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DOE OSTI2024

Coil optimization for quasi-helically symmetric stellarator configurations

Filament-based coil optimizations are performed for several quasi-helical stellarator configurations, beginning with the one from Landreman & Paul ( Phys. Rev. Lett. , vol. 128, 2022, 035001), demonstrating that precise quasi-helical symmetry can be achieved with realistic coils. Several constraints are placed on the shape and spacing of the coils, such as low curvature and sufficient plasma–coil distance for neutron shielding. The coils resulting from this optimization have a maximum curvature 0.8 times that of the coils of the Helically Symmetric eXperiment (HSX) and a mean squared curvature 0.4 times that of the HSX coils when scaled to the same plasma minor radius. When scaled up to reactor size and magnetic field strength, no fast particle losses were found in the free-boundary configuration when simulating 5000 alpha particles launched at $3.5\,\mathrm {MeV}$ on the flux surface with a normalized toroidal flux of $s=0.5$ . An analysis of the tolerance of the coils to manufacturing errors is performed using a Gaussian process model, and the coils are found to maintain low particle losses for smooth, large-scale errors up to amplitudes of approximately $0.15\,\mathrm {m}$ . Another coil optimization is performed for the Landreman–Paul configuration with the additional constraint that the coils are purely planar. Visual inspection of the Poincaré plot of the resulting magnetic field-lines reveal that the planar modular coils alone do a poor job of reproducing the target equilibrium. Additional non-planar coil optimizations are performed for the quasi-helical configuration with $5\,\%$ volume-averaged plasma beta from Landreman et al. ( Phys. Plasma , vol. 29, issue 8, 2022, 082501), and a similar configuration also optimized to satisfy the Mercier criterion. The finite beta configurations had larger fast-particle losses, with the free-boundary Mercier-optimized configuration performing the worst, losing approximately $5.5\,\%$ of alpha particles launched at $s=0.5$ .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Nanoscale Examination of Chemical and Enzymatic Degradation of Plant Cell Walls

Lignocellulosic materials present the largest source of biomass for biotechnology and green energy. This study aimed at better understanding the cell wall disintegration mechanisms relevant for the biochemical conversion of biomass to carbohydrates. Herein, we examined nanoscale changes in cell wall structure and composition upon industrially relevant chemical and enzymatic treatments to achieve the desired level of breakdown. One treatment involved hydrogen peroxide and acetic acid to remove lignin. Another modification used the cellulase enzyme for cell wall degradation. Band excitation contact resonance atomic force microscopy was used to visualize and mechanically characterize cell wall layers. After cellulase treatments, we detected microcracks across the cell wall. Wet-chemical, Fourier-transform infrared and Raman spectroscopic analyses confirmed the removal of lignin and extractives through acid bleaching, while the enzymatic treatment minimally affected the biopolymer composition. Delignification resulted in cell wall delamination and reduced stiffness. In conclusion, X-ray diffraction revealed changes in cellulose structure and crystallinity.

Soini, Steven A. [Florida Atlantic Univ., Boca Rat↗

DOE OSTI2025

Advancing Sodium-Ion Battery Cathodes: A Low-Cost, Eco-Friendly Mechanofusion Route from TiO 2 Coating to Ti 4+ Doping

Layered oxide battery cathodes often require extra stabilization strategies, such as surface coating or doping, to mitigate side reactions and enhance longevity. Conventional methods such as aqueous deposition and atomic layer deposition are costly and environmentally unfriendly and even damage the original structure, especially for air-sensitive sodium-ion battery (SIB) cathodes. Herein, we introduce an all-dry mechanofusion technique that modifies hydroxide precursors with TiO 2 coating before sintering with a sodium source. Using advanced characterizations including X-ray diffraction, neutron diffraction, and solid-state nuclear magnetic resonance for structural insights, X-ray absorption spectroscopy to study metal valence states, and transmission X-ray microscopy for nanoscale visualization of nickel oxidation states, we verified that postsintering transforms TiO 2 surface coating into Ti doping, leading to improved Ni-oxidation homogeneity, modified charge compensation, and enhanced thermal stability. Electrochemical tests reveal superior performance in capacity retention, rate capability, and air stability for these modified cathodes, with pouch cells maintaining over 85% capacity after 650 cycles. This method presents a sustainable, cost-effective route for advanced SIB cathode development.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗

