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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗
NASA NTRS2016

Enabling Wireless Avionics Intra-Communications

The Electromagnetics and Sensors Branch of NASA Langley Research Center (LaRC) is investigating the potential of an all-wireless aircraft as part of the ECON (Efficient Reconfigurable Cockpit Design and Fleet Operations using Software Intensive, Networked and Wireless Enabled Architecture) seedling proposal, which is funded by the Convergent Aeronautics Solutions (CAS) project, Transformative Aeronautics Concepts (TAC) program, and NASA Aeronautics Research Institute (NARI). The project consists of a brief effort carried out by a small team in the Electromagnetic Environment Effects (E3) laboratory with the intention of exposing some of the challenges faced by a wireless communication system inside the reflective cavity of an aircraft and to explore potential solutions that take advantage of that environment for constructive gain. The research effort was named EWAIC for "Enabling Wireless Aircraft Intra-communications." The E3 laboratory is a research facility that includes three electromagnetic reverberation chambers and equipment that allow testing and generation of test data for the investigation of wireless systems in reflective environments. Using these chambers, the EWAIC team developed a set of tests and setups that allow the intentional variation of intensity of a multipath field to reproduce the environment of the various bays and cabins of large transport aircraft. This setup, in essence, simulates an aircraft environment that allows the investigation and testing of wireless communication protocols that can effectively be used as a tool to mitigate some of the risks inherent to an aircraft wireless system for critical functions. In addition, the EWAIC team initiated the development of a computational modeling tool to illustrate the propagation of EM waves inside the reflective cabins and bays of aircraft and to obtain quantifiable information regarding the degradation of signals in aircraft subassemblies. The nose landing gear of a UAV CAD model was used to model the propagation of a system in a "deployed" configuration versus a "stowed" configuration. The differences in relative field strength provide valuable information about the distribution of the field that can be used to engineer RF links with optimal radiated power and antenna configuration that accomplish the intended system reliability. Such modeling will be necessary in subsequent studies for managing multipath propagation characteristics inside a main cabin and to understand more complex environments, such as the inside wings, landing gear bays, cargo bays, avionics bays, etc. The results of the short research effort are described in the present document. The team puts forth a set of recommendations with the intention of informing the project and program leadership of the future work that, in the opinion of the EWAIC team, would assist the ECON team reach the intended goal of developing an all-wireless aircraft.

Torres, Omar↗
DOE OSTI2025

Investigating Bacterial-Fungal Interactions using Fungal Highway Columns in Diverse Environments and Substrates

Bacterial-fungal interactions (BFIs) play an integral role in shaping microbial community composition, biogeochemical functions, spatial dynamics, and microbial dispersal. Mycelial networks created by filamentous fungi or other filamentous microorganisms (e.g., Oomycetes) act as 'fungal highways' that can be utilized by bacteria for transport throughout heterogeneous environments, greatly facilitating their mobility and granting them access to regions that may be challenging or impossible to reach on their own (e.g., due to air pockets within the soil). Several devices and experimental protocols have been created to study these fungal highways, including fungal highway columns. The fungal highway column designed by our group can be used for a variety of in situ or in vitro applications, as well as with diverse environmental and host-associated sample types. Herein, we describe the methods for performing experiments with these columns, including designing, printing, sterilizing, and preparing the devices. The options for analyzing data obtained from the use of these devices are also discussed here, and troubleshooting advice regarding potential pitfalls associated with experiments using fungal highway columns is offered. These devices can be used to gain a more comprehensive understanding of the diversity, mechanisms, and dynamics of fungal highway BFIs to provide valuable insights into the structural and functional dynamics within complex environments (e.g., soils) and across diverse habitats in which bacteria and fungi co-exist.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Probing the initial stages of iron surface corrosion: Effect of O 2 and H 2 O on surface carbonation

Iron plays a vital role in natural processes such as water, mineral, iron, and nutrient cycles. Iron undergoes reduction-oxidation and catalytic reactions to produce various corrosion films depending on its chemical environment. Near ambient pressure X-ray photoelectron spectroscopy, polarized modulated infrared reflection absorption spectroscopy, and Auger electron spectroscopy were used to study the key reactants, from O 2 (g), H 2 O vapor, Na + and Cl – on the initial stages of iron surface corrosion. Here, with increasing the ratio of O 2 and H 2 O, surface hydrocarbons were shown to oxidize into carbonates, while the Cl – was found to migrate into the interface. The effect of each individual reactant was measured separately and water was shown to have a first order rate dependence on the carbonate growth at low pressures, with little dependence for O 2 . Near ambient pressures, both H 2 O and O 2 were found to increase the carbonate growth, which was estimated using the Langmuir isotherm model, yielding Gibbs energies between –9.8 to –8.5 kJ/mol. A mechanism is suggested to explain the oxidation is catalyzed by NaCl on iron surfaces and the adventitious hydrocarbons served as the source for surface carbonation. These findings have implications for understanding other surface catalytic and redox interface chemistry in complex environments.

