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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

RadVolViz: An Information Display-Inspired Transfer Function Editor for Multivariate Volume Visualization

In volume visualization transfer functions are widely used for mapping voxel properties to color and opacity. Typically, volume density data are scalars which require simple 1D transfer functions to achieve this mapping. If the volume densities are vectors of three channels, one can straightforwardly map each channel to either red, green or blue, which requires a trivial extension of the 1D transfer function editor. Here, we devise a new method that applies to volume data with more than three channels. These types of data often arise in scientific scanning applications, where the data are separated into spectral bands or chemical elements. Our method expands on prior work in which a multivariate information display, RadViz, was fused with a radial color map, in order to visualize multi-band 2D images. In this work, we extend this joint interface to blended volume rendering. The information display allows users to recognize the presence and value distribution of the multivariate voxels and the joint volume rendering display visualizes their spatial distribution. We design a set of operators and lenses that allow users to interactively control the mapping of the multivariate voxels to opacity and color. This enables users to isolate or emphasize volumetric structures with desired multivariate properties. Furthermore, it turns out that our method also enables more insightful displays even for RGB data. We demonstrate our method with three datasets obtained from spectral electron microscopy, high energy X-ray scanning, and atmospheric science.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-throughput experimentation for microstructural design in additively manufactured 316L stainless steel

In the present study, a combination of high-throughput (HT) and low-throughput (LT) techniques was used to rapidly determine the processing window and generate processing maps for Selective Laser Melting (SLM) of 316L stainless steel. The HT method includes the fabrication of hundreds of hex nut-shaped specimens, each processed with a unique combination of laser power, scanning speed, and hatch spacing. An easily removable scaffolding permitted rapid sample extraction from the base plate, thus saving machining cost and time. Hardness and immersion density measurements were used for HT characterization to identify a processing window for maximum strength and density. Within the defined processing window, a low-throughput (LT) microstructural interrogation of specimens were performed. The microstructural analysis included quantification at various length scales (i.e., grains size and morphology, texture, primary dendrite arm spacing, and melt pool geometry analysis). Microstructure-based processing maps as a function of volumetric energy density were generated. The combination of HT and LT methods produced a predictive relationship between hardness and primary dendrite arm spacing using a Hall-Petch relationship. A model is proposed to explain the dependence of microstructure on the melt pool geometry. Here, the HT method can be applied for the microstructural design of SLM-fabricated components in other alloys.

316L stainless steel↗
DOE OSTI2023

Simulating and Optimizing Quantum State Transport

The goal of this project was to produce an accurate simulator of the “pitch and catch” process of sending quantum states between SRF cavities, and to find a method for optimizing the control pumps. We developed a program in C++ to integrate the equations of motion with high speed and precision, and used this as a basis for finding an optimal control function to maximize the state transfer efficiency. To demonstrate this we have shown an example of an optimal drive function and the resulting system dynamics, as well as a heat map of the cost function for a range of drive amplitudes.

Weston, Jacob↗
DOE OSTI2017

Novel Analysis and Visualization of Chemical Events for Public Health Surveillance

