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At least 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Decoding Active Sites for Highly Efficient Semihydrogenation of Acetylene in Palladium–Copper Nanoalloys

Accurately decoding the three-dimensional atomic structure of surface active sites is essential yet challenging for a rational catalyst design. Here, we used comprehensive techniques combining the pair distribution function and reverse Monte Carlo simulation to reveal the surficial distribution of Pd active sites and adjacent coordination environment in palladium-copper nanoalloys. After the fine-tuning of the atomic arrangement, excellent catalytic performance with 98% ethylene selectivity at complete acetylene conversion was obtained in the Pd 34 Cu 66 nanocatalysts, outperforming most of the reported advanced catalysts. Further, t he quantitative deciphering shows a large number of active sites with a Pd-Pd coordination number of 3 distributed on the surface of Pd 34 Cu 66 nanoalloys, which play a decisive role in highly efficient semihydrogenation. This finding not only opens the way for guiding the precise design of bimetal nanocatalysts from atomic-level insight but also provides a method to resolve the spatial structure of active sites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Correlation between thickness dependent nanoscale structural chemistry and superconducting properties of ultrathin epitaxial NbN films

NbN-based superconductors have attracted interest for superconducting circuits, quantum computation and high frequency devices. The superconducting properties of NbN films are predominately reliant on the microstructure, therefore, an atomic-level understanding of the structure-chemistry is required to achieve high quality epitaxial NbN films. Here, in this study, the thickness-dependent superconducting properties of NbN films (5, 10, and 50 nm) within NbN/AlN/Al 2 O 3 heterostructures are investigated. NbN and AlN were epitaxially grown by an industrial scale physical vapor deposition technique. The role of nanoscale chemistry on the ultrathin NbN superconducting film is investigated at the atomic level for the first time via atom probe tomography, providing three-dimensional atomic distribution, chemical homogeneity, effect of impurities, specially, in secondary phase formations and interfacial abruptness. The NbN film with 5 nm of thickness demonstrates a superconducting transition temperature of 11.2 K as compared to 50 nm NbN films with a transition temperature of 15.3 K. These thickness dependent variation of superconducting properties are associated with the chemical inhomogeneity in terms of in-plane N:Nb distribution, secondary phase formations and NbN/AlN interfacial abruptness as a function of the NbN films thicknesses. The analysis depicts the interplay between the surface/interface and the superconducting properties of ultrathin NbN films. These results provide insights on material design and growth that will enable the development of optimized superconducting NbN films for quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Deterministic Fast Scrambling with Neutral Atom Arrays

Fast scramblers are dynamical quantum systems that produce many-body entanglement on a timescale that grows logarithmically with the system size N. Here, we propose and investigate a family of deterministic, fast scrambling quantum circuits realizable in near-term experiments with arrays of neutral atoms. We show that three experimental tools—nearest-neighbor Rydberg interactions, global single-qubit rotations, and shuffling operations facilitated by an auxiliary tweezer array—are sufficient to generate nonlocal interaction graphs capable of scrambling quantum information using only O(logN) parallel applications of nearest-neighbor gates. These tools enable direct experimental access to fast scrambling dynamics in a highly controlled and programmable way and can be harnessed to produce highly entangled states with varied applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Determination of the Evolution of Heterogeneous Single Metal Atoms and Nanoclusters under Reaction Conditions: Which Are the Working Catalytic Sites?

Identification of active sites in heterogeneous metal catalysts is critical for understanding the reaction mechanism at the molecular level and for designing more efficient catalysts. Because of their structural flexibility, subnanometric metal catalysts, including single atoms and clusters with a few atoms, can exhibit dynamic structural evolution when interacting with substrate molecules, making it difficult to determine the catalytically active sites. Here, Pt catalysts containing selected types of Pt entities (from single atoms to clusters and nanoparticles) have been prepared, and their evolution has been followed, while they were reacting in a variety of heterogeneous catalytic reactions, including selective hydrogenation reactions, CO oxidation, dehydrogenation of propane, and photocatalytic H2 evolution reaction. By in situ X-ray absorption spectroscopy, in situ IR spectroscopy, and high-resolution electron microscopy techniques, we will show that some characterization techniques carried out in an inadequate way can introduce confusion on the interpretation of coordination environment of highly dispersed Pt species. Finally, the combination of catalytic reactivity and in situ characterization techniques shows that, depending on the catalyst–reactant interaction and metal–support interaction, singly dispersed metal atoms can rapidly evolve into metal clusters or nanoparticles, being the working active sites for those abovementioned heterogeneous reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2011