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

Thermal perturbation of NMR properties in small polar and non-polar molecules

Water is an important constituent in an abundant number of chemical systems; however, its presence complicates the analysis of in situ 1 H MAS NMR investigations due to water’s ease of solidification and vaporization, the large changes in mobility, affinity for hydrogen bonding interactions, etc., that are reflected by dramatic changes in temperature-dependent chemical shielding. To understand the signatures of water and other small molecules in complex environments, in particular how water interacts with the other molecules, in this work the thermally-perturbed NMR properties of water are investigated in detail by in situ MAS NMR. Our results substantially extend the previously published temperature-dependent 1 H and 17 O chemical shifts, linewidths, and spin-lattice relaxation times over a much wider range of temperatures and with significantly enhanced thermal resolution. The following major results are obtained: Hydrogen bonding is clearly shown to weaken at elevated temperatures in both 1 H and 17 O spectra, showing an increase in chemical shielding. At low temperatures, tetrahedral domains of H-bonding networks are evidenced and the observation of solid ice is made under in situ MAS conditions. The 1 H chemical shift properties in other small polar and non-polar molecules have also been described over a range of temperatures, showing the dramatic effect hydrogen bonding perturbation. Gas phase species are described where chemical exchange between gas and liquid phases plays an important role on the observed NMR shifts. The results disclosed herein lay the foundation for a clearer interpretation of complex systems during the increasingly popular in situ NMR characterization at elevated temperatures and pressures for studying chemical systems containing water molecules.

17O NMR↗
DOE OSTI2024

Understanding Trace Iron and Chromium Incorporation During Gibbsite Crystallization and Effects on Mineral Dissolution

Incorporation of pollutants, e.g., heavy metals, or critical elements, e.g., lithium, as impurities in mineral phases can significantly affect their mobility or sequestration in the environment. Even when present at low concentrations, impurities can alter the solubility and reactivity of the host mineral. Here, in this study, we investigate the incorporation of trace amounts of iron (Fe 3+ ) and chromium (Cr 3+ ) during the crystal growth of the aluminum (Al 3+ ) hydroxide, gibbsite, a major component of bauxite ores, an important soil mineral, and a dominant mineral phase in stored radioactive wastes. Using a comprehensive suite of analytical techniques, we show that both Cr 3+ and Fe 3+ can be incorporated into the gibbsite lattice during coprecipitation by replacing Al 3+ in octahedral sites. These small amounts are consistent with limited to no structural isomorphism shared between Al 3+ and Cr 3+ /Fe 3+ hydroxide precipitates, nor room temperature miscibility of their isostructural M 2 O 3 oxide forms, in contrast with oxyhydroxide forms where Al 3+ and Fe 3+ share similar structural topologies. Despite the limited uptake of Cr 3+ /Fe 3+ , we show that these impurities have significant implications for gibbsite dissolution behavior. The limited uptake of Cr 3+ /Fe 3+ (e.g. 0.43% Cr 3+ and 0.4% Fe 3+ ), we show that these impurities have significant implications for gibbsite dissolution behavior and subsequent reactivity in complex environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2005

Visualization Methods for Viability Studies of Inspection Modules for the Space Shuttle

