum yields of ∼2%. This optimized loading is postulated to represent a balance between maximal turnover frequency (TOF; 300+ h –1 ) and excess catalyst that can limit excited-electron lifetimes, as probed via transient absorption spectroscopy. An increase in the incident irradiance yields a concomitant increase in the TOFs and CO rates only for the higher catalyst loadings, reaching up to 2,149 μmol CO/g·h with a more efficient use of the catalyst surface capacity. The lower catalyst loadings, by comparison, already function at maximal TOFs. Higher surface loadings are also found to help mitigate deactivation of the molecular catalysts during extended catalytic testing (>24 h) owing to the greater net surface capacity for CO 2 reduction, thus representing an effective strategy to extend lifetime. The hybrid particles can be deposited onto an FTO substrate to yield ∼60% Faradaic efficiency for photoelectrochemical CO production at −1.2 V vs Ag/AgCl bias. In conclusion, these results demonstrate the synergistic combination of a crystalline carbon nitride with a molecular catalyst that achieves among the highest known rates in carbon-nitride systems for the light-driven CO 2 reduction to CO in aqueous solution with >95% selectivity.

CO2 reduction↗
DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗
DOE OSTI2021

Complex Formation and Dissociation Dynamics on Amorphous Silica Surfaces

Benzene complex formation and dissociation dynamics with silanols on the amorphous silica surfaces of nanoporous SiO 2 , from a benzene/carbon tetrachloride solution, were measured by the growth of off-diagonal peaks in the two dimensional infrared (2D IR) chemical exchange spectrum of the isolated Si-OD stretch. The presence of two types of isolated silanols, referred to as type I and II, was revealed, with dissociation time constants of 82 ps and 4.0 ps for type I and II complexes, respectively. The type I silanols are associated with the main IR absorption feature in the Si-OD stretching region, while the type II silanols give rise to a broader shoulder to lower frequency. Polarization selective pump-probe (PSPP) measurements provided the vibrational lifetimes and orientational relaxation rates of the two silanols in the CCl 4 (free) and benzene (complex) environments. The type II silanols constitute roughly 30% of the isolated silanol population and exhibit a substantially faster rate of vibrational relaxation, making the type I dynamics the dominant contribution to the PSPP and 2D IR signals. From the measured dissociation times, the enthalpies of formation for the two surface complexes were obtained; the formation of the type I complex being significantly more exothermic. Furthermore, as the type II site is preferentially removed from the amorphous silica surface with increasing activation temperature, the results provide a reasonable explanation for the increased exothermicity of benzene adsorption on silica with increasing activation temperature in previous calorimetry experiments.

14 SOLAR ENERGY↗
DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Revealing the Predominant Surface Facets of Rough Cu Electrodes under Electrochemical Conditions

Metal electrodes with rough surfaces are frequently found to convert CO or CO 2 to hydrocarbons and oxygenates with high selectivity and at high reaction rates in comparison with their smooth counterparts. The atomic-level morphology of a rough electrode is likely one key factor responsible for its comparatively high catalytic selectivity and activity. However, few methods are capable of probing the atomic-level structure of rough metal electrodes under electrocatalytic conditions. As a result, the nuances in the atomic-level surface morphology that control the catalytic characteristics of these electrodes have remained largely unexplored. Because the C≡O stretching frequency of atop-bound CO (CO atop ) depends on the coordination of the underlying metal atom, the IR spectrum of this reaction intermediate on the copper electrode could, in principle, provide structural information about the catalytic surface during electrolysis. However, other effects, such as dynamic dipole coupling, easily obscure the dependence of the frequency on the surface morphology. Further, in the limit of low CO atop coverage, where coupling effects are small, the C≡O stretching frequencies of CO atop on Cu(111) and Cu(100) facets are virtually identical. Therefore, on the basis of the C≡O stretching frequency, it is not straightforward to distinguish between these two ubiquitous surface facets, which exhibit vastly different CO reduction activities. Herein, we show that key features of the atomic-level surface morphology of rough copper electrodes can be inferred from the potential dependence of the line shape of the C≡O stretching band of CO atop . Specifically, we compared two types of rough copper thin-film electrodes that are routinely employed in the context of surface-enhanced infrared absorption spectroscopy (SEIRAS). We found that copper films that are electrochemically deposited on Si-supported Au films (CuAu–Si) are poor catalysts for the reduction of CO to ethylene in comparison to copper films (Cu–Si) that are electrolessly deposited onto Si crystals. As quantified by differential electrochemical mass spectrometry (DEMS), the onset potential for ethylene is ~200 ± 65 mV more cathodic for CuAu–Si than that for Cu–Si. To reveal the origin of the disparate catalytic properties of Cu–Si and CuAu–Si, we probed the surfaces of the electrodes with cyclic voltammetry (CV) and SEIRAS. The CV characterization suggests that the (111) surface facet predominates on CuAu–Si, whereas the (100) facet is more common on Cu–Si. SEIRAS reveals that the line shape of the C≡O stretching of CO atop is composed of two bands that are attributable to CO atop on terrace and defect sites. The different surface structures manifest themselves in the form of starkly different potential dependences of the line shape of the C≡O stretching mode of CO atop on the two types of electrodes. With a simple Boltzmann model that considers the different adsorption energies of CO atop on terrace and defect sites, and the resulting CO atop populations on terrace and defect sites, we deduced that the observed electrode-specific potential dependence of the line shape is consistent with the presence of different predominant terrace sites on the two types of films. This strategy for assessing the atomic-level morphology is not restricted to SEIRAS but could also be applied to the C≡O stretching bands recorded with surface-enhanced Raman spectroscopy (SERS), which is suitable for probing a wide range of rough copper electrodes. Therefore, with this work, we establish the potential dependence of the C≡O stretching band of CO atop as a probe of the atomic-level surface structure of rough metal electrodes under electrochemical conditions. When it is coupled with complementary techniques, this methodology provides essential structural information for further improvement in the reaction selectivity of rough metal electrodes.