DOE OSTI2025

Unsteady- and Steady-State Relative Permeability Study with X-ray and Acoustic Monitoring for CO 2 Storage in Deep Saline Aquifers

In this study, we link the multiphase flow measurements with controls of sedimentary structures (e.g., heterogeneity and anisotropy) on relative permeability to variations in ultrasonic velocities for two deep saline aquifer formations (Entrada and Bluff Sandstones) in the San Juan Basin of the Southwestern USA. The rock specimens were extracted from outcrop sites near Durango, CO, USA. They have distinct differences in grain size, cementation composition, and individual chemical amounts, despite both formations being eolian sandstones. We performed a series of unsteady- and steady-state CO 2 -brine relative permeability experiments under capillary-controlled displacement rates. Unsteady-state experiments were conducted at 71 °C and 9.65 MPa; steady-state experiments were conducted at 85 °C and 22.8 MPa and 89 °C and 24.1 MPa for the Bluff and Entrada Sandstones, respectively. During the unsteady experiments, X-ray computed tomography was used to visualize multiphase flow in porous media and quantify saturations during brine drainage under various flow rates. Scan images and saturation profiles indicate that the CO 2 distribution in the pore volume was strongly impacted by the presence of high-angle cross-laminations, heterogeneous rock structure, and direction of bedding orientation. Those factors contribute to dramatic and quick initial breakthroughs and affect the overall saturation dynamics. Steady-state relative permeability tests were conducted at net flow rates of 1 mL/min for both brine drainage and imbibition. During the experimental steps, the CO 2 fractional flow was increased and decreased for both drainage and imbibition scenarios to mimic the front when CO 2 contacts brine and behind the front when brine enters space previously occupied by CO 2 . It was found that compressional velocity decreased, while shear waves slightly increased as brine saturation decreased. The hysteresis effects for the relative permeability and acoustic velocities were distinct. Furthermore, the CO 2 /brine front stability is quantified by applying a mobility ratio approach to spot saturations at which the boundary line between fluids becomes uneven. The results presented in this work can potentially boost the quality and precision of forecasts for the CO 2 storage projects in which the vertical and horizontal core-scale heterogeneity and anisotropy impact the plume migration within host reservoirs.

carbon dioxide (CO2)↗

DOE OSTI2026

A Review and Outlook on Experimental Advances and Innovations in Geological CO 2 Storage: Insights from Depleted Gas Reservoirs and Saline Aquifers

Geological storage of carbon dioxide (CO 2 ) in depleted gas reservoirs and deep saline aquifers is a key part of global decarbonization efforts. As carbon capture and storage advances toward commercial-scale deployment, the credibility and scalability of laboratory experiments are increasingly vital for guiding safe and effective field implementation. This review offers a comprehensive, cross-scale evaluation of experimental methodologies, including core flooding, high-pressure, high-temperature systems, microfluidic visualization, and emerging systems such as multilayer commingled/compartmentalized core flooding, 3D-printed micromodels, and AI-powered digital twins. These innovations are demonstrated to enhance representativeness, reproducibility, and real-time insight, thereby addressing the limitations of conventional workflows. A critical analysis of methodological gaps, such as inconsistent pressure–temperature conditions, oversimplified brine chemistry, and a lack of standardization, reveals experimental sources of scale translation errors and performance uncertainty. By comparing the unique challenges of depleted gas reservoirs (such as low water saturation and legacy well leakage) to those of saline aquifers (including pressure buildup and caprock integrity), this review identifies formation-specific priorities for experimental design. Novel contributions include a synthesis of best practices, integration strategies for model calibration, and recommendations for standardizing core handling, saturation procedures, and reporting protocols. Furthermore, this work serves as a guide for developing robust, field-relevant experimental strategies that can increase the deployment and regulatory acceptance of CO 2 storage technologies at scale.