An effective simulation of an object, process, or task must be similar to that object, process, or task. A simulation could consist of a physical device, a set of mathematical equations, a computer program, a person, or some combination of these. There are many reasons for the use of simulators. Although some of the reasons are unique to a specific situation, there are many general reasons and purposes for using simulators. Some are listed but not limited to (1) Safety, (2) Scarce resources, (3) Teaching/education, (4) Additional capabilities, (5) Flexibility and (6) Cost. Robot simulators are in use for all of these reasons. Virtual environments such as simulators will eliminate physical contact with humans and hence will increase the safety of work environment. Corporations with limited funding and resources may utilize simulators to accomplish their goals while saving manpower and money. A computer simulation is safer than working with a real robot. Robots are typically a scarce resource. Schools typically don t have a large number of robots, if any. Factories don t want the robots not performing useful work unless absolutely necessary. Robot simulators are useful in teaching robotics. A simulator gives a student hands-on experience, if only with a simulator. The simulator is more flexible. A user can quickly change the robot configuration, workcell, or even replace the robot with a different one altogether. In order to be useful, a robot simulator must create a model that accurately performs like the real robot. A powerful simulator is usually thought of as a combination of a CAD package with simulation capabilities. Computer Aided Design (CAD) techniques are used extensively by engineers in virtually all areas of engineering. Parts are designed interactively aided by the graphical display of both wireframe and more realistic shaded renderings. Once a part s dimensions have been specified to the CAD package, designers can view the part from any direction to examine how it will look and perform in relation to other parts. If changes are deemed necessary, the designer can easily make the changes and view the results graphically. However, a complex process of moving parts intended for operation in a complex environment can only be fully understood through the process of animated graphical simulation. A CAD package with simulation capabilities allows the designer to develop geometrical models of the process being designed, as well as the environment in which the process will be used, and then test the process in graphical animation much as the actual physical system would be run . By being able to operate the system of moving and stationary parts, the designer is able to see in simulation how the system will perform under a wide variety of conditions. If, for example, undesired collisions occur between parts of the system, design changes can be easily made without the expense or potential danger of testing the physical system.

Mobasher, Amir A.↗
DOE OSTI2023

Ion Conducting Polymer Interfaces for Lithium Metal Anodes: Impact on the Electrodeposition Kinetics

Electrochemical cells that utilize metals (e.g., lithium, sodium, zinc) as anodes are under intense investigation as they are projected to replace the current lithium-ion batteries to serve as a more energy-dense option for commercial applications. In addition, metal electrodes provide opportunities for fundamental research of different phenomena, such as ion transport and electrochemical kinetics, in the complex environment of reactive metal-electrodeposition. In this work, computationally and experimentally the competing effects related to transport and kinetics during the metal electrodeposition process are examined. Using Brownian dynamics simulations, it is shown that slower deposition kinetics results in a more compact and uniform Li morphology. This finding is experimentally implemented by designing ion-containing polymeric coatings on the electrodes that simultaneously provide pathways for lithium-ion transport, while impeding the charge transfer (Li + + e - → Li) at heterogeneous surfaces. It is further shown that these ionic polymer interfaces can significantly extend the cell-lifetime of a lithium metal battery in both ether-based and carbonate-based electrolytes. Through theoretical and experimental investigations, it is found that a low kinetic to transport rate ratio is a major factor in influencing the Li plating morphology. The plating morphology can be further fine-tuned by increasing ionic conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Toward Intelligent Multimodal Holography for Real-Time Chemical Imaging of Dynamic Ion Separation

Molecular-level visualization of ion transport and separation dynamics in complex environments is crucial for advancing energy systems, water purification, and critical materials recovery. Achieving this requires imaging platforms that combine structural sensitivity, chemical specificity, and real-time operation. Digital off-axis holography (DOAH) provides high-throughput, label-free quantitative phase imaging but inherently lacks chemical selectivity. Integrating DOAH with complementary spectroscopic channels such as fluorescence or hyperspectral imaging introduces the needed molecular specificity, while also creating challenges in multimodal data fusion, synchronization, and computational throughput. Artificial intelligence offers a powerful route to address these limitations by uniting physics-based reconstruction with data-driven interpretation. In this Perspective, we outline a framework for intelligent multimodal holography and demonstrate its potential using a preliminary AI-driven test case. Raw DOAH holograms of lanthanide solutions subjected to magnetic field gradients were analyzed using multi-agent AI workflows that autonomously selected reconstruction tools, extracted NMF components, and generated scientific claims consistent with true paramagnetic and diamagnetic behavior. This demonstration shows how AI-enabled reasoning can deliver real-time chemical–structural interpretation directly from raw holograms. Together, these advances define a path toward adaptive, intelligent holography platforms capable of supporting in situ chemical separations, dynamic ion transport analysis, and next-generation interfacial science.

