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At least 631 records · Page 35

Evaluating the state-of-the-art in remote volcanic eruption characterization Part II: Ulawun volcano, Papua New Guinea

Retrospective eruption characterization is valuable for advancing our understanding of volcanic systems and evaluating our observational capabilities, especially with remote technologies (defined here as a space-borne system or non-local, ground-based instrumentation which include regional and remote infrasound sensors). In June 2019, the open-system Ulawun volcano, Papua New Guinea, produced a VEI 4 eruption. We combined data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System infrasound network, and GLD360 globally detected lightning with information from the local authorities and social media to characterize the pre-, syn- and post-eruptive behaviour. The Rabaul Volcano Observatory recorded ~24 h of seismicity and detected SO 2 emissions ~16 h before the visually-documented start of the Plinian phase on 26 June at 04:20 UTC. Infrasound and SO2 detections suggest the eruption started during the night on 24 June 2019 at 10:39 UTC ~38 h before ash detections with a gas-dominated jetting phase. Local reports and infrasound detections show that the second phase of the eruption started on 25 June 19:28 UTC with ~6 h of jetting. The first detected lightning occurred on 26 June 00:14 UTC, and ash emissions were first detected by Himawari-8 at 01:00 UTC. Post-eruptive satellite imagery indicates new flow deposits to the south and north of the edifice and ash fall to the west and southwest. In particular, regional infrasound data provided novel insight into eruption onset and syn-eruptive changes in intensity. We conclude that, while remote observations are sufficient for detection and tracking of syn-eruptive changes, key challenges in data latency, acquisition, and synthesis must be addressed to improve future near-real-time characterization of eruptions at minimally-monitored or unmonitored volcanoes.

58 GEOSCIENCES↗

TPSAS-NF1676L-23428-DND

Recent theoretical advances now enable accurate characterization of both the single scattering and multiple scattering contributions to the lidar backscatter signals obtained from opaque water clouds (Hu et al., 2006). As a consequence, lidar measurements of opaque water clouds have increasingly broad applications, especially for space-based polarization-sensitive lidars such as CALIOP. Among the most prominent and useful of these are (1) calibration and assessments of calibration accuracy (e.g., O'Connor et al., 2004; Hu et al., 2006); (2) accurate estimates of extrinsic (e.g., optical depths) and intrinsic (e.g., extinction-to-backscatter ratios) optical properties of clouds and aerosol layers lying above opaque water clouds (Hu et al., 2007; Liu et al., 2015); and (3) retrievals of water cloud microphysical properties such as cloud droplet number concentrations (Hu et al., 2007; Li et al., 2011; Zeng et al., 2014). In the first part of this presentation we give an overview of the recent advances in this subject area. The second part introduces several new studies of water clouds using the multi-wavelength depolarization measurement capabilities of NASA's airborne high spectral resolution lidars (HSRL). We use these measurements to assess existing theory, validate the measurement concept and explore several new application concepts. The third part discusses changes in Arctic water clouds using CALIOP measurements. The HSRL water cloud study is supported by NASA's atmospheric composition program.

Y Hu↗

Implications of Advanced Crew Escape Suit Transpiration for the Orion Program

Human testing was conducted to more fully characterize the integrated performance of the Advanced Crew Escape Suit (ACES) with liquid cooling provide by an Individual Cooling Unit (ICU) across a broad range of environmental conditions and metabolic rates. Together with a correlation for the ACES Liquid Cooling Garment as a function of inlet temperature, metabolic rate, and crew size, a reasonably conservative correlation for core temperature was achieved for the human thermal model applied to the ACES with ICU cooling. A key observation for this correlation was accounting for transpiration of evaporated sweat through the Gortex(Registered TradeMark) liner of the ACES indicated by as much as 0.6 lbm of sweat evaporated over the course of the 1 hour test profile, most of which could not be attributed to respiration or head sweat evaporation of the crew. Historically it has been assumed that transpiration was not an important design feature of the ACES suit. The correlated human thermal model will show transpiration to be highly useful in hot survival situations for the Orion Program when adequate liquid cooling is not available.