NASA Tech Briefs, August 2011

Topics covered include: Miniature, Variable-Speed Control Moment Gyroscope; NBL Pistol Grip Tool for Underwater Training of Astronauts; HEXPANDO Expanding Head for Fastener-Retention Hexagonal Wrench; Diagonal-Axes Stage for Pointing an Optical Communications Transceiver; Improvements in Speed and Functionality of a 670-GHz Imaging Radar; IONAC-Lite; Large Ka-Band Slot Array for Digital Beam-Forming Applications; Development of a 150-GHz MMIC Module Prototype for Large-Scale CMB Radiation; Coupling Between Waveguide-Fed Slot Arrays; PCB-Based Break-Out Box; Multiple-Beam Detection of Fast Transient Radio Sources; Router Agent Technology for Policy-Based Network Management; Remote Asynchronous Message Service Gateway; Automatic Tie Pointer for In-Situ Pointing Correction; Jitter Correction; MSLICE Sequencing; EOS MLS Level 2 Data Processing Software Version 3; DspaceOgre 3D Graphics Visualization Tool; Metallization for Yb14MnSb11-Based Thermoelectric Materials; Solvent/Non-Solvent Sintering To Make Microsphere Scaffolds; Enhanced Fuel-Optimal Trajectory-Generation Algorithm for Planetary Pinpoint Landing; Self-Cleaning Coatings and Materials for Decontaminating Field-Deployable Land and Water-Based Optical Systems; Separation of Single-Walled Carbon Nanotubes with DEP-FFF; Li Anode Technology for Improved Performance; Post-Fragmentation Whole Genome Amplification-Based Method; Microwave Tissue Soldering for Immediate Wound Closure; Principles, Techniques, and Applications of Tissue Microfluidics; Robotic Scaffolds for Tissue Engineering and Organ Growth; Stress-Driven Selection of Novel Phenotypes; Method for Accurately Calibrating a Spectrometer Using Broadband Light; Catalytic Microtube Rocket Igniter; Stage Cylindrical Immersive Display; Vacuum Camera Cooler; Atomic Oxygen Fluence Monitor; Thermal Management Tools for Propulsion System Trade Studies and Analysis; Introduction to Physical Intelligence; Technique for Solving Electrically Small to Large Structures for Broadband Applications; Accelerated Adaptive MGS Phase Retrieval; Large Eddy Simulation Study for Fluid Disintegration and Mixing; Tropospheric Correction for InSAR Using Interpolated ECMWF Data and GPS Zenith Total Delay; Technique for Calculating Solution Derivatives With Respect to Geometry Parameters in a CFD Code; Acute Radiation Risk and BRYNTRN Organ Dose Projection Graphical User Interface; Probabilistic Path Planning of Montgolfier Balloons in Strong, Uncertain Wind Fields; Flight Simulation of ARES in the Mars Environment; Low-Outgassing Photogrammetry Targets for Use in Outer Space; Planning the FUSE Mission Using the SOVA Algorithm; Monitoring Spacecraft Telemetry Via Optical or RF Link; and Robust Thermal Control of Propulsion Lines for Space Missions.

Source record↗
NASA NTRS2003

Diagnostics of Carbon Nanotube Formation in a Laser Produced Plume: An Investigation of the Metal Catalyst by Laser Ablation Atomic Fluorescence Spectroscopy

Carbon nanotubes, elongated molecular tubes with diameters of nanometers and lengths in microns, hold great promise for material science. Hopes for super strong light-weight material to be used in spacecraft design is the driving force behind nanotube work at JSC. The molecular nature of these materials requires the appropriate tools for investigation of their structure, properties, and formation. The mechanism of nanotube formation is of particular interest because it may hold keys to controlling the formation of different types of nanotubes and allow them to be produced in much greater quantities at less cost than is currently available. This summer's work involved the interpretation of data taken last summer and analyzed over the academic year. The work involved diagnostic studies of carbon nanotube formation processes occurring in a laser-produced plume. Laser ablation of metal doped graphite to produce a plasma plume in which carbon nanotubes self assemble is one method of making carbon nanotube. The laser ablation method is amenable to applying the techniques of laser spectroscopy, a powerful tool for probing the energies and dynamics of atomic and molecular species. The experimental work performed last summer involved probing one of the metal catalysts, nickel, by laser induced fluorescence. The nickel atom was studied as a function of oven temperature, probe laser wavelength, time after ablation, and position in the laser produced plume. This data along with previously obtained data on carbon was analyzed over the academic year. Interpretations of the data were developed this summer along with discussions of future work. The temperature of the oven in which the target is ablated greatly influences the amount of material ablated and the propagation of the plume. The ablation conditions and the time scale of atomic and molecular lifetimes suggest that initial ablation of the metal doped carbon target results in atomic and small molecular species. The metal atoms survive for several milliseconds while the gaseous carbon atoms and small molecules nucleate more rapidly. Additional experiments and the development of in situ methods for carbon nanotube detection would allow these results to be interpreted from the perspective of carbon nanotube formation.