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

Topological nanospaser

We propose a nanospaser made of an achiral plasmonic–metal nanodisk and a two-dimensional chiral gain medium – a monolayer nanoflake of a transition-metal dichalcogenide (TMDC). When one valley of the TMDC is selectively pumped (e.g. by a circular-polarized radiation), the spaser (surface plasmon amplification by stimulated emission of radiation) generates a mode carrying a topological chiral charge that matches that of the gain valley. There is another, chirally mismatched, time-reversed mode with exactly the same frequency but the opposite topological charge; it is actively suppressed by the gain saturation and never generates, leading to a strong topological protection for the generating matched mode. This topological spaser is promising for use in nano-optics and nanospectroscopy in the near field especially in applications to biomolecules that are typically chiral. Another potential application is a chiral nanolabel for biomedical applications emitting in the far field an intense circularly polarized coherent radiation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding Self-Assembly and the Stabilization of Liquid/Liquid Interfaces: The Importance of Ligand Tail Branching and Oil-Phase Solvation

Organophosphorus-based ligands represent a versatile set of solvent extraction reagents whose chemical makeup plays an important role in extraction mechanism. We hypothesize that the branching of the extractant hydrophobic tail and its oil-phase solvation affect the liquid/liquid interfacial structure. Understanding the structure mediated adsorption and interfacial ordering becomes key in designing ligands with enhanced selectivity and efficiency for targeted extractions. We employed vibrational sum frequency generation spectroscopy and interfacial tension measurements to extract thermodynamic adsorption energies, map interfacial ordering, and rationalize disparate behaviors of model di-(2-ethylhexyl) phosphoric acid and dioctyl phosphoric acid ligands at the hexadecane water interface. With increased surface loading, ligands with branched hydrophobic tails formed stable interfaces at much lower concentrations than those observed for ligands with linear alkyl tails. The lack of an oil phase and associated solvation results in markedly different interfacial properties, and thus measurements made at air/liquid surfaces cannot be assumed to correlate with the processes occurring at buried liquid/liquid interfaces. Here, we attribute these differences in the surface mediated self-assembly to key variations in hydrophobic interactions and tail solvation taking place in the oil phase demonstrating that interactions in both the polar and nonpolar phases are essential to understand self-assembly and function.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Method for electrochemical roughening of thin film electrodes

The present invention relates to surface roughening methods and more particularly to a method for electrochemical roughening of thin film macro- and micro-electrodes. In one embodiment, an electrochemical etch template is formed comprising polymer particles adsorbed on a surface of a substrate to be roughened, followed by electrochemically etching of exposed regions of the substrate between the polymer particles in the electrochemical etch template so as to selectively roughen the surface of the substrate. In another embodiment, a surface of the electrode is immersed in either a adsorbing acidic solution, such as sulfuric acid, or a non-adsorbing acidic solution, such as perchloric acid, followed by electrochemically pulse etching the surface of the substrate at a narrow frequency range for adsorbing acidic solutions, or at a wide frequency range for non-adsorbing acidic solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Single-Atom Manganese-Based Catalysts for the Oxidative Dehydrogenation of Propane