Bue, Grant↗

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗

Study of Advanced Occupant Models to Quantify Injury Risk for eVTOL Vehicles

Urban transportation is currently evolving from traditional ground-based vehicles (cars, taxis, and buses) to include air-based electric vertical take-off and landing (eVTOL) vehicles which can be utilized for on-demand transportation, cargo transport, and emergency services. These new eVTOL vehicles are designed to be small, lightweight, and able to operate autonomously without user intervention. Safety is a big part of eventual eVTOL adoption, however gaps in the consideration of safety features exist. Anthropomorphic test devices (ATDs) are used in aerospace crashworthiness standards to quantify occupant injury risk and develop improved safety designs for emergency landing situations, but the ATDs currently used in aircraft certification requirements were developed many decades ago. Developments have occurred over the years involving ATD technology, which includes a host of newer and more biofidelic ATDs such as the Test Device for Human Occupant Restraint (THOR). Increased computing power has also allowed for detailed computational human body models (HBMs) to be created, such as the Global Human Body Model Consortium (GHBMC). This study aims to assess the capability of both HBMs and new ATD designs to identify injury mechanisms within eVTOL relevant emergency landing conditions. Finite element (FE) analysis was used to expand upon full-scale and seat level impact testing conducted by researchers at the National Aeronautics and Space Administration (NASA) to look at effects of occupant model configurations on prediction of injury. The GHBMC HBM and THOR ATD models were simulated in the seat level test conditions to characterize differences between these advanced assessment tools and traditional ATDs in the isolated seat loading environment. Results identified key differences in the responses from each of the models utilized and compared their impact response in head, neck, and spinal injury metrics. The THOR model identified potential risks for head injuries due to head impacts on the seat, however it predicted lower spinal loads than the other occupant surrogates. The GHBMC showed distinctly different biomechanical responses compared to the ATD. The GHBMC model is much more deformable than the ATDs and it exhibited higher distribution of forces and increased sensitivity to the duration of acceleration pulses. Both models incorporated into this study identified key mechanisms for injury that should be considered for passenger safety in the development of these novel aircraft. In addition, this study demonstrated the value of FE modeling for running a variety of complex human surrogates to identify potential injury mechanisms for consideration in regulation and development of new aircraft. Continued research in this field to improve validation these models will only lead to safer aircraft and more comprehensive safety measures.

Crashworthiness↗

Advancements of On-Line Monitoring and Real-Time Characterization of Actual Low-Level Hanford Tank-Waste Samples

Waste and process stream characterization is essential to the safe, efficient, and cost-effective processing of Hanford Site materials. The demand for materials characterization including chemical, radionuclide, and physical attributes during waste management, transfer, and staging operations in the Hanford tank farms is expected to significantly increase as the U.S. Department of Energy River Protection Project progresses toward Hanford waste treatment and immobilization. Our past work has applied Raman on-line monitoring and chemometric modeling to the supernate of Hanford tank 241-AP-105 and has demonstrated the quantitative measurement of nine analytes within this waste. To demonstrate broader applicability, this method has now been expanded to waste from two additional Hanford tanks, AW-102 and AP-107, and the offgas condensate from lab-scale melter runs of actual-tank waste feeds. To enhance the performance of the Raman method, instruments with various excitation wavelengths were compared, since it is known that the Raman response is enhanced by shorter wavelength excitation. The laser excitations for the three systems tested were 404 nm, 532 nm, and 671 nm. In addition to laser wavelength selection, the laser power, measurement integration times, and signal averaging techniques were also investigated to determine their effect on detection limits for oxy-anion analytes within tank wastes. These advancements in Raman capability are compared with past standards and will be presented.

Bryan, Samuel A.↗

Feasibility of source-free DAS logging for next-generation borehole imaging

Characterizing and monitoring geologic formations around a borehole are crucial for energy and environmental applications. However, conventional wireline sonic logging usually cannot be used in high-temperature environments nor is the tool feasible for long-term monitoring. We introduce and evaluate the feasibility of a source-free distributed-acoustic-sensing (DAS) logging method based on borehole DAS ambient noise. Our new logging method provides a next-generation borehole imaging tool. The tool is source free because it uses ever-present ambient noises as sources and does not need a borehole sonic source that cannot be easily re-inserted into a borehole after well completion for time-lapse monitoring. The receivers of our source-free DAS logging tool are fiber optic cables cemented behind casing, enabling logging in harsh, high-temperature environments, and eliminating the receiver repeatability issue of conventional wireline sonic logging for time-lapse monitoring. We analyze a borehole DAS ambient noise dataset to obtain root-mean-squares (RMS) amplitudes and use these amplitudes to infer subsurface elastic properties. We find that the ambient noise RMS amplitudes correlate well with anomalies in conventional logging data. The source-free DAS logging tool can advance our ability to characterize and monitor subsurface geologic formations in an efficient and cost-effective manner, particularly in high-temperature environments such as geothermal reservoirs. Further validation of the source-free DAS logging method using other borehole DAS ambient noise data would enable the new logging tool for wider applications.