58 GEOSCIENCES↗

DOE OSTI2025

Biogeochemical Controls on Wood Degradation as a Source of Bioavailable Carbon in Denitrifying Bioreactors

Woodchip bioreactors (WBRs) are important tools for the removal of nitrate in agricultural drainage, but their effectiveness is often limited by the slow degradation of lignocellulosic wood residues into bioavailable forms of carbon that fuel denitrifying microorganisms. Here, we examine biogeochemical factors regulating wood degradation in saturated woodchip beds, with a focus on the effects of dissolved oxygen (DO), iron (Fe), and manganese (Mn) in generating oxidative activity that can enhance wood decomposition. Woodchips from a 10-year-old WBR were characterized with bulk techniques and a novel combination of μX-ray scattering, μXRF, and μXANES to visualize the depletion of crystalline cellulose as a proxy for wood degradation. Woodchips from upstream portions of the reactor exhibited the greatest degradation, probably due to greater DO exposure, and degradation was localized to a 100 to 200 μm thick surface layer that was also associated with higher concentrations of Fe and Mn. Greater degradation was associated with faster nitrate removal. μXANES analysis of Fe and Mn in the surface layer indicated the presence of a microenvironment in which oxygenation reactions of Fe(II) and Mn(II) could contribute to the formation of reactive oxidants involved in the degradation of lignocellulose. In conclusion, our results provide new insight into biogeochemical properties that influence wood decomposition in WBRs at both micro- and macroscales and how these wood degradation processes are coupled with denitrification.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Single-Determinant Ground State in Ce 4+ Imidophosphorane Complexes

X-ray spectroscopy techniques are critical in the electronic structure analysis of high-valent lanthanides. The interpretation of multipeaked features at the lanthanide L 3 -edge has remained a challenging question, as it is observed across a range of material classes. A series of structurally related Ce 4+ complexes were prepared to probe the potential ligand field perturbation of the ground state within the series. The tuning of relative 4f and ligand orbital energies in homoleptic and heteroleptic tetravalent Ce imidophosphorane complexes is achieved through ligand derivatization and is clearly demonstrated by UV−vis spectroscopy and electrochemically measured redox potentials. However, Ce L 3 - edge high-energy resolution fluorescence-detected (HERFD) X-ray absorption near-edge structure (XANES) spectra present features at consistent numbers and energies across the range of complexes. Resonant inelastic X-ray scattering (RIXS) is employed to visualize the observed features in the HERFD-XANES spectra. Large complete active space configuration interaction singles and doubles (CASCISD) calculations demonstrate that the ground-state wave function of all complexes can be described employing a single determinant. As a result, the multielectron feature at the L 3 -edge observed in this study for the Ce 4+ imidophosphorane complexes is described as excited-state multiconfigurational behavior that is independent of ligand variation, in systems where the ground state is described using the simple single determinant wave function.

Lanthanides↗

DOE OSTI2024

Teaching Nonradiative Transitions with MATLAB and Python

Nonradiative transitions are changes in energy states of atoms, ions, or molecules that do not involve the emission or absorption of photons. Despite their importance in understanding luminescent properties and photochemical reaction mechanisms, nonradiative transitions are rarely given more than a qualitative overview in undergraduate and even graduate physical chemistry curricula. To supplement the coverage of nonradiative transition topics, we provide here a set of active learning exercises to help students develop an intuitive understanding of the factors that determine the rate of nonradiative transitions. Here, we start by outlining the theoretical background through the formulations of the Franck–Condon factor and its relation to the rate of nonradiative transition. We then introduce three teaching modules, with associated MATLAB and Python codes, to explore how (1) the excited state nuclear displacement, (2) the electronic energy gap between excited and ground state and (3) the excited/ground state vibrational mode frequencies affect the magnitude of the Franck–Condon factor and thereby the rate of nonradiative transitions. The wave function overlap plots that accompany all teaching modules provide direct visualization of the effect of input parameters on the magnitude of Franck–Condon overlap integral.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Nanopolysaccharide Builder: A User-Friendly Tool for Atomistic Models of Polysaccharide-Based Nanostructures