Pacific Northwest National Laboratory hosted an intern-based web application development contest in the summer of 2016 centered around developing novel chemical surveillance applications to aid in health situational awareness. Making up the three teams were three graduate students (n=9) from various US schools majoring in non-public health domains, such as computer science and user design. The interns successfully developed three applications that demonstrated a value-add to chemical surveillance—ChemAnalyzer (text analytics), RetroSpect (retrospective analysis of chemical events),and ToxicBusters (geo-based trend analytics). These applications will be the basis for the first chemical surveillance application to be incorporated into the DTRA Biosurveillance Ecosystem (BSVE).Pacific Northwest National Laboratory (PNNL), on behalf the Defense Threat Reduction Agency (DTRA; project number CB10190), hosts an annual intern- based web app development contest. Previous competitions have focused on mobile biosurveillance. The 2016 competition pivoted away from biosurveillance to focus on addressing challenges within the field of chemical surveillance and increasing public health chemical situational awareness. The result of the app will be integrated within the DTRA BSVE. PNNL hosted nine graduate interns for a 10-week period in the summer of 2016 as participants in a summer web application development contest. Students were drawn from such fields as software engineering and user experience and design and placed into three teams of three students. The challenge presented to the interns was to design and develop a fully-functional web application that would address a critical need within the chemical surveillance community. The interns developed their own ideas (vetted by PNNL and DTRA), discovered and integrated their own data sources, and produced their own visualizations and analytics, independent of any assistance outside of that provided in an advisory capacity. The competition end with a judging event with a panel of subject matter experts and cash awards were distributed to the teams. Each team produced a unique application. Although there was mild overlap between some of the ideas, the applications were developed independently and each reflected the unique contributions of the teams. ChemAnalyzer is a text-analytics platform designed to facilitate more data-driven decision, given a corpus of text data about a chemical event. Their platform provided the ability to automatically identify and highlight key words in documents related to chemical events. The keywords are drawn from an ontology installed with the system, as well as any user-identified keywords. The ChemAnalyzer team finished in third place. The RetroSpect team developed a visual analytic tool for performing retrospective analysis and monitoring of chemical events. Their app provided the ability to search and analyze past events, as well as visualization of state and county information for the recorded chemical events. The RetroSpect team finished in second place. The Toxic busters team - the winners of the competition - created a geo-based situational awareness tool for tracking chemical events. Their app featured an updateable map overlay, search functionality for finding specific or related events, incident and city/state/national-level statistics and trends, as well as news and social media integration based on keywords related to chemical surveillance. Each of the apps developed by the teams provides value to an analyst tasked with monitoring chemical events. The apps integrated unique data sources to provides a full picture of a chemical event, and its effects upon the surrounding population. This integrated analytics provides a valuable benefit over existing workflows, where analysts must monitor news, social, and other information sources manually for real-time information. The apps developed by these interns are designed to enable identification and analysis of the incident as quickly as possible, allowing for more timely assessments of the incident and its impacts. The web app development contest provided a unique opportunity for students to learn about the emerging needs in chemical surveillance as it relates to health situational awareness. Students were drawn from a variety of fields and were tasked with developing novel web apps addressing some of the most pressing challenges in the field of chemical surveillance. The ideas generated by the students will help form the basis for future chemical surveillance application development to be integrated with the DTRABSVE.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Some constructions on total labelling of m triangles

Let mK{sub 3} = (V{sub m}, E{sub m}) be a finite disconnected graph consisting of m disjoint triangles K{sub 3}, where V{sub m} is the set of vertices, E{sub m} is the set of edges and both V{sub m} and E{sub m} are of the same size 3m. A total labelling of mK{sub 3} is a function f which maps the elements in V{sub m} and E{sub m} to positive integer values, i.e. f : V{sub m} ∪ E{sub m} → {1, 2, 3,···}. Let c be a positive integer. A triangle is said have a c-Erdősian triangle labelling if it is a total labelling f : V{sub m} ∪ E{sub m} → {c, c + 1, ···, c + 6m − 1} such that f (x) + f (y) = f (xy) for any x, y ∈ V{sub m} and an edge xy ∈ E{sub m} joining them. In order to find all the c-Erdősian triangle labelling, a straightforward is to use the exhaustive search. However, the exhaustive search is only able to find c-Erdősian triangle labelling for m ≤ 5 due to combinatorial explosion. By studying the constant sum of vertex labels, we propose a strong permutation approach, which allows us to generate a certain classes of c-Erdősian triangle labelling up until m = 8.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Reducing systematic error in weak lensing cluster surveys

Weak lensing provides an important route toward collecting samples of clusters of galaxies selected by mass. Subtle systematic errors in image reduction can compromise the power of this technique. We use the B-mode signal to quantify this systematic error and to test methods for reducing this error. We show that two procedures are efficient in suppressing systematic error in the B-mode: (1) refinement of the mosaic CCD warping procedure to conform to absolute celestial coordinates and (2) truncation of the smoothing procedure on a scale of 10'. Application of these procedures reduces the systematic error to 20% of its original amplitude. We provide an analytic expression for the distribution of the highest peaks in noise maps that can be used to estimate the fraction of false peaks in the weak-lensing κ-signal-to-noise ratio (S/N) maps as a function of the detection threshold. Based on this analysis, we select a threshold S/N = 4.56 for identifying an uncontaminated set of weak-lensing peaks in two test fields covering a total area of ∼3 deg{sup 2}. Taken together these fields contain seven peaks above the threshold. Among these, six are probable systems of galaxies and one is a superposition. We confirm the reliability of these peaks with dense redshift surveys, X-ray, and imaging observations. The systematic error reduction procedures we apply are general and can be applied to future large-area weak-lensing surveys. Our high-peak analysis suggests that with an S/N threshold of 4.5, there should be only 2.7 spurious weak-lensing peaks even in an area of 1000 deg{sup 2}, where we expect ∼2000 peaks based on our Subaru fields.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A relativistically interacting exactly solvable multi-time model for two massless Dirac particles in 1 + 1 dimensions

