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At least 253 records · Page 14

Possibility of an integrated transmission electron microscope: enabling complex in-situ experiments

Abstract Multimodal in-situ experiments are the wave of the future, as this approach will permit multispectral data collection and analysis during real-time nanoscale observation. In contrast, the evolution of technique development in the electron microscopy field has generally trended toward specialization and subsequent bifurcation into more and more niche instruments, creating a challenge for reintegration and backward compatibility for in-situ experiments on state-of-the-art microscopes. We do not believe this to be a requirement in the field; therefore, we propose an adaptive instrument that is designed to allow nearly simultaneous collection of data from aberration-corrected transmission electron microscopy (TEM), probe-corrected scanning transmission electron microscopy, ultrafast TEM, and dynamic TEM with a flexible in-situ testing chamber, where the entire instrument can be modified as future technologies are developed. The value would be to obtain a holistic understanding of the underlying physics and chemistry of the process-structure–property relationships in materials exposed to controlled extreme environments. Such a tool would permit the ability to explore, in-situ, the active reaction mechanisms in a controlled manner emulating those of real-world applications with nanometer and nanosecond resolution. If such a powerful tool is developed, it has the potential to revolutionize our materials understanding of nanoscale mechanisms and transients. Graphical Abstract

36 MATERIALS SCIENCE↗

Predicting defects in laser powder bed fusion using in-situ thermal imaging data and machine learning

Variation in the local thermal history during the Laser Powder Bed Fusion (LPBF) process in Additive Manufacturing (AM) can cause micropore defects, which add to the uncertainty of the mechanical properties (e.g., fatigue life, tensile strength) of the built materials. In-situ sensing has been proposed for monitoring the AM process to minimize defects, but successful minimization requires establishing a quantitative relationship between the sensing data and the porosity, which is particularly challenging with a large number of variables (e.g., laser speed, power, scan path, powder property). Physics-based modeling can simulate such an in-situ sensing-porosity relationship, but it is computationally costly. In this work, we develop Machine Learning (ML) models that can use in-situ thermographic data to predict the micropore of LPBF stainless steel materials. This work considers two identified key features from the thermal histories: the time above the apparent melting threshold ($\tau$) and the maximum radiance ( T max ). These features are computed, stored for each voxel in the built material, and then used as inputs. The binary state of each voxel, either defective or normal, is the output. Different ML models are trained and tested for the binary classification task. In addition to using the thermal features of each voxel to predict its own state, the thermal features of neighboring voxels are also included as inputs. This is shown to improve the prediction accuracy, which is consistent with thermal transport physics around each voxel contributing to its final state. Among the models trained, the F1 scores on test sets reach above 0.96 for Random Forests. Feature importance analysis based on the ML models shows that T max is more important to the voxel state than $\tau$ . The analysis also finds that the thermal history of the voxels above the present voxel is more influential than those beneath it. Our study significantly extends the capability of using in-situ thermographic data to predict porosity in LPBF materials. Finally, since ML models are fast, they may play integral roles in the optimization and control of such AM technologies.

36 MATERIALS SCIENCE↗

In situ characterization of phase transformations in petroleum pitch by high temperature X-ray diffraction

The phase transformation from isotropic to mesophase of a petroleum-derived pitch was monitored by in situ X-ray diffraction at 410 °C. The kinetics of the transformation were characterized by monitoring the growth of a broad peak at 2θ~24° and could be described by Avrami’s equation. The volatilization of low molecular weight components originally present in the pitch, or produced during the condensation reaction, was assessed by thermal gravimetry analysis, following the same thermal history. Ex situ characterizations of the pitch precursor before and after thermal treatment provided insight into the evolution of the molecular structure associated with mesophase generation (optical polarized microscopy, molecular weight distribution by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, X-ray photoelectron spectroscopy, Auger spectroscopy, and thermal stability). Here, this investigation demonstrates the value of using complementary in situ and ex situ experimental techniques to characterize complex mechanisms during the processing of organic materials.