58 GEOSCIENCES↗

Survey of baffle plate samples, specimen machining, and hydrogen measurements

This report outlines preliminary results on the survey and characterization of irradiated baffle plate, baffle former, and flux thimble tube specimens as part of the ongoing investigation into irradiation-induced embrittlement in austenitic stainless steels at ambient (room temperature) conditions. The specimens originated from commercial pressurized water reactor (PWR) components, covering displacement damage doses ranging from approximately 0.065 to 75 dpa. Initial scanning electron microscopy (SEM) surveys revealed that specimen surfaces exhibited fine machining marks and in-service-formed oxide layers on the side surfaces of the analyzed specimens. The oxide layers revealed specific features resembling localized "pitting-like" corrosion. An additional set of specimens representing in-service oxidation is being preserved for future microstructure analysis work. As believed, this will provide additional insights into long-term material degradation in PRWs. Specimen machining challenges emerged due to a complex failure of the electric discharge machining (EDM) system located in hot area. Despite partial restoration, issues persist with the EDM’s secondary power supply, necessitating the exploration of alternative EDM or computer numerical control (CNC) machining approaches to facilitate tensile specimen preparation. Currently, low speed saw cutting is in progress to prepare specimens for hydrogen measurements and general microstructure analysis. The near-term goals include completing tensile specimen machining for advanced mechanical testing and characterizing fracture mechanisms, and stress-corrosion cracking testing, ultimately aiming to identify and mitigate the ambient-condition intergranular cracking through targeted post-irradiation annealing strategies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

OpenCRUMS USA: An Open Machine Learning Framework for Characterizing Variability in Aerosol Reanalysis Data

Advances in artificial intelligence (AI) have called for exploring how these techniques can be used for exploring patterns in large climate datasets. To that regard, the U.S. Department of Energy AI for Earth System Predictability (AI4ESP) supported a pilot initiative called the Open Classification of Regimes in the Southeast USA (OpenCRUMS USA) project to explore how AI can be used to characterize modes of spatial variability in large climate datasets. For this study, we focus on comparing two methods for characterizing the modes of spatial variability of surface aerosol concentration over the Houston region: empirical orthogonal functions (EOFs) and layerwise relevance propagation (LRP) applied to a convolutional neural network (CNN) classifier. We show that EOF analysis typically attributes spatial variability modes that span all of southeast Texas, prohibiting the attribution of spatial variability to localized regions. However, using LRP on the CNN classifier resolves the explanatory parameters at a finer spatial resolution than EOFs. This allows for the attribution of the spatial variability of surface aerosols to local regions of organic carbon which was not possible using EOFs. In addition, the LRP analysis also suggests that synoptic-scale transport of dust is most prevalent during anticyclonic and pretrough synoptic conditions as categorized by self-organizing maps.

54 ENVIRONMENTAL SCIENCES↗

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗

Irradiation-induced chemical disordering in ceramics: The case of SiC

Chemical disordering is one feature of damage that occurs in irradiation environments and is common in ceramic compounds. This paper reviews irradiation-induced chemical disordering in SiC-based materials at elevated temperatures. Here the results were obtained using advanced analytical tools to characterize atomistic defects and to evaluate the chemistry of defect clusters and homonuclear bond structures. Finally, this paper demonstrates that chemical disordering is crucial to understanding microstructural stability and establishing a mechanistic modeling of microstructural evolution of irradiated SiC.

36 MATERIALS SCIENCE↗

Quo Vadis, Borophene?

The materials-by-design paradigm is based on synergistic efforts involving advanced computation, synthesis and characterization to ensure properties meet various technological needs within a cost-effective framework. However, starting from the elements of the periodic table to achieving useful devices is a daunting road. Borophene, a two-dimensional (2D) allotrope of boron, is envisaged to play a role in this exciting area due to its extraordinarily rich polymorphism. The multitude of potentially stable structures, several of them already realized experimentally, differentiates borophene from all other mono-elemental 'X-enes'. The possibility of harnessing this unique characteristic fuels hopes for achieving 'ondemand' crystallographic arrangements making borophene a candidate platform for various electronics, energy sciences and biology applications. Furthermore, despite the scarcity of data on intrinsic electronic properties, the experimentally confirmed polymorphisms, the recent synthesis of bilayers and the first steps towards transferring borophene on device-compatible substrates are important milestones in borophene research.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A proposed high-intensity radiometer calibration method using concentrated solar radiation