deBoer, Gary↗
DOE OSTI2022

Realistic simulations of spin squeezing and cooperative coupling effects in large ensembles of interacting two-level systems

We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which combines the mean-field dynamics of a spin ensemble with a Monte Carlo sampling of discrete initial spin values to account for quantum correlations. Here we show how this approach can be generalized for dissipative spin systems by replacing the deterministic mean-field evolution by a stochastic process, which describes the decay of coherences and populations while preserving the length of each spin. We demonstrate the application of this technique for simulating nonclassical spin-squeezing effects or the dynamics and steady states of cavity QED models with 10 5 interacting two-level systems. This opens up the possibility to perform accurate real-scale simulations of a diverse range of experiments in quantum optics or with solid-state spin ensembles under realistic laboratory conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

We present a new interatomic potential for solids and liquids called Spectral Neighbor Analysis Potential (SNAP). The SNAP potential has a very general form and uses machine-learning techniques to reproduce the energies, forces, and stress tensors of a large set of small configurations of atoms, which are obtained using high-accuracy quantum electronic structure (QM) calculations. The local environment of each atom is characterized by a set of bispectrum components of the local neighbor density projected onto a basis of hyperspherical harmonics in four dimensions. The bispectrum components are the same bond-orientational order parameters employed by the GAP potential [1]. The SNAP potential, unlike GAP, assumes a linear relationship between atom energy and bispectrum components. The linear SNAP coefficients are determined using weighted least-squares linear regression against the full QM training set. This allows the SNAP potential to be fit in a robust, automated manner to large QM data sets using many bispectrum components. The calculation of the bispectrum components and the SNAP potential are implemented in the LAMMPS parallel molecular dynamics code. We demonstrate that a previously unnoticed symmetry property can be exploited to reduce the computational cost of the force calculations by more than one order of magnitude. We present results for a SNAP potential for tantalum, showing that it accurately reproduces a range of commonly calculated properties of both the crystalline solid and the liquid phases. In addition, unlike simpler existing potentials, SNAP correctly predicts the energy barrier for screw dislocation migration in BCC tantalum.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Accessing Atomic-scale Phosphorus Dopant Distribution in Precise Silicon Devices by Advanced STEM Imaging and Spectroscopy

The structural and chemical characterization at the atomic-scale plays a critical role in understanding the structure-property relationship in precise electrical devices such as those produced by atomic-precision advanced manufacturing (APAM). APAM, utilizing hydrogen lithography in a scanning tunneling microscope, offers a potential pathway to ultra-efficient transistors, and has been developed to produce phosphorus (P)-based donor devices integrated into bare Si substrates. Structural characterization of the buried, Si with P dopant (Si:P) delta-layer in the devices by scanning transmission electron microscopy (STEM), however, is a challenge due to similar atomic number and low concentration of the P dopants. In this paper, we describe several efforts of utilizing advanced STEM imagining and spectroscopic techniques to quantify the Si:P deltalayers. STEM imaging combining low-angle and high-angle annular dark-field (LAADF, HAADF) detectors as well as atomic-scale elemental mapping using energy-dispersive X-ray spectroscopy (EDS) are used to reveal the P and defect distribution across the delta-layer processed under various thermal conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Effect of nano particle sizes on the third-order optical non-linearities and nanostructure of copolymer P3HT:PCBM thin film for organic photovoltaics