Combinatorial screening of 150 supported metal oxide (manganese and additives) catalysts was carried out via a high-throughput synthesis platform and parallel reactors for the oxidative dehydrogenation (ODH) of propane to propylene. Specifically, an organomanganese (0.05-2.5 Mn atoms/nm 2 ) complex was grafted on metal oxide supports (Al 2 O 3 , SiO 2 , TiO 2 , and ZrO 2 ) premodified with either Lewis acid (Al, Ti, Zn, and Zr) or redox-active (Cu, Cr, Ga Ni, V) additives at various surface coverages (25, 50, and 75%). Catalysts were characterized by high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Raman spectroscopy, and UV-vis spectroscopy. Catalysts 0.05 Mn/V(50%)/Al 2 O 3 and 0.05 Mn/Ni(50%)/ZrO 2 showed the highest combined propane conversion and propylene selectivities (31/41% and 15/85%), with excellent stability at 500 degrees C for 25 h. The presence of Ni in Mn/Ni/ZrO 2 resulted in a 6-fold increase in turnover frequency (TOF) over the Mn/ZrO 2 . HRTEM identified single Mn atoms after 500 degrees C heat treatment. For the Mn/Ni/ZrO 2 system, Mn was incorporated into the support lattice due to the similar ionic radius of Mn 2+ and Zr 4+ , which was also enhanced by the presence of Ni. For the Mn/V/Al 2 O 3 system, highly active MnO was prevalent as observed by Raman. Both V and Mn contributed to an increase in mutual dispersion, but both species remained on the surface. Finally, it is proposed that the highly dispersed atom and interactions between Mn with either Ni or V are responsible for the ODH performance and stability.

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

Controlled removal of hydrogen atoms from H-terminated silicon surfaces

The controlled formation of dangling bond structures on a H-terminated silicon surface is the first step in an atomically precise method of fabrication of silicon quantum electronic devices. An ultrahigh vacuum scanning tunneling microscope (STM) tip is used to selectively desorb hydrogen atoms from a Si(100)-2x1:H surface by injecting electrons with the sample held at a positive bias voltage. The authors propose a lithography method that allows the STM to operate under negative bias imaging conditions and simultaneously desorb H atoms as required. A high frequency signal is added to the negative bias voltage to deliver the required energy for hydrogen removal. The resulting current at this frequency and its harmonics are filtered to minimize their effect on the operation of the STM’s feedback control loop. The authors show that the chance of tip-sample crash during the lithography process is reduced by employing this method. They also demonstrate that this approach offers a significant potential for controlled and precise removal of H atoms from a H-terminated silicon surface and thus may be used for the fabrication of practical silicon-based atomic-scale devices.

42 ENGINEERING↗
DOE OSTI2024

Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Coherent spin wave excitation with radio-frequency spin–orbit torque

Spin waves, collective perturbations of magnetic moments, are both fundamental probes for magnetic physics and promising candidates for energy-efficient signal processing and computation. Traditionally, coherent propagating spin waves have been generated by radio frequency (RF) inductive Oersted fields from current-carrying electrodes. An alternative mechanism, spin–orbit torque (SOT), offers more localized excitation through interfacial spin accumulation but has been mostly limited to DC to kHz frequencies. SOT driven by RF currents, with potentially enhanced pumping efficiency and unique spin dynamics, remains largely unexplored, especially in magnetic insulators. Here, we conduct a comprehensive theoretical and computational investigation into the generation of coherent spin waves via RF-SOT in the prototypical yttrium iron garnet. We characterize the excitation of forward volume, backward volume, and surface modes in both linear and nonlinear regimes, employing single and interdigitated electrode configurations. We reveal and explain several unique and surprising features of RF-SOT compared to inductive excitation, including higher efficiency, distinct mode selectivity, and directional symmetry, a ~ $3π/4$ phase offset, reduced anharmonic distortion in the nonlinear regime, and the absence of second harmonic generation. These insights position RF-SOT as a promising new mechanism for future magnonic and spintronic applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Adsorption of hydroxamic acid ligands for improved extraction of rare earth elements from monazite ores

Efficient separation of rare earth element (REE) ores via froth flotation requires the development of novel ligands with enhanced adsorption capacity and selectivity. To realize these advances, understanding the mechanisms underlying interactions between the ligand and mineral surfaces is essential. This study systematically evaluates the adsorption behavior of alkyl- and aromatic alkyl-substituted hydroxamic acid ligands on monazite surfaces using complementary spectroscopic techniques, including UV–visible (UV–vis) spectroscopy, Raman spectroscopy, infrared spectroscopy, and vibrational sum frequency generation (SFG) spectroscopy, together with the ab initio molecular dynamics (AIMD) simulations. Among the studied ligands, octanohydroxamic acid (OHA) and 4-ethoxy-N,2-dihydroxybenzamide (EDHBA) exhibit high adsorption capacity under basic pH (8–10) by forming multilayers on the surface. OHA has a higher equilibrium adsorption capacity compared to EDHBA, but it forms a less stable multilayer susceptible to disruption in the presence of interfering ions. AIMD results show that OHA adopts a single stable chelating geometry, while EDHBA exhibits multiple binding modes involving distinct interactions with La surface atoms and phosphate-bound oxygens, resulting in more complex adsorption kinetics. The variations in surface binding and intermolecular interactions observed between alkyl and aromatic molecules influence the differences in adsorption kinetics, equilibrium adsorption capacities on the mineral surface, and their flotation performance. This work provides valuable insight into the adsorption mechanism of ligands at mineral interfaces, which is crucial for guiding the design of new ligands with enhanced separation performance.