02 PETROLEUM↗

Tensile behavior and microstructural evolution of a Fe-25Ni-20Cr austenitic stainless steel (alloy 709) from room to elevated temperatures through in-situ synchrotron X-ray diffraction characterization and transmission electron microscopy

Uniaxial tensile tests were done on Fe-25Ni-20Cr Austenitic Stainless Steel (Alloy 709) along with in-situ synchrotron measurement at different temperatures (25 degrees C, 500 degrees C, 700 degrees C and 900 degrees C). The X-Ray diffraction data was collected in-situ in order to follow the phases present as well as to derive the dislocation density as a function of strain through peak broadening analysis based on the modified Williamson-Hall method and see how trends are affected as a function of temperature. The XRD data were complemented by TEM and STEM-EDX characterization done on the post-experiment samples to observe the deformed microstructures. Finally, the paper presents a depiction of the tensile behavior of this advanced steel by interpreting the stress-strain curves and the effect of temperature through the information gained by in-situ XRD and TEM observations as well as fractography done ex-situ on the samples tested to rupture.

36 MATERIALS SCIENCE↗

Demonstrating the viability of Lagrangian in situ reduction on supercomputers

Performing exploratory analysis and visualization of large-scale time-varying computational science applications is challenging due to inaccuracies that arise from under-resolved data. In recent years, Lagrangian representations of the vector field computed using in situ processing are being increasingly researched and have emerged as a potential solution to enable exploration. However, prior works have offered limited estimates of the encumbrance on the simulation code as they consider “theoretical” in situ environments. Further, the effectiveness of this approach varies based on the nature of the vector field, benefitting from an in-depth investigation for each application area. With this study, an extended version of Sane et al. (2021), we contribute an evaluation of Lagrangian analysis viability and efficacy for simulation codes executing at scale on a supercomputer. We investigated previously unexplored cosmology and seismology applications as well as conducted a performance benchmarking study by using a hydrodynamics mini-application targeting exascale computing. Here, to inform encumbrance, we integrated in situ infrastructure with simulation codes, and evaluated Lagrangian in situ reduction in representative homogeneous and heterogeneous HPC environments. To inform post hoc accuracy, we conducted a statistical analysis across a range of spatiotemporal configurations as well as a qualitative evaluation. Additionally, our study contributes cost estimates for distributed-memory post hoc reconstruction. In all, we demonstrate viability for each application — data reduction to less than 1% of the total data via Lagrangian representations, while maintaining accurate reconstruction and requiring under 10% of total execution time in over 90% of our experiments.

97 MATHEMATICS AND COMPUTING↗

Deep Learning enabled spectral energy conversion for in situ exposure measurements

A detector-specific deep learning (DL) approach is presented for spectra-to-exposure conversion using large-format sodium iodide (NaI(Tl)) detectors deployed for in situ environmental radiation measurements in emergency response scenarios. Accurate determination of exposure from NaI spectra is challenging due to poor energy resolution, partial energy absorption, and the strong sensitivity of traditionally deployed analytical conversion methods to calibrated source geometry and pre-deployment assumptions. Here, to address these limitations, a multi-layer perceptron model was trained on a hybrid in situ /Monte Carlo dataset constructed to span a broad range of photon energies, spatial extents, and realistic deployment variability, representative of general in situ emergency response conditions. The DL model was evaluated against commonly fielded analytical approaches under matched simulation conditions, including a single-factor method, a G-function method, and a modeled pressurized ion chamber (PIC) baseline. This study was intentionally computational in scope to enable controlled, like-for-like comparisons between conversion techniques while minimizing confounding real-world variability. Comparison to the modeled PIC provides contextual benchmarking and is not intended as a field inter-comparison with deployed instruments. Across the evaluated 20 keV to 3 MeV energy range, the DL approach consistently exhibited higher accuracy and reduced variance relative to the analytical methods against a deterministically calculated exposure. This may indicate improved robustness to spectral complexity without reliance on source-, geometric-, or spectral region-specific optimization. While results do not represent real-world validation, the presented work demonstrates that deep learning may effectively learn the nonlinear detector response-to-exposure relationship for asymmetric NaI(Tl) detectors and offers a promising pathway for improving in situ exposure estimation using spectroscopic systems already integrated into initial real-time emergency response operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

In Situ Observation of Ion Migration in a Ferroelectric Ionic Conductor Rb-KTP during Thermal Annealing