The question how to Lorentz transform an N-particle wave function naturally leads to the concept of a so-called multi-time wave function, i.e., a map from (space-time){sup N} to a spin space. This concept was originally proposed by Dirac as the basis of relativistic quantum mechanics. In such a view, interaction potentials are mathematically inconsistent. This fact motivates the search for new mechanisms for relativistic interactions. In this paper, we explore the idea that relativistic interaction can be described by boundary conditions on the set of coincidence points of two particles in space-time. This extends ideas from zero-range physics to a relativistic setting. We illustrate the idea at the simplest model which still possesses essential physical properties like Lorentz invariance and a positive definite density: two-time equations for massless Dirac particles in 1 + 1 dimensions. In order to deal with a spatio-temporally non-trivial domain, a necessity in the multi-time picture, we develop a new method to prove existence and uniqueness of classical solutions: a generalized version of the method of characteristics. Both mathematical and physical considerations are combined to precisely formulate and answer the questions of probability conservation, Lorentz invariance, interaction, and antisymmetry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Field validation of data-driven BSDF and peak extraction models for light-scattering fabric shades

Shading and daylighting systems affect cooling, heating, and lighting energy use by modulating solar radiation through the building façade. Characterizing shading systems holistically and accurately helps designers and engineers evaluate shading systems to achieve energy and non-energy performance goals. These complex fenestration systems can be modeled using Bidirectional Scattering Distribution Functions (BSDF), which map incident radiation to hemispherical distributions of outgoing radiation. Data-driven, tabulated BSDFs are derived from interpolated goniophotometer measured data, then sampled during the raytracing calculation. A peak extraction (PE) algorithm was developed to circumvent limits in BSDF angular resolution, where the specular peak is extracted during simulation by evaluating the BSDF in the through direction and surrounding region. The objective of this study was to validate this measurement and modeling workflow using field monitored data from a full scale testbed with eleven installed fabrics of different weaves, openness factors, and colors and assess the accuracy of the workflow under different adaptation and contrast conditions. Test conditions were limited to clear sky conditions with the sun in the field of view. Results showed that, for tensor tree datasets, vertical illuminance, solar luminance (2.5° apex), and daylight glare probability (DGP) were predicted to within a mean bias error (MBE) error of -456 lx (-12.3%), -3.46e5 (-38.4%), and -0.042 (-7.8%) when full PE occurred. With a binary classification of glare/ no glare, DGP was predicted accurately with a true positive rate of 0.98 and true negative rate of 1.0 using tensor tree data and less accurately with Klems BSDF data, particularly for cases of no glare. The workflow may be of insufficient accuracy to distinguish borderline performance between fabrics using the four-point glare scale, particularly under low adaptation, high contrast daylit conditions. Errors were due to reductions in peak shape and intensity across the BSDF interpolation and data reduction workflow. Future work is needed to better preserve measurement fidelity during interpolation and sampling, which in turn will improve PE performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

X-ray fluorescence mapping: Insights into mesoscale structure impact on battery functional electrochemistry

Abstract Electron transfer and ion transport occurs over multiple-length scales ranging from the atomic to mesoscale within battery materials and electrodes. Micro-X-ray fluorescence (µ-XRF) is an important characterization tool as it can resolve structural, compositional, and redox information while providing insight into the spatial distribution of an electroactive material. In this work, µ-XRF mapping is used to probe the distribution of iron within thin planar slurry-based and thick porous carbon nanotube (CNT)-based magnetite (Fe 3 O 4 ) electrodes. Notably, the porous CNT-based electrode showed homogenous distribution of Fe within the electrode whereas the planar electrode demonstrated distinct Fe aggregates. This information was used to rationalize the electrochemistry observed by cyclic voltammetry and galvanostatic cycling. The thick porous electrode delivered 215% more capacity per gram of magnetite during the first discharge, consistent with increased electrode homogeneity enabling effective ion access and electron transfer. Graphical Abstract

Sadique, Nahian↗
DOE OSTI2023

Energy landscapes from cryo-EM snapshots: a benchmarking study

Abstract Biomolecules undergo continuous conformational motions, a subset of which are functionally relevant. Understanding, and ultimately controlling biomolecular function are predicated on the ability to map continuous conformational motions, and identify the functionally relevant conformational trajectories. For equilibrium and near-equilibrium processes, function proceeds along minimum-energy pathways on one or more energy landscapes, because higher-energy conformations are only weakly occupied. With the growing interest in identifying functional trajectories, the need for reliable mapping of energy landscapes has become paramount. In response, various data-analytical tools for determining structural variability are emerging. A key question concerns the veracity with which each data-analytical tool can extract functionally relevant conformational trajectories from a collection of single-particle cryo-EM snapshots. Using synthetic data as an independently known ground truth, we benchmark the ability of four leading algorithms to determine biomolecular energy landscapes and identify the functionally relevant conformational paths on these landscapes. Such benchmarking is essential for systematic progress toward atomic-level movies of continuous biomolecular function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