Zhou, Muchu [ORNL] (ORCID:0000000182650215)↗
DOE OSTI2021

Search for Infrasound Signals in InSight Data Using Coupled Pressure/Ground Deformation Methods

The unprecedented quality and sampling rate of seismometer and pressure sensors of the InSight Mars mission allow us to investigate infrasound through its pressure and ground deformation signals. This study focuses on compliance effects induced by acoustic waves propagating almost horizontally close to the surface. The compliance of acoustic waves is first estimated using the compliance estimates from pressure perturbations moving at wind speed. Then, a marker of compliance events is used to detect events of ground deformation induced by pressure variations, in three frequency bands from 0.4 to 3.2 Hz, from InSight sol 180 to 690. Additional selection criteria are imposed on the detected events to focus on acoustic waves and to remove various noise sources (e.g., wind effects or seismometer artifacts). After an automated selection, the visual inspection of the records allows us to validate two infrasound candidates that cannot be related to pressure perturbations moving at wind speed nor to known noise sources. For our highest quality infrasound candidate, the relation between this event and a convective vortex occuring 10 s later is tested. The azimuth of the vortex position at the time of infrasound detection is not consistent with the arrival azimuth of the suspected infrasound inferred from the polarization of seismometer records, thus the link between these two phenomena cannot be demonstrated. Further investigations would require a better understanding of wind-related noise impacting InSight sensors and of the effects of lateral variations of subsurface mechanical properties on the ground deformations induced by atmospheric pressure variations.

58 GEOSCIENCES↗
DOE OSTI2026

Heterobimetallic Iridium-Niobia Catalyst for Efficient and Selective Methane Ammonia Reforming

A Surface OrganoMetallic Chemistry (SOMC) approach, leveraging a molecularly defined heterobimetallic niobium–iridium complex, was used to prepare a mesoporous SBA-15 silica-supported Ir-NbOx catalyst. The resulting Ir-NbOx/SiO2 catalyst exhibited excellent catalytic performance in selective methane/ammonia reforming. Specifically, the Ir-NbOx/SiO2 catalyst showed significantly higher activity (turnover frequency 8.5 s–1), selectivity (75%), and stability than the Ir/SiO2 analog, whereas the NbOx/SiO2 counterpart was almost inactive. This contrasts with ethane/ammonia reforming via C–C cleavage, for which the bimetallic Ir-NbOx/SiO2 was less active than Ir/SiO2, demonstrating tuned selectivity toward C–H activation rather than C–C cleavage due to the Ir/NbOx synergy. Importantly, an Ir-NbOx/SiO2 reference catalyst, prepared by conventional impregnation/calcination/reduction steps, was found to be inactive, highlighting the value of the SOMC catalyst preparation approach using well-defined heterobimetallic precursors. These results represent a significant advance over existing catalysts due to the atomic-scale synergy between Ir and NbOx sites, enabling access to activity and selectivity regimes inaccessible to monometallic analogs.

Wu, Jiachun↗
DOE OSTI2026

Seismic Elastic Double-Beam Characterization of Faults and Fractures for CO₂ Storage Site Selection

Site characterization for underground injection and storage of gigatonne-scale CO₂ requires reliable and cost-effective methods to detect and characterize faults and fractures and to assess their stress state and fault activation potential. This is critical, as wastewater injection and disposal have been shown to activate faults and induce earthquakes, and CO₂ leakage remains a key concern for long-term storage. In this project, we developed seismic methods to detect and characterize large-scale sedimentary and crystalline basement faults and associated small-scale fractures below conventional seismic imaging resolution using multicomponent (9C) surface seismic data. Machine learning was used to automatically interpret large-scale faults, providing key information for estimating the maximum magnitude of potential induced earthquakes. High-fidelity imaging was achieved by exploiting redundancy across multiple elastic wave modes, where independent images from different modes and frequencies cross-validate each other. We also used our nonlinear signal comparison (NLSC) method for ground roll removal, improving data quality in complex near-surface conditions. The methods were validated using field data acquired in central Montana. Results show that basement faults extend into the sedimentary section and that small-scale fractures are widespread above the basement. The inferred stress orientation is consistent with regional stress data, and the estimated maximum induced earthquake magnitude is small (Mw ~2.3). The developed workflow provides a practical approach for fault and fracture characterization and for assessing induced seismicity and leakage risk. It is directly applicable to CO₂ storage site selection and to other subsurface systems.

02 PETROLEUM↗