Ion exchange in Rb-doped KTiOPO 4 has facilitated significant advancements in ferroelectric domain engineering, yet understanding the underlying mechanisms remains in its infancy. We perform time-of-flight secondary ion mass spectrometry analysis on multiple periodically ion-exchanged and periodically poled Rb-doped KTiOPO 4 samples under different temperatures and annealing durations. The results are compared between annealing in air, which involved ex situ annealing before periodic poling, and vacuum annealing conducted in situ after periodic poling. The Rb + diffusion profile after periodic ion exchange forms a tooth-shaped pattern. We show that in situ annealing causes a surface pinning effect on the nonpolar face, limiting Rb + migration along the polar axis at the surface. Once the pinned layer is removed through milling, the underlying Rb + diffusion is distinctively different from the surface. Additionally, the rate of Rb + diffusion during in situ annealing is linear, while the periodic domain structures remain stable after annealing. These results contribute to understanding the ionic diffusion process in a ferroelectric ionic conductor and using ion exchange to tailor the linear and nonlinear properties of KTiOPO 4 .

36 MATERIALS SCIENCE↗

In Situ Phosphatizing of Triphenylphosphine Encapsulated within Metal–Organic Frameworks to Design Atomic Co 1 –P 1 N 3 Interfacial Structure for Promoting Catalytic Performance

The engineering coordination environment offers great opportunity in performance tunability of isolated metal single-atom catalysts. For the most popular metal–N x (MN x ) structure, the replacement of N atoms by some other atoms with relatively weak electronegativity has been regarded as a promising strategy for optimizing the coordination environment of an active metal center and promoting its catalytic performance, which is still a challenge. Herein, we proposed a new synthetic strategy of an in situ phosphatizing of triphenylphosphine encapsulated within metal–organic frameworks for designing atomic Co 1 –P 1 N 3 interfacial structure, where a cobalt single atom is costabilized by one P atom and three N atoms (denoted as Co-SA/P-in situ). In the acidic media, the Co-SA/P-in situ catalyst with Co 1 –P 1 N 3 interfacial structure exhibits excellent activity and durability for the hydrogen evolution reaction (HER) with a low overpotential of 98 mV at 10 mA cm –2 and a small Tafel slope of 47 mV dec –1 , which are greatly superior to those of catalyst with Co 1 –N 4 interfacial structure. We discover that the bond-length-extended high-valence Co 1 –P 1 N 3 atomic interface structure plays a crucial role in boosting the HER performance, which is supported by in situ X-ray absorption fine structure (XAFS) measurements and density functional theory (DFT) calculation. With this work, we hope to promote the development of high performance metal single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An in situ generated polymer electrolyte via anionic ring-opening polymerization for lithium–sulfur batteries

The use of solid polymer electrolytes has previously proven to be an effective approach to address the lithium polysulfide dissolution and high electrode interfacial impedance of Li–S batteries via an in situ polymerization process. However, the conventional in situ synthesis employs a cationic ring-opening polymerization (CROP) of 1,3-dioxolane (DOL) catalyzed by a strong Lewis acid. New polymerization chemistry that is more compatible with Li–S chemistry needs to be developed to mitigate the disadvantages associated with the CROP process. Herein we report a new approach to in situ polymerize a set of new episulfide monomers in solution with LiTFSI salt via an anionic ring-opening polymerization (AROP). This new polymer system takes advantage of the inherent cell chemistry present in the Li–S cell through the nucleophilic lithium sulfides which are generated during the initial discharge cycle and act as the initiator for the polymerization. Additionally, their presence was shown to initiate the monomer solvents through AROP with no need for additional catalysts, rather than the more commonly utilized cationic systems which require an external Lewis acid catalyst. This work offers an important pathway toward in situ polymer electrolytes for Li–S batteries and offers a new avenue of exploration for polymer electrolyte synthesis.