Highlights: • Active layer (P3HT:PCBM) has been deposited on substrate type by spin coating at 1000 rpm. • The device was completed by evaporating a 60 nm thick, circular gold electrodes onto the P3HT:PCBM. • Nonlinear refractive indices of the three particle sizes are found to be of the order of 10{sup −7} cm{sup 2}/W - Abstract: Organic solar cells are based on (3-hexylthiophene):[6,6]-phenyl C61-butyric acid with methyl ester Bulk Heterojunction. An inverted structure has been fabricated using nano-anatase crystalline titanium dioxide, as the electron transport layer, which was prepared on either the Indium Tin Oxide coated glass (ITO—glass), or Silicon wafer, as well as on glass substrates by the sol–gel method, at different spin speed, using the spin-coating system. The effect of thickness on the surface morphology and on the optical properties of TiO{sub 2} layer, was investigated using the Atomic Force Microscopy (AFM), X-ray diffraction, and UV–visible spectrophotometer. The samples were examined to feature currents and voltages, in the darkness and light extraction efficiency of the solar cell. The highest open-circuit voltage, V{sub oc}, and power conversion efficiency were 0.66% and 0.39%, fabricated with 90 nm, respectively. The non-linear optical properties of nano-anatase TiO{sub 2} sol–gel, were investigated at different particle sizes, using the z-scan technique.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Neural Network Interatomic Potentials

In this project, we investigate the use of neural networks for the prediction of molecular properties, namely the interatomic potential. We use the machine learning package Tensorflow to build a variety of neural networks and compare performance with a popular Fortran package - Atomic Energy Networks (aenet). There are two primary goals for this work: 1) use the wide availability of different optimization techniques in Tensorflow to outperform aenet and 2) use new descriptors that can outperform Behler descriptors.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Emerging Electron Microscopy Techniques for Probing Functional Interfaces in Energy Materials

Interfaces play a fundamental role in many areas of chemistry. However, their localized nature requires characterization techniques with high spatial resolution in order to fully understand their structure and properties. State-of-the-art atomic resolution or in situ scanning transmission electron microscopy and electron energy-loss spectroscopy are indispensable tools for characterizing the local structure and chemistry of materials with single-atom resolution, but they are not able to measure many properties that dictate function, such as vibrational modes or charge transfer, and are limited to room-temperature samples containing no liquids. Here, we outline emerging electron microscopy techniques that are allowing these limitations to be overcome and highlight several recent studies that were enabled by these techniques. We then provide a vision for how these techniques can be paired with each other and with in situ methods to deliver new insights into the static and dynamic behavior of functional interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2023

Modeling of transient interference phenomena in colinear laser spectroscopy

Colinear laser spectroscopy of fast atomic beams has been established as one of the main tools to perform precision experiments with atoms containing short-lived nuclei. Although highly sensitive, the spectral resolution of these techniques is typically limited to several MHz. Here, we study the use of transient interference phenomena to potentially improve the experimental resolution. Previous attempts to implement Ramsey-type measurements with fast beams were limited by the lack of understanding of the observed line shapes. Additionally, by using a simple model, we provide a satisfactory description of the previously observed line shapes and propose alternative experimental schemes to improve the resolution in fast ion-beam experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

First-Principles Simulation of Beam-Induced Processes Underlying Atomic Manipulation in Electron Microscopes

The development of experimental methods and apparatuses capable of promoting atomically precise material manipulations holds great promise for realizing the ultimate limit of feature miniaturization in materials and devices. The ability to modify materials atom by atom is anticipated to usher in new technologies in areas as diverse as separation science, medicine, and quantum information science. Historically, scanning probe-based techniques have been the most prominent approaches in this space. However, these methods are best suited for the manipulation of surface-exposed regions of materials, as the strong perturbations required for bond scission are delivered most effectively to atoms in the near-proximity to the scanning probe. In contrast, convergent electron beams with energies tuned slightly below the threshold for inducing irreversible knock-on damage have recently been employed (within scanning transmission electron microscopy) to promote atomic-scale bond rearrangements in various beam-stable solids. Currently, however, the efficiency and selectivity of beam-induced atomic manipulation processes with focused electron beams are such that long irradiation times are required to induce a desired atomic rearrangement. With a better understanding of the underlying physics dictating the outcome of a given irradiation event, methods can be devised to improve the efficiency of these techniques so that their promise can be fully realized through widespread adoption.To this end, this Account details our recent efforts to develop and apply tractable first-principles simulation approaches for studying the response of materials to electric beam-like external electric potentials applied in real space. We briefly review the concepts and capabilities in the area of atomically precise materials manipulation and review the early demonstrations of accomplishments in this area, focusing on studies using scanned convergent electron beam probes in particular. We expound upon the depth of the challenge and identify critical shortcomings of theoretical methods that have previously been employed in the simulation of beam-induced processes. We then describe the computational methods that we have generalized from the concepts and tools most commonly applied to the study of molecular photochemistry and how our adaptations of these methods can be employed to capture the relevant dynamical phenomena for beam-induced processes ranging from the initial electron scattering to the ensuing multistate reactions. Here, we contextualize these methods within the current state of the art in this area, which has historically focused primarily on the simulation of inelastic image formation in the electron microscope for the purpose of interpreting the results of quantitative electron microscopy experiments. We demonstrate that the spatial distribution of state-specific excitation rates due to the presence of an external (probe) electric charge is inhomogeneous, such that irradiation at particular locations in materials can favor specific electronic transitions (and disallow others). In addition to the potential for excited-state reaction pathways to be accessed through the initial inelastic scattering of the tightly focused electron beam from the targeted atoms, we also identify favorable conditions for the electronically nonadiabatic evolution of the highly vibrationally excited system to open complex multistate reaction pathways. Implications of the early results for understanding the mechanisms and potential routes to improved efficiency and selectivity in beam-induced reactions are discussed. We conclude with a summary of the current state of theory and modeling capabilities in this area and provide our perspective on future directions for theoretical and experimental developments that we view as crucial to advancing the use of convergent electron beams in mode-specific, atomically precise platforms for direct-write materials modifications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Effective optimization of atomic decoration in giant and superstructurally ordered crystals with machine learning