Ricchiuti, Giovanna↗
DOE OSTI2021

Single‐Atomic Site Catalyst with Heme Enzymes‐Like Active Sites for Electrochemical Sensing of Hydrogen Peroxide

Abstract Heme enzymes, with the pentacoordinate heme iron active sites, possess high catalytic activity and selectivity in biosensing applications. However, they are still subject to limited catalytic stability in the complex environment and high cost for broad applications in electrochemical sensing. It is meaningful to develop a novel substitute that has a similar structure to some heme enzymes and mimics their enzyme activities. One emerging strategy is to design the Fe‐N‐C based single‐atomic site catalysts (SASCs). The obtained atomically dispersed Fe‐N x active sites can mimic the active sites of heme enzymes effectively. In this work, a SASC (Fe‐SASC/NW) is synthesized by doping single iron atoms in polypyrrole (PPy) derived carbon nanowire via a zinc‐atom‐assisted method. The proposed Fe‐SASC/NW shows high heme enzyme‐like catalytic performance for hydrogen peroxide (H 2 O 2 ) with a specific activity of 42.8 U mg −1 . An electrochemical sensor based on Fe‐SASC/NW is developed for the detection of H 2 O 2 . This sensor exhibits a wide detection concentration range from 5.0 × 10 −10 m to 0.5 m and an excellent limit of detection (LOD) of 46.35 × 10 −9 m . Such excellent catalytic activity and electrochemical sensing sensitivity are attributed to the isolated Fe‐N x active sites and their structural similarity with natural metalloproteases.

Ding, Shichao↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Design and implementation of dynamic I/O control scheme for large scale distributed file systems

In this paper, we have analyzed the input/output (I/O) activities of Cori, which is a high-performance computing system at the National Energy Research Scientific Computing Center at Lawrence Berkeley National Laboratory. Our analysis results indicate that most users do not adjust storage configurations but rather use the default settings. In addition, owing to the interference from many applications running simultaneously, the performance varies based on the system status. To configure file systems autonomously in complex environments, we developed DCA-IO, a dynamic distributed file system configuration adjustment algorithm that utilizes the system log information to adjust storage configurations automatically. Our scheme aims to improve the application performance and avoid interference from other applications without user intervention. Moreover, DCA-IO uses the existing system logs and does not require code modifications, an additional library, or user intervention. To demonstrate the effectiveness of DCA-IO, we performed experiments using I/O kernels of real applications in both an isolated small-sized Lustre environment and Cori. Our experimental results shows that our scheme can improve the performance of HPC applications by up to 263% with the default Lustre configuration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Path-Integrated X-Ray Images for Multi-Surface Digital Image Correlation (PI-DIC)

X-ray imaging offers unique possibilities for Digital Image Correlation (DIC), opening the door for full-field deformation measurements of a test article in complex environments where optical DIC suffers severe biases or is impossible. While X-ray DIC has been performed in the past with standard DIC codes designed for optical images, the path-integrated nature of X-ray images places constraints on the experimental setup, predominantly that only a single surface of interest moves/deforms. These requirements are difficult to realize for many practical situations and limit the amount of information that can be garnered in a single test. Other X-ray based diagnostics such as Digital Volume Correlation (DVC) and Projection DVC (P-DVC) overcome these obstacles, but DVC is limited to quasi-static tests, and both DVC and P-DVC necessitate high-resolution computed tomography (CT) scan(s) and often require a potentially invasive pattern throughout the volume of the specimen. Here this work presents a novel approach to measure time-resolved displacements and strains on multiple surfaces from a single series of 2D, path-integrated (PI) X-ray images, called PI-DIC. The principle of optical flow or conservation of intensity—the foundation of DIC—was reframed for path-integrated images, for an exemplar setup comprised of two plates moving and deforming independently. Synthetic images were generated for rigid translations, rigid rotations, and uniform stretches, where each plate underwent a unique motion/deformation. Experimental specimens were fabricated (either an aluminum plate with tantalum features or a plastic plate with steel features) and the two specimens were independently translated. PI-DIC was successfully demonstrated with the synthetic images and validated with the experimental images. Prescribed displacements were recovered for each plate from the single set of path-integrated, deformed images. Errors were approximately 0.02 px for the synthetic images with 1.5% image noise, and 0.05 px for the experimental images. These results provide the foundation for PI-DIC to measure motion and deformation of multiple, independent surfaces with subpixel accuracy from a single series of path-integrated X-ray images.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2024

High-purity germanium semiconductor modeling in the detector response function toolkit