25 ENERGY STORAGE↗

Synergy between Ni and Fe in NiFe aerogel oxygen evolution reaction catalyst: in situ 57 Fe Mössbauer and X-ray absorption spectroscopy studies

Anion-exchange-membrane water electrolyzers (AEMWE) for hydrogen production have attracted interest because cost-effective Ni- and Fe-based catalysts can be used for the oxygen evolution reaction (OER). Although NiFe oxide/hydroxide-based catalysts have been extensively studied, the role of Fe and its chemical state during OER are not well understood, with inconsistent findings across different studies. In this work, we combined in situ 57 Fe Mössbauer (MS) and X-ray absorption spectroscopy (XAS) to investigate the chemical states of Fe and Ni and elucidate their synergy during the OER. A NiFe (8 : 1 molar ratio) aerogel catalyst with high surface area, nano crystallinity, and high performance in AEMWE was used. We show that both Fe and Ni are oxidized during anodic polarization, and the potential for the change of oxidation states correlates well with the onset of the OER. In situ MS shows that 80–90% of Fe 3+ becomes tetravalent at OER potentials and remains so even after the potential is lowered below OER onset. Analysis of in situ XAS results suggests full Fe incorporation into Ni hydroxide. At OER potentials, lattice contraction indicates high oxidation states for both Ni and Fe. Upon returning to lower potentials, a portion of the Fe remains in its more oxidized form which corroborates the in situ MS findings. Results from this work affirm the importance of high-valent Ni and Fe in promoting the OER. Ni and Fe exhibit synergy during OER and the aerogel's unique nanomorphology leads to high OER activity.

36 MATERIALS SCIENCE↗

An in situ shearing x-ray measurement system for exploring structures and dynamics at the solid–liquid interface

Revealing interfacial structure and dynamics has been one of the essential thematic topics in material science and condensed matter physics. Synchrotron-based x-ray scattering techniques can deliver unique and insightful probing of interfacial structures and dynamics, in particular, in reflection geometries with higher surface and interfacial sensitivity than transmission geometries. We demonstrate the design and implementation of an in situ shearing x-ray measurement system, equipped with both inline parallel-plate and cone-and-plate shearing setups and operated at the advanced photon source at Argonne National Laboratory, to investigate the structures and dynamics of end-tethered polymers at the solid-liquid interface. With a precise lifting motor, a micrometer-scale gap can be produced by aligning two surfaces of a rotating upper shaft and a lower sample substrate. A torsional shear flow forms in the gap and applies tangential shear forces on the sample surface. The technical combination with nanoscale rheology and the utilization of in situ x-ray scattering allow us to gain fundamental insights into the complex dynamics in soft interfaces under shearing. In this work, we demonstrate the technical scope and experimental capability of the in situ shearing x-ray system through the measurements of charged polymers at both flat and curved interfaces upon shearing. Furthermore, through the in situ shearing x-ray scattering experiments integrated with theoretical simulations, we aim to develop a detailed understanding of the short-range molecular structure and mesoscale ionic aggregate morphology, as well as ion transport and dynamics in soft interfaces, thereby providing fundamental insight into a long-standing challenge in ionic polymer brushes with a significant technological impact.

36 MATERIALS SCIENCE↗

In situ multimodal imaging for nanoscale visualization of tribofilm formation

A third of the energy from fuel combustion in passenger car gasoline engines is lost due to friction. Carefully designed engine lubricants can recover some of these losses by reducing friction and wear by forming a nanometer-scale chemico-physico tribofilm between surfaces. Accordingly, attention has focused on developing oil formulations that form low-friction tribofilms. However, analyses of resultant tribofilms are typically conducted after tribo-tests with conventional characterization tools and do not offer insights into tribofilm formation and evolution, precluding information critical to tuning tribofilm properties. In this work, we developed a unique multimodal methodology based on Atomic Force Microscopy (AFM) with local probe heating for in situ tribological studies that activates friction modifiers and simultaneously captures the evolution of friction and surface roughness, with nanometer resolution. As a platform to demonstrate the ability of this methodology to visualize dynamics of tribofilm formation in situ, we apply it to molybdenum-based friction modifiers to distinguish key factors in their functionality and correlate nanoscale AFM and Friction Force Microscopy data to bench tribo-tests used in the industry. To decode the formation mechanisms observed in situ and underlying chemistry of tribofilms, we performed ab initio Molecular Dynamics (AIMD) simulations at comparable conditions. AIMD simulations confirmed both nanoscale and bench tribo-test results and showed deviations in molecular organization in tribofilms that are formed from different molybdenum-based friction modifiers that corroborates with surface functionality. With this innovative methodology, we demonstrate proof-of-principle in situ formation of molybdenum-based tribofilms directly on steel surfaces that could be applied generally to studying tribofilm formation.

