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At least 289 records · Page 16

AGC 4 Graphite Specimen Postirradiation Characterization Plan

This characterization plan describes the thermal, physical, and mechanical measurement techniques that will be used to characterize graphite samples being tested in the fourth Advanced Graphite Creep experiment (AGC-4). Instruments, fixtures, and methods are currently in place for both pre and postirradiation material property measurements of bulk density, thermal diffusivity, coefficient of thermal expansion, elastic modulus, and electrical resistivity. Postirradiation testing procedures used to characterize the samples are described and discussed in the plan. Where they exist, American Society for Testing and Materials (ASTM) International testing standards will apply to the tests. Any departure from ASTM International testing standards or the approved laboratory procedures are documented within this characterization plan. Deviations that occur during testing will be documented in data reports.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advanced Characterization Techniques for Overcoming Challenges of Perovskite Solar Cell Materials

Abstract In the last 10 years, organic–inorganic hybrid perovskite solar cells have achieved unprecedented advances, to the point where they now exhibit extremely high efficiency. However, long‐term stability and areal scalability limitations impede the commercial application of perovskite materials, and appropriate diagnosistic tools have become necessary to evaluate perovskite materials. Characterization of perovskite materials is regularly misinterpretated, due to unique intrinsic and extrinsic factors: degradation from the measurement source, ion migration, phase transition, and separation. Herein, studies on perovskites are reviewed that have used advanced characterization tools to overcome characterization challenges. Cryogenic temperature assisted measurements mitigate degradation or phase transitions induced by the measurement source. In situ measurements can track the variation of perovskite materials depending on external stimuli. Spatial material properties are able to be evaluated by the use of multidimensional mapping techniques. An overview of these advanced characterization tools that can overcome the challenges associated with established tools provides the opportunity for further understanding perovskite materials and solving the remaining challenges on the road to commercialization.

Kim, Min‐cheol↗

A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li-Ion and Li-Metal Batteries

Whether attempting to eliminate parasitic Li metal plating on graphite (and other Li-ion anodes) or enabling stable, uniform Li metal formation in ‘anode-free’ Li battery configurations, the detection and characterization (morphology, microstructure, chemistry) of Li that cannot be reversibly cycled is essential to understand the behavior and degradation of rechargeable batteries. In this review, various approaches used to detect and characterize the formation of Li in batteries are discussed. Each technique has its unique set of advantages and limitations, and works towards solving only part of the full puzzle of battery degradation. Going forward, multimodal characterization holds the most promise towards addressing two pressing concerns in the implementation of the next generation of batteries in the transportation sector (viz. reducing recharging times and increasing the available capacity per recharge without sacrificing cycle life). Such characterizations involve combining several techniques (experimental- and/or modeling-based) in order to exploit their respective advantages and allow a more comprehensive view of cell degradation and the role of Li metal formation in it. Additionally, it is also discussed which individual techniques, or combinations thereof, can be implemented in real-world battery management systems on-board electric vehicles for early detection of potential battery degradation that would lead to failure.

25 ENERGY STORAGE↗

Characterizing Disorders Within Cathode Materials of Lithium‐Ion Batteries

The demand for developing high-energy density cathode materials has been increasing. The energy densities of cathode materials have been improved by adapting structural deviation from the ideal fully ordered α-NaFeO2 type, but that led to limitations in terms of structural stability and safety. Although disorders in cathode materials are closely related to their electrochemical properties, unfortunately, characterizing the disorder itself in cathode materials has been challenging due to its complex parasitic reaction and strong correlation with other disorders occurring during charge/discharge. In this review, we categorize various disorders by their scales of ordering from short-range to long-range. We addressed the principles of various characterization tools to figure out how they can help to identify the structural disorder in cathode materials. Specifically, we focused on the underlying principles of each characterization technique to correlate different disorder-driven phenomena through several case studies. It underscores the substantial importance of disorder-property relationships and the corresponding characterization methods, which can provide novel research strategies for developing high-energy density cathode materials with decent structural stability.