Here, we introduce Nanopolysaccharide Builder (NPB), a user-friendly software tool designed to construct polysaccharide nanostructures─mainly those based on cellulose, chitin, and chitosan─using experimental data or user-defined parameters. NPB enables the generation of cellulose and chitin allomorphs with customizable biochemical topologies and also facilitates the construction of large bundles that replicate nanostructures found in biological support systems, including plant cell walls and arthropod cuticles. The software outputs atomic Cartesian coordinates in Protein Data Bank (PDB) format and also provides atom connectivity files in PSF and PARM formats, ensuring seamless integration with major molecular dynamics (MD) engines such as NAMD, CHARMM, GROMACS, AMBER, OpenMM, and LAMMPS. Built on an interactive visualization framework, NPB features a graphical user interface (GUI) and supports both macOS and Linux operating systems. By enabling detailed atomic-scale studies of polysaccharide evolution in extracellular matrices and cell walls of algae, bacteria, fungi, and plants, NPB is poised to advance AI-guided research in sustainable chemical development and biomass utilization.

Wan, Zhangmin [Univ. of British Columbia, Vancouve↗

DOE OSTI2026

Multiresolution Quantum Chemistry: Nonlinear Response Properties at the Basis Set Limit

We benchmark the accuracy of Dunning correlation-consistent Gaussian basis sets for computing frequencydependent second-order hyperpolarizabilities relevant to second-harmonic generation (SHG), using multiresolution analysis (MRA) as a reference. Basis set errors are analyzed using a unit-sphere representation of the effective hyperpolarizability vector, enabling direct assessment of directional error structure. We introduce a relative RMS total error metric that integrates directional deviations over the unit sphere and complement it with signed projection errors that distinguish over- and underestimation. Unsupervised clustering based on these signed directional metrics reveals four distinct convergence behaviors across a set of 68 molecules. Unitsphere visualizations of representative systems show that basis set errors are often highly anisotropic and localized along specific bond directions, even when global error measures appear small. Doubly augmented basis sets consistently outperform singly augmented ones, and core-polarization functions are required for uniform convergence in second-row systems. Overall, this work demonstrates that directional analysis combined with clustering provides a robust framework for understanding basis set convergence in nonlinear optical response properties.

Basis sets↗

DOE OSTI2025

Catalight─An Open-Source Automated Photocatalytic Reactor Package Illustrated through Plasmonic Acetylene Hydrogenation

An open-source and modular Python package, Catalight, is developed and demonstrated to automate (photo)catalysis measurements. (Photo)catalysis experiments require studying several parameters to evaluate performance, including the temperature, gas flow rate and composition, illumination power, and spectral profile. Catalight orchestrates measurements over this complicated parameter space and systematically stores, analyzes, and visualizes the results. To showcase the capabilities of Catalight, we perform an automated apparent activation barrier measurement of acetylene hydrogenation over a plasmonic AuPd catalyst on an Al 2 O 3 support, simultaneously varying laser power, wavelength, and temperature in a multiday experiment controlled by a simple Python script. Our chemical results unexpectedly show an increased activation barrier upon light excitation, contrary to previous findings for other plasmonic reactions and catalysts. We show that the reaction rate order with respect to both acetylene and hydrogen remains unchanged upon illumination, suggesting that molecular surface coverage is not changed by light. By analyzing the inhomogeneity of the laser-induced heating, we attribute these results to a partial photothermal effect combined with a photochemical/hot electron-driven mechanism. In conclusion, our findings highlight the capabilities of a new experiment automation tool; explore the photocatalytic mechanism for an industrially relevant reaction; and identify systematic sources of error in canonical photocatalysis experimental procedures.