36 MATERIALS SCIENCE↗

Deciphering the influence of high-flux helium plasma exposure on tungsten nanostructure growth using real-time, in situ spectroscopic ellipsometry

In situ analysis of surfaces during high-flux plasma exposure represents a long-standing challenge in the study of plasma–material interactions. While post-mortem microscopy can provide a detailed picture of structural and compositional changes, in situ techniques can capture the dynamic evolution of the surface. In this study, we demonstrate how spectroscopic ellipsometry can be applied to the real-time characterization of W nanostructure (also known as “fuzz”) growth during exposure to low temperature, high-flux He plasmas. Strikingly, over a wide range of sample temperatures and helium fluences, the measured ellipsometric parameters (Ψ,Δ) collapse onto a single curve that can be directly correlated with surface morphologies characterized by ex situ helium ion microscopy. The initial variation in the (Ψ,Δ) parameters appears to be governed by small changes in surface roughness (<50 nm) produced by helium bubble nucleation and growth, followed by the emergence of 50 nm diameter W tendrils. This basic behavior appears to be reproducible over a wide parameter space, indicating that the spectroscopic ellipsometry may be of general practical use as a diagnostic to study surface morphologies produced by high-flux He implantation in refractory metals. An advantage of the methods outlined here is that they are applicable at low incident ion energies, even below the sputtering threshold. As an example of this application, we apply in situ ellipsometry to examine how W fuzz growth is affected both by varying ion energy and the temperature of the surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

X-ray sources for in situ wavelength calibration of x-ray imaging crystal spectrometers

X-ray sources for a range of wavelengths are being considered for in situ calibration of X-ray Imaging Crystal Spectrometers (XICSs) and for monitoring line shifts due to changes in the crystal temperature, which can vary during experimental operation over a day [A. Ince-Cushman et al., Rev. Sci. Instrum. 79, 10E302 (2008), L. Delgado-Aparicio et al., Plasma Phys. Control. Fusion 55, 125011 (2013)]. Such crystal temperature dependent shifts, if not accounted for, could be erroneously interpreted as Doppler shifts leading to errors in plasma flow-velocity measurements. The x-ray sources encompass characteristic x-ray lines falling within the wavelength range of 0.9–4.0 Å, relevant for the XICSs on present and future fusion devices. Several technological challenges associated with the development of x-ray sources for in situ calibration are identified and are being addressed in the design of multiple x-ray tubes, which will be installed inside the spectrometer housing of the XICS for the JT-60SA tokamak. These x-ray sources will be especially useful for in situ calibration between plasma discharges. Here, in this paper, laboratory experiments are described that were conducted with a Cu x-ray source, a heated quartz (102) crystal, and a pixelated Pilatus detector to measure the temperature dependent shifts of the Cu Kα 1 and Kα 2 lines at 1.5405 and 1.5443 Å, respectively, and to evaluate the 2d-lattice constant for the Bragg reflecting crystal planes as a function of temperature, which, in the case of in situ wavelength calibration, would have to be used for numerical analysis of the x-ray spectra from the plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dual Channel Dual Staging: Hierarchical and Portable Staging for GPU-Based In-Situ Workflow