Lee, Hakwoo↗

Ultrasound Characterization of Plastic Bonded Explosives With Varied Binder Content and Density

Advanced explosive formulations and methods of production require rapid characterization for both processes and materials. Here, we present results for ultrasound characterization of a plastic bonded explosive (PBX) formulation as a function of binder weight percent and pressing density using through-transmission sound speed measurements. The explosive in this study was composed of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) combined with the fluoropolymer binder Kynar Ultraflex B. Binder content ranged from 2.6 wt.% to 11.5 wt.% with associated explosive formulation densities from 1.69 g/cc to 1.89 g/cc. We find linear and nonlinear changes in longitudinal and shear sound speeds, peak frequencies, and measured elastic properties for the different PBX formulations. These measured changes can differentiate the tested formulations, highlighting the potential for ultrasound as a nondestructive characterization method for newly-formulated PBXs. We also demonstrate through-transmission measurements using different coupling media and present results from an ultrasound technique called resonant ultrasound spectroscopy (RUS). Both transmission and RUS approaches may allow for rapid and even automated characterization of PBX components suitable for high-throughput manufacturing operations.

Engineering↗

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of mechanical discontinuities based on data-driven classification of compressional-wave travel times

Wave propagation and diffusive transport phenomena are influenced by the mechanical discontinuities in material. Here this study shows that certain bulk properties of the network of low-velocity mechanical discontinuities (e.g. air-filled cracks) in a material can be characterized by processing compressional-wave travel times using traditional data-driven classification techniques. To that end, we perform three tasks in chronological order: (1) use the discrete fracture network (DFN) method to create two-dimensional (2D) numerical models of crack-bearing material embedded with various types of low-velocity mechanical discontinuities, (2) use the fast marching method (FMM) to simulate the propagation of the wave/diffusion front from a single source through the 2D crack-bearing material to multiple receivers placed on the boundary of the material, and (3) train 9 data-driven classifiers to characterize the crack-bearing materials (i.e. bulk properties of the network of mechanical discontinuities in the crack-bearing material) by learning from the simulations of travel times detected by multiple receivers placed around the crack-bearing material. The classifiers identified the orientation, spatial distribution, and dispersion of the low-velocity mechanical discontinuities. Voting classifier performs the best among the 9 classifiers. For the characterization of bulk dispersion and distribution of discontinuities, the sensors located on the adjacent boundaries are more important; whereas for the characterization of bulk orientation of discontinuities, the sensors located on the opposite side are more important.

42 ENGINEERING↗

The characterization of wear-causing particles and silica sand in particular

Erodants and abradants are two types of wear-causing particles (WCP). Despite their effects on the severity and rate of wear, WCP are inadequately characterized in a surprising number of publications, especially those involving impingement erosion and three-body abrasion. That shortfall makes it difficult to correlate features of WCP with the details of worn surfaces, or to develop wear models that account for those features. It is argued that the documentation of WCP should go beyond simply reporting their composition and mean particle size. In late 1985, ASTM Committee G2 on Wear and Erosion established a task group on the characterization of WCP. At that time, image analysis was slower and less sophisticated than it is today. While that ASTM task group failed to produce a consensus standard, computerized particle characterization methods were developing in fields other than tribology, fields like geoscience, heavy sand mining, materials processing, and pharmaceuticals. A notable exception to this is ferrography, which is a widely-used diagnostic for lubricated tribosystems. In the context of dry wear, it is useful to identify which features of WCP would be beneficial to document, and to identify some techniques and scales of detail appropriate to particular tribosystems. In this paper, examples are presented for the morphological and mechanical characterization of silica sand grains, as prompted by a triboanalysis of the abrasive and erosive wear of biomass pre-processing equipment. The authors propose a minimum level of documentation for WCP, one that can enrich tribosystem analysis both in laboratory tests and field studies.