Catalysts↗

DOE OSTI2025

PySIDT: Subgraph Isomorphic Decision Trees for Molecular Property Prediction

Accurate molecular property prediction is important across all fields of chemistry. Deep neural networks (DNNs) have become increasingly popular due to their ability to train automatically, avoiding the incredibly tedious process of constructing and extending traditional property estimation schemes. However, DNNs require large amounts of training data, are challenging to interpret, require large amounts of memory to load even during inference, and have severe difficulties incorporating qualitative chemical knowledge, which are often desired for molecular property prediction tasks. Here, in this study, we present PySIDT (https://github.com/zadorlab/PySIDT), a software for training and running inference on Subgraph Isomorphic Decision Trees (SIDTs). SIDTs are graph-based decision trees made of nodes associated with molecular substructures. Inference is done by descending target molecular structures down the decision tree to nodes with matching subgraph isomorphic substructures and making predictions based on the final (most specific) nodes matched. SIDTs scale down well to dataset sizes much smaller than is feasible for DNNs. As trees of molecular substructures, SIDTs are inherently readable and easy to visualize, making them easy to analyze. They are also straightforward to extend and retrain, facilitate uncertainty estimation, and enable easy integration of expert knowledge. We demonstrate the SIDT approach discussing its application to a diverse range of molecular prediction tasks: rate coefficient estimation, diffusion coefficient estimation, thermochemistry estimation, transition state bond stretch prediction, p K a prediction, stability of molecular structures, stability of surface structures, and prediction of surface lateral interaction energetics. Additionally, we demonstrate the power of the SIDT algorithms in two direct learning curve vanilla comparisons with the popular DNN-based software Chemprop and the popular gradient boosted trees-based software XGBoost on enthalpy of formation and rate coefficient prediction tasks. In particular, in the enthalpy of formation case, vanilla PySIDT is able to outperform vanilla Chemprop and XGBoost across the full range of training/validation set sizes out to 11,560 data points.

Johnson, Matthew Sean [Sandia National Laboratorie↗

DOE OSTI2026

X‑ray Coherent Diffractive Imaging of Large Helium Nanodroplets Doped with Small Molecules

We report the first X-ray coherent diffractive imaging experiment on molecule-doped helium nanodroplets. It complements previous work, where we reported single-shot X-ray coherent diffractive imaging studies of Xe dopant clusters formed in 4He and 3He droplets. These noble gas clusters were used to visualize the impact of rotational excitation of the droplets on the spatial distribution of atomic dopants within the droplets, and to study the differences and connections between quantum and classical droplet rotational motion. Here, we expand our studies to the molecular dopants CF4, CHF3, CH3CN, and SF6, imaged with 1.5 keV photons. We find multiple Bragg spots in the diffraction patterns of molecule-doped droplets with radii of approximately 600 nm, which provide evidence that molecules form elongated clusters with preferential alignment along the angular momentum axis of the 4He droplets, in agreement with our previous results on the aggregation of Xe clusters on quantum vortices. Real-space reconstructions of molecular dopant cluster density profiles are obtained for droplets with smaller radii of approximately 300 nm. The diffuse images suggest the formation of low-density, potentially porous, molecular clusters upon aggregation at T = 0.4 K in 4He droplets. In the normal fluid 3He droplets, molecules aggregate into loose clusters on the droplets' equator, similar to previous observations for Xe atoms. Time-of-flight mass spectra reveal that the doped helium nanodroplet moieties fragment extensively into constituent atomic ions, producing only a small fraction of molecular fragment ions. The findings are discussed in the context of previously proposed schemes to use He droplets as potential tamper materials for ultrafast X-ray imaging experiments.

Feinberg, AlexandraJ↗

DOE OSTI2024

Elucidation of a Metastable p(2 × 1) O Atom Adlayer Structure on Cu(111)

Cu-based catalysts are ubiquitous in many industrial reactions, including methanol synthesis. Under partially oxidizing conditions, Cu catalysts can have dynamic surface structures that greatly influence their reactivities. Therefore, elucidating the surface structures that are present on Cu, and looking for metastable structures, aids in the long term goal of understanding and controlling their catalytic behavior. Thin-film copper oxides such as the “29” and “44” structures have been described at length in the literature, but precursors to these thin-film oxides can be challenging to study because they exist only under certain conditions. Using a combination of experimental and computational surface science techniques, we discovered, modeled, and quantified a previously unreported O atom adlayer structure on Cu(111) with a p(2 × 1) unit cell. Here, we used scanning tunneling microscopy to visualize the striped 2 × 1 structure and density functional theory (DFT) structure optimizations to identify the thermodynamically most favorable positions of Cu and O atoms in a p(2 × 1) unit cell. Using X-ray photoelectron spectroscopy and temperature-programmed desorption, we determined the stoichiometry of the structure to be 2:1 for surface Cu atoms to O adatoms, the same stoichiometry as that modeled by DFT. This work reports a new metastable structure formed on Cu(111) at the very initial stages of oxidation and is therefore worth considering in models of catalytically relevant redox processes at Cu surfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Response of fs-Laser-Irradiated Diamond by Ultrafast Electron Diffraction

