Optimized Substrates for Analysis of an Individual Atmospheric Particle Across Multiple Microspectroscopy Techniques: Fabrication and Characterization
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Kolozsvari, Katherine R. A.↗
SEARCH · Engineering Papers
Results for “characterization techniques”
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Recent Advancements in Tools and Techniques for Materials Characterization in the EML [Slides]
Abstract not provided.
36 MATERIALS SCIENCE↗
Bayesian Techniques for Accelerator Characterization and Control
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Roussel, R. J.↗
Microstructure and water absorption of ancient concrete from Pompeii: An integrated synchrotron microtomography and neutron radiography characterization
There is renewed interest in using advanced techniques to characterize ancient Roman concrete due to its exceptional durability and low-carbon footprint. In the present work, samples were drilled from the “Hospitium” in Pompeii and were analyzed by synchrotron microtomography (μCT) and neutron radiography to study how the microstructure, including the presence of induced cracks, affects their water adsorption. The water distribution and absorptivity were quantified by neutron radiography. The 3D crack propagation, pore size distribution and orientation, tortuosity, and connectivity were analyzed from μCT results using advanced imaging methods. Porosity was also measured by mercury intrusion porosimetry (MIP) as a reference. Ductile fracture patterns were observed once cracks were introduced. Compared to Portland cement mortar/concrete, the Pompeii samples had relatively high porosity, low connectivity, and a similar coefficient of capillary penetration. In addition, permeability was predicted from models based on percolation theory and pore structure data to evaluate the fluid transport properties. Understanding the microstructure of ancient Pompeii concrete is important because it could inspire the development of modern concrete with high durability.
36 MATERIALS SCIENCE↗
A General Autofluorescence Method to Characterize Polymerization Progress
An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium-catalyzed ring-opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here-developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst–inhibitor-stabilized formulations. Multiple-well analysis demonstrated suitability for future high-throughput evaluation of formulations for thermosets. Furthermore, the central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Advanced Characterization of Solid-State Battery Materials Using Neutron Scattering Techniques
Advanced batteries require advanced characterization techniques, and neutron scattering is one of the most powerful experimental methods available for studying next-generation battery materials. Neutron scattering offers a non-destructive method to probe the complex structural and chemical processes occurring in batteries during operation in truly in situ/in operando measurements with a high sensitivity to battery-relevant elements such as lithium. Neutrons have energies comparable to the energies of excitations in materials and wavelengths comparable to atomic distances in the solid state, thus giving access to study structural and dynamical properties of materials on an atomic scale. In this review, a broad overview of selected neutron scattering techniques is presented to illustrate how neutron scattering can be used to gain invaluable information of solid-state battery materials, with a focus on in situ/in operando methods. These techniques span multiple decades of length and time scales to uncover the complex processes taking place fundamentally on the atomic scale and to determine how these processes impact the macroscale properties and performance of functional battery systems. This review serves the solid-state battery research community by examining how the unique capabilities of neutron scattering can be applied to answer critical and unresolved questions of materials research in this field. A thorough and broad perspective is provided with numerous practical examples showing these techniques in action for battery research.
25 ENERGY STORAGE↗
Improving the oxygen redox reversibility of Li-rich battery cathode materials via Coulombic repulsive interactions strategy
The oxygen redox reaction in lithium-rich layered oxide battery cathode materials generates extra capacity at high cell voltages (i.e., >4.5 V). However, the irreversible oxygen release causes transition metal (TM) dissolution, migration and cell voltage decay. To circumvent these issues, we introduce a strategy for tuning the Coulombic interactions in a model Li-rich positive electrode active material, i.e., Li 1.2 Mn 0.6 Ni 0.2 O 2 . In particular, we tune the Coulombic repulsive interactions to obtain an adaptable crystal structure that enables the reversible distortion of TMO 6 octahedron and mitigates TM dissolution and migration. Moreover, this strategy hinders the irreversible release of oxygen and other parasitic reactions (e.g., electrolyte decomposition) commonly occurring at high voltages. When tested in non-aqueous coin cell configuration, the modified Li-rich cathode material, combined with a Li metal anode, enables a stable cell discharge capacity of about 240 mAh g -1 for 120 cycles at 50 mA g -1 and a slower voltage decay compared to the unmodified Li 1.2 Mn 0.6 Ni 0.2 O 2 .