36 MATERIALS SCIENCE↗

Discovery, characterization, and application of chromosomal integration sites for stable heterologous gene expression in Rhodotorula toruloides

Rhodotorula toruloides is a non-model, oleaginous yeast uniquely suited to produce acetyl-CoA-derived chemicals. However, the lack of well-characterized genomic integration sites has impeded the metabolic engineering of this organism. Here we report a set of computationally predicted and experimentally validated chromosomal integration sites in R. toruloides. We first implemented an in silico platform by integrating essential gene information and transcriptomic data to identify candidate sites that meet stringent criteria. We then conducted a full experimental characterization of these sites, assessing integration efficiency, gene expression levels, impact on cell growth, and long-term expression stability. Among the identified sites, 12 exhibited integration efficiencies of 50% or higher, making them sufficient for most metabolic engineering applications. Using selected high-efficiency sites, we achieved simultaneous double and triple integrations and efficiently integrated long functional pathways (up to 14.7 kb). Additionally, we developed a new inducible marker recycling system that allows multiple rounds of integration at our characterized sites. Here, we validated this system by performing five sequential rounds of GFP integration and three sequential rounds of MaFAR integration for fatty alcohol production, demonstrating, for the first time, precise gene copy number tuning in R. toruloides. These characterized integration sites should significantly advance metabolic engineering efforts and future genetic tool development in R. toruloides.

59 BASIC BIOLOGICAL SCIENCES↗

Characterizing Electrode Materials and Interfaces in Solid-State Batteries

Solid-state batteries (SSBs) could offer improved energy density and safety, but the evolution and degradation of electrode materials and interfaces within SSBs are distinct from conventional batteries with liquid electrolytes and represent a barrier to performance improvement. Over the past decade, a variety of imaging, scattering, and spectroscopic characterization methods has been developed or used for characterizing the unique aspects of materials in SSBs. These characterization efforts have yielded new understanding of the behavior of lithium metal anodes, alloy anodes, composite cathodes, and the interfaces of these various electrode materials with solid-state electrolytes (SSEs). This review provides a comprehensive overview of the characterization methods and strategies applied to SSBs, and it presents the mechanistic understanding of SSB materials and interfaces that has been derived from these methods. This knowledge has been critical for advancing SSB technology and will continue to guide the engineering of materials and interfaces toward practical performance.

25 ENERGY STORAGE↗

The Challenge of Characterizing High-Concentration Electrolytes at the Molecular Level: A Perspective

High-concentration electrolytes (HCEs) are promising materials composed of highly concentrated salt solutions in organic solvents. HCEs have many desirable properties and are particularly important in the field of batteries. However, the number of ways in which these materials can be tuned is very large, which is crucial for tailored electrolyte design. Moreover, the molecular characterization of HCEs is challenging both experimentally and computationally, but it is necessary for their rational design. Therefore, currently the structure–property–performance relationship of these electrolytes has not been directly derived from their characterization. Here, in this Perspective, we present a brief overview of the HCEs and discuss the state-of-the-art characterization methods used to study them at the molecular level. We also address the challenges associated with these methods, including both experimental techniques and computational tools currently available. Emphasis is placed on methods aimed at understanding the physical phenomena that govern the molecular structure and dynamics occurring on the subnanosecond and nanometer time and length scales. Finally, we discuss new strategies for obtaining a comprehensive characterization of HCEs at the molecular level.

electrolytes↗

Online LIBS–ML Framework for Dynamic Characterization of Heterogeneous Waste-Derived Gasification Feedstocks