Structural details of the proposed solid–liquid phase transition of carbon have remained elusive, despite years of study. While it is theorized that novel carbon materials form from a liquid precursor, experimental studies have lacked the temporal and spatial resolution necessary to fully characterize the purported liquid state. Here, in this work, we utilize megaelectronvolt-ultrafast electron diffraction (MeV-UED) to study laser irradiated submicron diamond thin films in a pump–probe scheme with picosecond time resolution to visualize potential structural changes of excited diamond. We probe the structure of diamond using a combination of fluences (13, 40 J/cm 2 ) and time delays (10, 25, 100 ps), but observe negligible changes in the static diffraction pattern of diamond and an overall decrease in diffraction intensity up to 100 ps after the excitation pulse. We thus conclude that no appreciable amount of liquid or graphitized carbon is present and highlight the structural resilience of bulk diamond to intense 800 nm ultrafast laser pulses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Assessing the Sensitivity of Pourbaix Diagrams to Computational Protocols: Electrochemical Stability of Ni Oxides as a Case Study

Pourbaix diagrams stand as a useful tool in assessing and visualizing materials’ electrochemical stability and are widely used for electrocatalyst design. However, their reliability hinges on the accuracy of the chemical potentials of involved phases, which may bear uncertainties and can be significantly impacted by decision-making steps in the computational protocol. Here, this study introduces a robust sensitivity analysis framework, exemplified through a detailed examination of the computational Pourbaix diagram of Ni, the oxides of which are used as high-activity and cost-friendly catalysts for many electrochemical reactions. Quantities of interest derived from the Pourbaix diagram include the appearance and stability domain of the catalytically active Ni oxide phases along with the onset electrochemical potentials of phase transitions. These metrics can guide the design of operational conditions for Ni oxide electrocatalysts. We find that the employed DFT exchange-correlation functional has the most significant influence on the computed Pourbaix diagram. Uncertainties on crystal structures, along with their related ab initio energetics, are also found to affect the size of the phase stability domain. Higher-order coupling among input parameters is found to play a crucial role in influencing the appearance and distribution of Ni phases in the diagram. Our findings suggest a need to consider variations and uncertainties associated with the computational procedures on predicted Pourbaix diagrams for materials design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Cyanine-Incorporated Amorphous Polymeric Carbon Dots for Optical Reactive Oxygen Species Sensing

Reactive oxygen species (ROS) are common cellular oxidants that when overproduced by cellular stressors cause harm to cells. Detection of ROS is of utmost importance to understanding a wide variety of cellular function and toxicity mechanisms. Conventional ROS fluorescence assays involve using a single dye to visualize the ROS quantity. Herein, we describe ROS-sensitive, fluorescent-dye-incorporated carbon dots with dual fluorescence capabilities and good biocompatibility. Carbon dots (CDs) made of citric acid and urea were synthesized with incorporated cyanine-3-amine (Cy3), a bright red fluorescent dye, to create Cy3-CDs. Additionally, to get Cy3 into the ROS-sensitive form, this work demonstrated that Cy3 alone and Cy3 within carbon dots can be electrochemically reduced to their colorless ROS-sensitive form. Cy3, CDs, and Cy3-CDs are all responsive to additions of superoxide, leading to an increase in the fluorescence. Overall, this work examines how O 2 •– and additional oxidizers interact with CDs, Cy3, and Cy3-CDs, and molecular-level hypotheses are explored that will inform the design of future carbon dot-based ROS sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