25 ENERGY STORAGE↗
A General Autofluorescence Method to Characterize Polymerization Progress
Abstract An autofluorescence technique to characterize polymerization progress in real time/in line was developed, which functioned in the absence of typical fluorogenic groups on the monomer or polymer. The monomer dicyclopentadiene and polymer polydicyclopentadiene are hydrocarbons that lack traditional functional groups for fluorescence spectroscopy. Here, the autofluorescence of formulations containing this monomer and polymer during ruthenium‐catalyzed ring‐opening metathesis polymerization (ROMP) was harnessed for reaction monitoring. The methods fluorescence recovery after photobleaching (FRAP) and here‐developed fluorescence lifetime recovery after photobleaching (FLRAP) characterized polymerization progress in these native systems—without requiring exogenous fluorophore. (Auto)fluorescence lifetime recovery changes during polymerization correlated linearly to degree of cure, providing a quantitative link with reaction progress. These changing signals also provided relative rates of background polymerization, enabling comparison of 10 different catalyst‐inhibitor‐stabilized formulations. Multiple‐well analysis demonstrated suitability for future high‐throughput evaluation of formulations for thermosets. The central concept of the combined autofluorescence and FLRAP/FRAP method may be extendable to monitoring other polymerization reactions previously overlooked for lack of an obvious fluorescence handle.
López, Pía A.↗
A new method for obtaining model-free viscoelastic material properties from atomic force microscopy experiments using discrete integral transform techniques
Viscoelastic characterization of materials at the micro- and the nanoscale is commonly performed with the aid of force–distance relationships acquired using atomic force microscopy (AFM). The general strategy for existing methods is to fit the observed material behavior to specific viscoelastic models, such as generalized viscoelastic models or power-law rheology models, among others. Here we propose a new method to invert and obtain the viscoelastic properties of a material through the use of the Z-transform, without using a model. We present the rheological viscoelastic relations in their classical derivation and their z-domain correspondence. We illustrate the proposed technique on a model experiment involving a traditional ramp-shaped force–distance AFM curve, demonstrating good agreement between the viscoelastic characteristics extracted from the simulated experiment and the theoretical expectations. We also provide a path for calculating standard viscoelastic responses from the extracted material characteristics. The new technique based on the Z-transform is complementary to previous model-based viscoelastic analyses and can be advantageous with respect to Fourier techniques due to its generality. Additionally, it can handle the unbounded inputs traditionally used to acquire force–distance relationships in AFM, such as ramp functions, in which the cantilever position is displaced linearly with time for a finite period of time.
36 MATERIALS SCIENCE↗
Machine Learning-Based Technique for Automated Sensor Characterization
The development of novel instrumentation requires an iterative cycle with three stages: design, prototyping, and testing. Recent advancements in simulation and nanofabrication techniques have significantly accelerated the design and prototyping phases. Nonetheless, detector characterization continues to be a major bottleneck in device development. During the testing phase, a significant time investment is required to characterize the device in different operating conditions and find optimal operating parameters. The total effort spent on characterization and parameter optimization can occupy a year or more of an expert s time. In this work, we present a novel technique for automated sensor calibration that aims to accelerate the testing stage of the development cycle. This technique leverages closed-loop Bayesian optimization (BO), using real-time measurements to guide parameter selection and identify optimal operating states. We demonstrate the method with a novel low-noise CCD, showing that the machine learning-driven tool can efficiently characterize and optimize operation of the sensor in a couple of days without supervision of a device expert.
Zepeda, Cuevas [Chicago U., KICP]↗
Report on initial development of a database of nuclear graphite characteristics based on microstructural characterization
This report outlines the current and future efforts to produce a comprehensive library of microstructures of nuclear graphite and carbon-based materials that are candidate materials for nuclear applications in the United States. This library must contain extensive characterizations of unirradiated graphite materials, a guide to some of the techniques used to characterize graphite, a compendium of characterization data of neutron-irradiated or oxidized material, and a compendium of microstructural information of carbon-based materials. These characterization efforts are being conducted at various length scales to understand these complex materials’ local structure and property relationships. Achieving this goal requires further developing or adapting advanced characterization techniques that capture graphite’s most relevant characteristics. Some of the general objectives of this project are to aid with the material selection, licensing, management, and core assessments of a graphite core by documenting the unirradiated microstructure of relevant grades or by characterizing the evolution of the microstructure under the reactor environment. Moreover, this project aims to provide additional information, guidelines for characterizing graphite, and a protocol to assess a nuclear graphite grade. This report also summarizes some of the initial results and some of the techniques commonly used to characterize nuclear graphite.
36 MATERIALS SCIENCE↗
Degrade-Repair Cycle of a Fuel-Forming Photoelectrode
Artificial leaves that produce fuels using sunlight hold promise for sustainably powering the planet, but they require advance- ments in energetic efficiency, cost effectiveness, and operational durability. Herein, we showcase the application of combined surface- sensitive spectroscopic techniques to durability studies that characterize structural changes accompanying functional degradation and go beyond just observing changes in function over time. Further, the photoelectrodes used in this work feature a polymeric surface coating functionalized with molecular complexes that catalyze the hydrogen evolution reaction. Using a polymeric layer to interface the light-harvesting component with catalytic sites enables reassembly of catalysts that detach during operation, establishing a degrade-repair cycle.