LIBS−ML framework for real time feedstock characterization during continuous conveyor transport Heterogeneous waste derived feedstocks (e.g., waste coal, biomass and blends) introduce rapid variability in heating value and ash chemistry that affect gasifier operation, yet conventional laboratory characterization techniques are too slow to support proactive control. To address this gap, this study reports on an online, in situ, dynamic characterization framework that couple’s laser-induced breakdown spectroscopy (LIBS) with leakage safe machine learning (ML) regression to deliver real time, decision quality predictions of gasifier relevant properties. A controlled sample matrix spanning two different waste coals, two different biomasses, and engineered blends under two particle size conditions were constructed and benchmarked using standardized laboratory analyses for proximate/ultimate properties and ash composition. LIBS spectra were acquired dynamically as material flowed on a conveyor belt, using high energy 1064 nm laser ablation and shot averaging to improve repeatability and precision. Supervised regression models (multi layer perceptron (MLP) /artificial neural network (ANN), random forest (RF), and support vector regression (SVR)) and an optimized weighted ensemble were trained on emission line feature sets using nested cross validation with Bayesian hyperparameter tuning and validated against an independent hold out set. The proposed LIBS−ML workflow achieves near laboratory predictive fidelity across parametric targets (including higher heating value (HHV), ash content, fixed carbon, sulfur, major ash forming oxides, and initial deformation temperature (IDT)), with the weighted ensemble providing a robust default predictor under dynamic measurement conditions. These results demonstrate a practical pathway for real time feedstock characterization that can enable feedforward adjustments and more resilient gasifier operation for variable quality waste derived fuels.

Biomass↗

ACS Sustainable Chemistry & Engineering Virtual Special Issue on Recent Advances in Biomass Characterization and Modeling

Recognizing the importance of biomass characterization and modeling, a virtual special issue (VSI) entitled Recent Advances in Biomass Characterization and Modeling was organized to showcase the recent contributions to this emerging field. This VSI features contributions from leading scientists in the biorefinery field, intending to provide the readers with the latest advances in analytical methodology and modeling to characterize biomass feedstocks and biomass-derived products. Further, the VSI contains perspectives and research articles. Advanced analytical methods that measure the mechanical, chemical, physical, biological, and other properties of biomass and biomass pyrolysis products are described along with their application’s limitations in two perspectives. Biomass is a multicomponent/multiscale, complex, nonconducting, and highly heterogeneous material; thus, it could be problematic for many characterization techniques. Traditional biomass analysis tools that are slow, laborious, and generally require harsh reagents have been replaced or supplemented by simpler and more rapid chromatographic and spectroscopic approaches such as GC-MS, HPLC, FTIR, Raman, and NMR spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design and Characterization of a Transcriptional Repression Toolkit for Plants

Regulation of gene expression is essential for all life. Tools to manipulate the gene expression level have therefore proven to be very valuable in efforts to engineer biological systems. However, there are few well-characterized genetic parts that reduce gene expression in plants, commonly known as transcriptional repressors. We characterized the repression activity of a library consisting of repression motifs from approximately 25% of the members of the largest known family of repressors. Combining sequence information with our trans-regulatory function data, we next generated a library of synthetic transcriptional repression motifs with function predicted in advance. After characterizing our synthetic library, we demonstrated not only that many of our synthetic constructs were functional as repressors but also that our advance predictions of repression strength were better than random guesses. Finally, we assessed the functionality of known transcriptional repression motifs from a wide range of eukaryotes. Our study represents the largest plant repressor motif library experimentally characterized to date, providing unique opportunities for tuning transcription in plants.

59 BASIC BIOLOGICAL SCIENCES↗

Using scalable computer vision to automate high-throughput semiconductor characterization

Abstract High-throughput materials synthesis methods, crucial for discovering novel functional materials, face a bottleneck in property characterization. These high-throughput synthesis tools produce 10 4 samples per hour using ink-based deposition while most characterization methods are either slow (conventional rates of 10 1 samples per hour) or rigid (e.g., designed for standard thin films), resulting in a bottleneck. To address this, we propose automated characterization (autocharacterization) tools that leverage adaptive computer vision for an 85x faster throughput compared to non-automated workflows. Our tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms that: (1) autonomously compute the band gaps of 200 compositions in 6 minutes, and (2) autonomously compute the environmental stability of 200 compositions in 20 minutes, achieving 98.5% and 96.9% accuracy, respectively, when benchmarked against domain expert manual evaluation. These tools, demonstrated on the formamidinium (FA) and methylammonium (MA) mixed-cation perovskite system FA 1−x MA x PbI 3 , 0 ≤ x ≤ 1, significantly accelerate the characterization process, synchronizing it closer to the rate of high-throughput synthesis.