In this study, we have extended the detector response function toolkit (DRiFT) to provide modeling capabilities of semiconductor sensors. DRiFT provides realistic nuclear instrumentation response by post-processing Monte-Carlo N-particle (MCNP®) radiation transport outputs. MCNP® is capable of modeling radiation transport in complex environments, but has limited detector physics and readout electronics modeling capabilities. Semiconductor detector response can be calculated with a high-fidelity for a flexible range of environments by utilizing MCNP® to simulate radiation interactions inside of detector volumes, and then using DRiFT to model charge transport and signal formation in the semiconductor, as well as the readout electronics. DRiFT models charge transport in the semiconductor, the preamplifier, shaping amplifier, pulse pile-up, and electronic noise to generate detector response. The semiconductor application in DRiFT can model a range of semiconductor materials, shapes, and sizes; and is demonstrated here for a large volume coaxial high-purity germanium (HPGe) detector. Here, we compare detector response functions of a coaxial HPGe detector with measurement of 60 Co, 133 Ba, and 137 Cs at varying count rates, and we conduct a parameter study to demonstrate the effect of changing parameters in the DRiFT simulation. The HPGe detector response function shows excellent agreement with measurements of difference sources with varying dead times and count rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Quantitative 14 N NMR with Monte Carlo Uncertainty Analysis of Nitrate/Nitrite in Alkaline Nuclear Waste

While monitoring of nitrate and nitrite concentrations is important for managing corrosion in nuclear waste systems, existing analytical methods are hindered by turbidity, spectral interference, and delays from sample handling. Here, we demonstrate quantitative 14 N nuclear magnetic resonance (qNMR) spectroscopy as a direct, matrix-tolerant approach for nitrate and nitrite detection at natural abundance. Monte Carlo resampling was integrated into the workflow to quantify random error, establish precision–time tradeoffs, and separate noise-limited uncertainty from systematic bias arising from shimming, transmitter offset, or excitation pulse conditions. Quantification of nitrate and nitrite were validated in controlled alkaline matrix challenges and in 18-component Hanford-type simulants. These results establish 14 N qNMR as a practical, uncertainty-bounded tool for monitoring redox-active nitrogen species in chemically complex environments and provide a generalizable framework for quantitative analysis of quadrupolar nuclei.

Graham, Trent R. [Pacific Northwest National Labor↗
DOE OSTI2023

Development and Characterization of Electrodes for Surface-Specific Attenuated Total Reflection Two-Dimensional Infrared Spectroelectrochemistry

Electrochemical interfaces still have remaining mysteries surrounding the interfacial region of the electrical double layer, despite being prevalent throughout the energy and water remediation industries. The electrical double layer is where many important dynamic processes such as catalysis and electron transfer occur. The goal of this work is to study the electrical double layer with two-dimensional infrared (2D IR) spectroscopy to experimentally access the details of the structural dynamics of this complex environment. However, there are several experimental challenges to applying 2D IR spectroscopy to this application, such as assuring the surface specificity of the spectrum, optimizing the signal strength while minimizing spectral distortions from dispersion and Fano line shapes, and selecting electrode materials that are both sufficiently IR compatible and conductive. Here we will discuss various considerations when designing 2D IR experiments of electrode interfaces utilizing several substrates and experimental configurations and demonstrate a robust method for 2D IR experiments of electrode interfaces under applied potential that combines nonconducting Si ATR wafers with conductive ITO and thin nanostructured films of plasmonically active Au functionalized with 3-mercapto-2-butanone (MCB). We show that layered electrodes on thin Si ATR wafers with MCB are sensitive to applied potential and that the distortions in the linear and 2D IR spectra are heavily dependent on the morphology of the Au surface.

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

Vibrational Probe at the Electrochemical Interface: Dependence on Plasmon Coupling and Potential of the Lineshape in Two-Dimensional Infrared Spectroscopy

Two-dimensional infrared spectroscopy of vibrational probes at an electrode surface shows promise for studying the structural dynamics at an active electrochemical interface. This interface is a complex environment where the solution structures in response to the applied potential. A strategy for achieving the necessary monolayer sensitivity is to use a plasmonically active electrode, which enhances the electromagnetic fields that produce the spectroscopic response. Here, in this study, we show how the coupling between the plasmon and the vibrations of the molecular monolayer impacts the FTIR and 2D IR spectroscopy, with an emphasis on the electrochemical potential difference spectra. We show how mixing between the vibrational and plasmonic states gives rise to the distortions that are observed in these measurements. This provides an important step toward 2D IR measurements of vibrational probes at the electrochemical interface as a tool for probing the structural dynamics in the double layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