14 SOLAR ENERGY↗
Challenges and Opportunities of Fe-based Core-Shell Catalysts for Fischer-Tropsch Synthesis
Here, Fe-based catalysts are an active, selective, and low-cost option for tuning Fischer-Tropsch synthesis (FTS) selectivity toward desirable light olefins. By encapsulating Fe within ZSM-5, the resultant core-shell catalysts have the potential to control the product distribution via secondary reactions that occur over the acid sites of the zeolite shell. In this paper, Fe is encapsulated within ZSM-5 via the seed-directed growth technique and characterized with a suite of analytical techniques including Mössbauer spectroscopy and X-ray absorption fine structure (XAFS). Characterization of the core-shell catalysts indicates that some of the Fe-based active phase is destabilized during seed-directed growth, demonstrating the challenges associated with encapsulating an Fe-based active phase within zeolites. However, comparing FTS performance of the core-shell catalyst with the Fe-based control synthesized via incipient wetness impregnation demonstrates improved selectivity toward the desired C 2 -C 4 olefins and C 5+ hydrocarbons.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Microscopy-based Multi-technique, Multi-scale Characterization of Polymer Electrolyte Membrane Devices
This paper will cover recent developments of both fuel cell and electrolyzer catalysts and catalyst layers, and the vital role of each technique in obtaining a comprehensive picture of how to improve constituent interactions within the device.
30 DIRECT ENERGY CONVERSION↗
Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning
Abstract Particle accelerators are invaluable discovery engines in the chemical, biological and physical sciences. Characterization of the accelerated beam response to accelerator input parameters is often the first step when conducting accelerator-based experiments. Currently used techniques for characterization, such as grid-like parameter sampling scans, become impractical when extended to higher dimensional input spaces, when complicated measurement constraints are present, or prior information known about the beam response is scarce. Here in this work, we describe an adaptation of the popular Bayesian optimization algorithm, which enables a turn-key exploration of input parameter spaces. Our algorithm replaces the need for parameter scans while minimizing prior information needed about the measurement’s behavior and associated measurement constraints. We experimentally demonstrate that our algorithm autonomously conducts an adaptive, multi-parameter exploration of input parameter space, potentially orders of magnitude faster than conventional grid-like parameter scans, while making highly constrained, single-shot beam phase-space measurements and accounts for costs associated with changing input parameters. In addition to applications in accelerator-based scientific experiments, this algorithm addresses challenges shared by many scientific disciplines, and is thus applicable to autonomously conducting experiments over a broad range of research topics.
43 PARTICLE ACCELERATORS↗
Proton Conducting Neuromorphic Materials and Devices
Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.
36 MATERIALS SCIENCE↗
A Technique for the Quantitative Characterization of Weld Microstructure and Application to Mo Welds
The choice of weld parameters determines the size, shape, and curvature of grains in the fusion zone (FZ) and heat-affected zone (HAZ) of welds while the mechanical properties of the welds are correlated to this microstructure. Here, a new technique to quantitatively evaluate these microstructural characteristics in both zones of welds has been applied to molybdenum gas tungsten arc welds fabricated using different weld parameters. Trends in microstructural characteristics in the FZ and HAZ were evaluated and correlated with changes to heat input, weld speed, and weld technique. The use of this approach showed that a 20 pct decrease in heat input caused a 20 pct decrease in the number of FZ grains with aspect ratios ≥ 4. The orientations of the FZ grain segments as a function of distance from the FZ centerline were significantly affected by the weld speed and its effect on weld pool shape. A 50 pct increase in weld speed caused a 20 pct decrease in grain segments orientated 60 to 90 deg from the normal to the direction of welding. This technique also captured differences in grain sizes and grain size anisotropy in the FZ between welds made with a constant current, pulsed current, and use of a 4-pole-magnetic oscillator.
36 MATERIALS SCIENCE↗
Towards Universal Non-Dimensional Characterization of the Oscillatory Dynamics of Wind Turbine Rotors of Multiple Sizes
One concern in the field of Horizontal Axis Wind Turbines (HAWTs) is what control strategies are needed to handle gust pulses in the wind to prevent extreme oscillations of the blades to reduce fatigue stress, prevent blade rupture, and extend the turbine’s operational life. In order to design innovative control strategies to modify the blade’s oscillatory response, it is crucial to establish the fundamental vibrational behavior of the blades when excited by gust pulses of different frequencies and amplitudes present in the fluctuating wind inflow. In a series of previous works, the authors presented a novel Reduced-Order Characterization (ROC) technique that provided an energy-based characterization of the fundamental modes of oscillation of wind turbine rotors when excited by combinations of wind gust pulses of different frequencies and amplitudes. The main focus of the present work is to extend these original notions of energy-based ROC to a universal technique expressed in terms of non-dimensional quantities that could be applied to turbines of any size, operating in any set of wind conditions, as long as they share geometrical and material similarity. The ROC technique provides a simple formula that is capable of predicting the dominant vibrational modes of a blade with sufficient precision to be useful in the determination of a control decision that can be computed in real time, an aspect of fundamental importance in dealing with rapid fluctuations in wind conditions.
Yates, North (ORCID:000900052204261X)↗