Science & Technology - Other Topics↗

Characterization of just one atom using synchrotron X-rays

Since the discovery of X-rays by Roentgen in 1895, its use has been ubiquitous, from medical and environmental applications to materials sciences. X-ray characterization requires a large number of atoms and reducing the material quantity is a long-standing goal. Here we show that X-rays can be used to characterize the elemental and chemical state of just one atom. Using a specialized tip as a detector, X-ray-excited currents generated from an iron and a terbium atom coordinated to organic ligands are detected. The fingerprints of a single atom, the L 2,3 and M 4,5 absorption edge signals for iron and terbium, respectively, are clearly observed in the X-ray absorption spectra. The chemical states of these atoms are characterized by means of near-edge X-ray absorption signals, in which X-ray-excited resonance tunnelling (X-ERT) is dominant for the iron atom. The X-ray signal can be sensed only when the tip is located directly above the atom in extreme proximity, which confirms atomically localized detection in the tunnelling regime. Finally, our work connects synchrotron X-rays with a quantum tunnelling process and opens future X-rays experiments for simultaneous characterizations of elemental and chemical properties of materials at the ultimate single-atom limit.

74 ATOMIC AND MOLECULAR PHYSICS↗

Extreme ultraviolet microscope characterization using photomask surface roughness

We demonstrate a method for characterizing the field-dependent aberrations of a full-field synchrotron-based extreme ultraviolet microscope. The statistical uniformity of the inherent, atomic-scale roughness of readily-available photomask blanks enables a self-calibrating computational procedure using images acquired under standard operation. We characterize the aberrations across a 30-um field-of-view, demonstrating a minimum aberration magnitude of smaller than λ/21 rms averaged over the center 5-um area, with a measurement accuracy better than λ/180 rms. The measured field variation of aberrations is consistent with system geometry and agrees with prior characterizations of the same system. In certain cases, it may be possible to additionally recover the illumination wavefront from the same images. Our method is general and is easily applied to coherent imaging systems with steerable illumination without requiring invasive hardware or custom test objects; hence, it provides substantial benefits when characterizing microscopes and high-resolution imaging systems in situ.

47 OTHER INSTRUMENTATION↗

Characterization of a mock up nuclear waste package using energy resolved MeV neutron analysis

Reliable radiographic methods for characterizing nuclear waste packages non-destructively (without the need to open containers) have the potential to significantly contribute to safe handling and future disposal options, particularly for legacy waste of unknown content. Due to required shielding of waste containers and the need to characterize materials consisting of light elements, X-ray methods are not suitable. Here, energy-resolved MeV neutron radiography is demonstrated as a first-of-its-kind application for non-destructive and remote examination of mock up nuclear waste packages from a safe position using time-of-flight techniques enabled by a novel event-mode imaging detector system. Energy-resolved neutron transmission spectra were measured spatially, permitting the detection of analogue materials to actual nuclear waste such as water, melamine, and ion exchange resin within a 2.54 cm wall thickness steel pipe. The results demonstrate the capability to locate the materials through this wall thickness by radiography and tomographic reconstruction, revealing detailed 3D distributions and structural anomalies. The method effectively detects residual water in ion exchange resin, highlighting its sensitivity to moisture content, a crucial parameter for nuclear waste characterization. Monte Carlo simulations are in agreement with the experimental findings, providing a pathway to simulate waste forms more difficult to tackle experimentally. This work paves the way to apply sub-nanosecond intense MeV neutron sources, such as laser-driven neutron sources under development, to nuclear waste characterization.

36 MATERIALS SCIENCE↗