Crystals with complicated geometry are often observed with mixed chemical occupancy among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar systems possessing exact occupancy on all the sites can exhibit superstructural ordering, dramatically inflating the unit cell size. In this work, a crystal graph convolutional neural network (CGCNN) is used to predict optimal atomic decorations on fixed crystalline geometries. This is achieved with a site permutation search (SPS) optimization algorithm based on Monte Carlo moves combined with simulated annealing and basin-hopping techniques. Our approach relies on the evidence that, for a given chemical composition, a CGCNN estimates the correct energetic ordering of different atomic decorations, as predicted by electronic structure calculations. This provides a suitable energy landscape that can be optimized according to site occupation, allowing the prediction of chemical decoration in crystals exhibiting mixed or disordered occupancy, or superstructural ordering. Verification of the procedure is carried out on several known compounds, including the superstructurally ordered clathrate compound Rb8Ga27Sb16 and vacancy-ordered perovskite Cs2SnI6, neither of which was previously seen during the neural network training. In addition, the critical temperature of an order–disorder phase transition in solid solution CuZn is probed with our SPS routines by sampling site configuration trajectories in the canonical ensemble. This strategy provides an accurate method for determining favorable decoration in complex crystals and analyzing site occupation at unprecedented speed and scale.

Chemistry↗
DOE OSTI2014

Polarization controlled deep sub-wavelength periodic features written by femtosecond laser on nanodiamond thin film surface

Deep sub-wavelength (Λ/λ = ∼0.22) periodic features are induced uniformly on a nanodiamond (ND) thin film surface using femtosecond (fs) laser irradiation (pulse duration = ∼110 fs and central wavelength of ∼800 nm). The topography of the surface features is controlled by the laser polarization. Orientation of features is perpendicular to laser polarization. Periodicity (spatial periodicity of < λ/4) of the surface features is less than the laser wavelength. This work gives an experimental proof of polarization controlled surface plasmon-fs laser coupling mechanism prompting the interaction between fs laser and solid matter (here ND thin film) which in turn is resulting in the periodic surface features. Scanning electron microscopy in conjunction with micro Raman scattering, X-ray diffraction, and atomic force microscopy are carried out to extract surface morphology and phase information of the laser irradiated regions. This work demonstrates an easy and efficient surface fabrication technique.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1998

Atomic Oxygen Treatment as a Method of Recovering Smoke Damaged Paintings

Smoke damage, as a result of a fire, can be difficult to remove from some types of painting media without causing swelling, leaching or pigment movement or removal. A non-contact technique has been developed which can remove soot from the surface of a painting by use of a gently flowing gas containing atomic oxygen. The atomic oxygen chemically reacts with the soot on the surface creating gasses such as carbon monoxide and carbon dioxide which can be removed through the use of an exhaust system. The reaction is limited to the surface so that the process can be timed to stop when the paint layer is reached. Atomic oxygen is a primary component of the low Earth orbital environment, but can be generated on Earth through various methods. This paper will discuss the results of atomic oxygen treatment of soot exposed acrylic gesso, ink on paper, and a varnished oil painting. Reflectance measurements were used to characterize the surfaces before and after treatment.

Rutledge, Sharon K.↗