Accurate calibration of irradiance measurement devices, or radiometers, is essential for ensuring the reliability of measurements in high heat applications such as concentrating solar power (CSP), aerospace, defense, and pulsed power systems. Despite the critical need, existing calibration standards and service providers are limited to irradiance levels below 100 kW/m 2 and specific radiation sources, which is insufficient for many applications. For instance, CSP technologies, particularly those under the Department of Energy’s Solar Energy Technologies Office (SETO) Gen 3 program, require accurate measurements of broadband irradiance at levels exceeding 2000 kW/m 2 . In even more extreme scenarios, such as re-entry vehicles, heat levels can surpass 10000 kW/m 2 . Current ISO standards, specifically ISO 14934–2 and ISO 14934–3, are constrained to lower irradiance levels and dependent on black body heat sources, limiting their applicability for high-intensity broadband irradiance measurements, particularly in concentrated solar applications. Here, to address this shortfall, the National Solar Thermal Test Facility (NSTTF) at Sandia National Laboratories (SNL) proposes a calibration method and facility capable of characterizing radiometers up to 2750 kW/m 2 using concentrated solar irradiance. Calibrating with concentrated sunlight is important for solar applications as it aligns the calibration process with the solar spectrum. This alignment is crucial for minimizing systematic errors and avoiding the need for additional corrections that may arise when radiometers designed for solar applications are calibrated using black-body or electrical sources. This paper presents the present day NSTTF characterization facility and procedure, detailing the proposed calibration method and uncertainty quantification. The presented method builds upon 1980′s NSTTF methodology and involves both theoretical and empirical methods to establish a robust relationship between gauge voltage output and irradiance intensity, quantifying both measurement and fitting errors. By addressing the limitations of existing standards and extending the characterization range, this work provides an advancement in the field of high-intensity irradiance measurement and instrumentation characterization.

Gardon gauge↗

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here we overcome this limitation by using a dual-gated ion injection approach to couple an 11-meter path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11-meter SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140k), and high-energy collision induced dissociation (HCD) in ~25 minutes over an $m/z$ range of ~1500 amu. The SLIM-Orbitrap was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (Rp CCS ) of ~218 and SLIM peak capacity of ~156 while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG 1+ , GRGDS 1+ , Rp CCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. In conclusion, this new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtainable with this system establishes the foundation for reference-free identification of unknown ion structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multiamorphous Phases in Diketopyrrolopyrrole-Based Conjugated Polymers: From Bulk to Ultrathin Films

The glass transition temperature (T g ) of conjugated polymers is a crucial physical parameter that governs their mechanical and electrical properties for applications from sensor technology to skin-like electronics. Despite some well-developed methods that exist for detecting T g of conjugated polymers, there is still a need for the combination of advanced calorimetric methodologies to characterize T g in a broad range of temperatures and scales from bulk to nanometer-thin films. In this work, alternating current (ac) chip calorimetry and flash differential scanning calorimetry (flash DSC) are applied to successfully identify the Tgs and segmental relaxations of conjugated polymers. The detected relaxations were interpreted, in agreement with existing observations in similar systems, as a side-chain relaxation (low temperature), mobile amorphous fractions (MAF), and rigid amorphous fractions (RAF). T g s of MAF and RAF increase and decrease with increasing size of fused thiophene units in the backbone, respectively. The T g s of diketopyrrolopyrrole-based conjugated polymer thin films are also identified by the same method, with both T g s showing a decreased value compared to those of bulk samples. Furthermore, the weight fractions of MAF and RAF with various film thicknesses are qualitatively analyzed based on the heat capacity step of each amorphous fraction during the glass transition. This facile method gives insights into the physical nature of amorphous phases in conjugated polymers for better revealing their structure-property relationships, which will guide the designs of new materials with optimized electrical and mechanical properties in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laser-Induced Trapping of Metastable Amorphous AlO x /C (2.5 < x ≤ 3.5) Nanocomposites: Implications for Use as Solid Phase Gas Generators

The synthesis of kinetically "frozen" metastable nanostructures remains elusive. This limitation has severely restricted the current paradigms in materials discovery. We overcame this challenge by phase-stabilizing unusually hyperoxidized and metastable amorphous aluminum oxide (a-AlO x ; 2.5 < x ≤ 3.5) nanostructures. Specifically, we employed laser ablation synthesis in solution (LASiS) as a one-pot nonequilibrium technique to achieve this pivotal advancement. Structural and compositional characterizations of the as-synthesized material reveal highly disordered a-AlO x nanoparticles that are remarkably stabilized by interfacial monolayers of ordered carbon atoms. Both structure and chemical composition were confirmed with disparate characterization methods at different length scales. The nanoparticles of sizes less than10 nm were stable even at elevated temperatures. Only at temperatures higher than 750 °C do the a-AlO x structures undergo a solid-solid phase transition that culminates in the formation of stable α-Al 2 O 3 while releasing excess trapped gases. In conclusion, such disruptive materials can find applications in emerging technologies seeking metastable phase-change materials for solid phase gas generators, batteries, neuromorphic computing, and energetic additives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