The E2-25K ubiquitin-associated (UBA) domain aids in polyubiquitin chain synthesis and linkage specificity

Research highlights: {yields} We examine the role of a ubiquitin-associated (UBA) domain in an E2 enzyme. {yields} The E2-25K UBA domain directs polyubiquitin chain linkage specificity. {yields} The E2-25K UBA domain regulates length of polyubiquitin chains synthesized. -- Abstract: E2-25K is an ubiquitin-conjugating enzyme with the ability to synthesize Lys48-linked polyubiquitin chains. E2-25K and its homologs represent the only known E2 enzymes which contain a C-terminal ubiquitin-associated (UBA) domain as well as the conserved catalytic ubiquitin-conjugating (UBC) domain. As an additional non-covalent binding surface for ubiquitin, the UBA domain must provide some functional specialization. We mapped the protein-protein interface involved in the E2-25K UBA/ubiquitin complex by solution nuclear magnetic resonance (NMR) spectroscopy and subsequently modeled the structure of the complex. Domain-domain interactions between the E2-25K catalytic UBC domain and the UBA domain do not induce significant structural changes in the UBA domain or alter the affinity of the UBA domain for ubiquitin. We determined that one of the roles of the C-terminal UBA domain, in the context of E2-25K, is to increase processivity in Lys48-linked polyubiquitin chain synthesis, possibly through increased binding to the ubiquitinated substrate. Additionally, we see evidence that the UBA domain directs specificity in polyubiquitin chain linkage.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Fourier-based methods for removing mesh anomalies from angle resolved photoemission spectra

Recent improvements to spatial resolution in angle-resolved photo-emission spectroscopy (ARPES) have made it common to perform measurements with a very brief dwell time, for the purpose of mapping the spectral function over large surface regions. However, rapid measurement modalities can suffer a grid-like intensity modulation due to a wire mesh that is typically placed in front of the ARPES detector to block stray electrons. Here, we explore Fourier-based methods that can effectively remove this artifact, and improve the quality of ARPES images obtained in rapid scanning modes. In conclusion, an open source software package is provided containing implementations of demonstrated algorithms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

42 ENGINEERING↗
DOE OSTI2020

Homoepitaxial growth of 9,10-diphenylanthracene

Organic single crystals are often shown to have significantly improved optoelectronic properties over polycrystalline thin films such as exciton diffusivity and carrier mobility. There is growing interest in incorporating such crystals in organic electronics despite a number of challenges. In this work, the homoepitaxial vapor phase growth modes for 9,10-diphenylanthracene (DPA) homoepitaxy are mapped as a function of growth rate and temperature using in situ ultra-low current reflection high energy electron diffraction (RHEED), X-ray diffraction (XRD), and atomic force microscopy (AFM). Vapor phase deposition was performed on free-standing single crystal DPA substrates, which show clear Kikuchi patterns. At room temperature, a transition from Frank-Van der Merwe layer-by-layer growth to step-flow growth is observed as the deposition rate is decreased, while at lower temperatures a Stranski-Krastanov layer-plus-island growth is observed. This is the first demonstration of true step-flow growth from room temperature vapor phase deposition for organic semiconductors and is reminiscent of traditional semiconductor growth regimes. Accordingly, these results could lead to improved control over growth and doping of organic single crystals, and lead to enhanced single crystal organic optoelectronic applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

EBSD characterization of high-temperature phase transformations in an Al-Si coating on Cr-Mo steel

5Cr-0.5Mo steel was coated by hot-dipping in a molten bath containing Al-10 wt.% Si. The phase transformation in the aluminide layer during diffusion at 750 Degree-Sign C in static air was analyzed by electron backscatter diffraction. The results show the aluminide layer of the as-coated specimen consisted of an outer Al-Si topcoat, a middle layer formed of scattered {tau}{sub 5(C)}-Al{sub 7}(Fe,Cr){sub 2}Si particles and minor plate-shaped {tau}{sub 4}-Al{sub 4}FeSi{sub 2} and {tau}{sub 6}-Al{sub 4}FeSi phases in the Al-Si matrix and an inner continuous {tau}{sub 5(H)}-Al{sub 7}Fe{sub 2}Si layer, respectively from the coating surface to the steel substrate. The formation of FeAl{sub 3} and Fe{sub 2}Al{sub 5} with {tau}{sub 1}-(Al,Si){sub 5}Fe{sub 3} precipitates can be observed with increasing exposure time at 750 Degree-Sign C. After 5 h of exposure, the Al-Si topcoat has been consumed, and the aluminide layer consisted of Fe{sub 2}Al{sub 5} and a few {tau}{sub 1}-(Al,Si){sub 5}Fe{sub 3} precipitates. The FeAl phase not only formed at the interface between Fe{sub 2}Al{sub 5} and the steel substrate, but also transformed from {tau}{sub 1}-(Al,Si){sub 5}Fe{sub 3} after diffusion for 10 h. With prolonged exposure, the aluminide layer comprised only FeAl{sub 2} and FeAl. - Highlights: Black-Right-Pointing-Pointer EBSD can differentiate phases in aluminide layer with similar chemical compositions. Black-Right-Pointing-Pointer Mapping and EBSPs functions in EBSD provide a reliable phase identification. Black-Right-Pointing-Pointer A phase transformation in the aluminide layer has been described in detail. Black-Right-Pointing-Pointer 5 Fe-Al-Si and 4 Fe-Al intermetallic phases are performed during the diffusion. Black-Right-Pointing-Pointer Cubic {tau}{sub 5(C)}-Al{sub 7} (Fe,Cr){sub 2}Si and hexagonal {tau}{sub 5(H)}-Al{sub 7}(Fe,Cr){sub 2}Si are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Study of Void Formation at the Lithium|Solid Electrolyte Interface

There is growing recognition of the critical role of void formation in lithium metal anodes in solid-state batteries and its impact on electrochemical performance. While experimental studies have demonstrated the challenges ensuing from void formation at the lithium metal interface with the solid electrolyte, there is a need to understand and quantify the role of intrinsic transport properties in lithium metal and the impact of external stimuli, such as temperature, pressure, and current density. Here, we develop this understanding by constructing a phase field-based model that captures the evolution of void domains at the lithium-solid electrolyte interface. Growth of the pores is driven by the fast removal of lithium from the interface during stripping at high current densities. Relative magnitudes of the bulk and surface lithium diffusivities, along with the applied current density, dictate the final pore morphology. Increasing the temperature results in faster diffusion, while external applied pressure causes creep flow of lithium, both of which help to mitigate the evolution of voids by quickly transporting metal from the bulk to the interface. Finally, a phase map as a function of temperature and pressure is developed as a guide to determine the regions that can lead to the stable cycling of lithium metal.

25 ENERGY STORAGE↗
DOE OSTI2015

Temperature Distribution within a Cold Cap during Nuclear Waste Vitrification

The kinetics of the feed-to-glass conversion affects the waste vitrification rate in an electric melter. In this study, the primary area of interest in this conversion process is the cold cap, a layer of reacting feed on top of molten glass. Knowing the temperature profile within a cold cap will help determine its characteristics and relate them to the rate of glass production. The work presented here provides an experimental determination of the temperature distribution within the cold cap. Since a direct measurement of the temperature field within the cold cap is impracticable, an indirect method was developed where the textural features in a laboratory-made cold cap with a high-level waste feed were mapped as a function of position using optical microscopy, scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffraction. To correlate the temperature distribution to microstructures within the cold cap, microstructures were identified of individual feed samples that were heat treated to set temperatures between 400°C and 1200°C and quenched. The temperature distribution within the cold cap was then established by correlating cold-cap regions with the feed samples of nearly identical structures and was compared with the temperature profile from a mathematical model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Suppressing Molecular Charging, Nanochemistry, and Optical Rectification in the Tip-Enhanced Raman Geometry

Classical vs quantum plasmons are operative in tapping vs contact mode tip-enhanced Raman scattering (TERS) and lead to distinct observables. Under otherwise identical experimental conditions, we illustrate the concept through tapping and contact mode TERS mapping of chemically functionalized silver nanocubes. Whereas molecular charging, chemical transformations, and optical rectification are prominent observables in contact mode TERS, the same effects are suppressed using tapping mode feedback. In effect, this work demonstrates that nanoscale physical and chemical processes can be accessed/suppressed on-demand in the TERS geometry. Further, the advantages of tapping mode TERS are otherwise highlighted with the latter in mind.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