In-situ workflows have emerged as an attractive approach for addressing data movement challenges at very large scales. Since GPU-based architectures dominate the HPC landscapes, porting these in-situ workflows, and, specifically, the inter-application data exchange, to GPU-based systems can be challenging. Technologies such as GPUDirect RDMA (GDR), which is typically used for I/O in GPU applications as an optimization that circumvents the CPU overhead, can be leveraged to support bulk data exchanges between GPU applications. However, current GDR design often lacks performance portability across HPC clusters built with different hardware configurations. Furthermore, the local CPU may also be effectively used as an auxiliary communication mechanism to offload data exchanges. In this paper, we present a dual channel dual staging approach for efficient, scalable, and performance-portable inter-application data exchange for in-situ workflows. This approach exploits the data access pattern within in-situ workflows along with the inherent execution asynchrony to accelerate data exchanges and, at the same time, improve performance portability. Specifically, the dual channel dual staging method leverages both the local CPU and the remote data staging server to build a hierarchical joint staging area and uses this staging area to transform blocking inter-application bulk data exchanges into best-effort local data movements between GPU and CPU. The dual channel dual staging is implemented as a portability extension of the Dataspaces-GPU staging framework. We present an experimental evaluation of its performance, portability, and scalability using this implementation on three leadership GPU clusters. The evaluation results demonstrate that the dual channel dual staging method saves up to 75% in data-exchange time compared to host-based, GDR, and alternate portable designs, while maintaining scalability (up to 512 GPUs) and performance portability across the three platforms.

Zhang, Bo [University of Utah]↗

Co-scheduling Ensembles of In Situ Workflows

Molecular dynamics (MD) simulations are widely used to study large-scale molecular systems. HPC systems are ideal platforms to run these studies, however, reaching the necessary simulation timescale to detect rare processes is challenging, even with modern supercomputers. To overcome the timescale limitation, the simulation of a long MD trajectory is replaced by multiple short-range simulations that are executed simultaneously in an ensemble of simulations. Analyses are usually co-scheduled with these simulations to efficiently process large volumes of data generated by the simulations at runtime, thanks to in situ techniques. Executing a workflow ensemble of simulations and their in situ analyses requires efficient co- scheduling strategies and sophisticated management of computational resources so that they are not slowing down each other. In this paper, we propose an efficient method to co-schedule simulations and in situ analyses such that the makespan of the workflow ensemble is minimized. We present a novel approach to allocate resources for a workflow ensemble under resource constraints by using a theoretical framework modeling the workflow ensemble’s execution. We evaluate the proposed approach using an accurate simulator based on the WRENCH simulation framework on various workflow ensemble configurations. Results demonstrate the significance of co-scheduling simulations and in situ analyses that couple data together to benefit from data locality, in which inefficient scheduling decisions can lead to slowdown in makespan up to a factor of 30.

Do, Tu Mai Anh↗

Review—In Situ X-ray and Infrared Spectroscopic Studies of Electrochemical Systems

Despite of intense research and a wealth of data, the phenomena occurring during electrocatalysis are still a major obstacle in many chemical processes. Molecular analysis of the electrode/electrolyte interface is needed to correctly describe the reaction through identifying the species involved, their interaction with the environment and kinetics in situ, i.e. while the reaction is taking place. That can be done by coupling the electrochemical system with complementary non-electrochemical techniques. Particularly revealing are in situ X-ray spectroscopic techniques to analyze the electrode itself, providing the information on the changes in the catalyst during the reaction. The synergy of the traditional electrochemical techniques with the complementary spectroscopic methodologies offer understanding of the electrode/electrolyte interface above and beyond traditional experimental mainframe. Here we demonstrate how in situ X-ray absorption spectroscopy (XAS), in situ infrared reflection/absorption spectroscopy (IRRAS), and traditional voltammetric studies can increase our understanding of electrochemical processes during oxidation of ethanol. The results show the pronounced role of electrode surface in determining reaction kineticks and revealed the selectivity of the catalyst to complete oxidation pathway. They further provide understanding of the parameters that enhance its oxidation for future designing catalysts for alcohol oxidation fuel cells.

30 DIRECT ENERGY CONVERSION↗

The ECP ALPINE project: In situ and post hoc visualization infrastructure and analysis capabilities for exascale

A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude the speed at which we save these results. Therefore the Exascale Computing Project (ECP) ALPINE project focuses on providing exascale-ready visualization solutions including in situ processing. In situ visualization and analysis runs as the simulation is run, on simulations results are they are generated avoiding the need to save entire simulations to storage for later analysis. The ALPINE project made post hoc visualization tools, ParaView and VisIt, exascale ready and developed in situ algorithms and infrastructures. The suite of ALPINE algorithms developed under ECP includes novel approaches to enable automated data analysis and visualization to focus on the most important aspects of the simulation. Many of the algorithms also provide data reduction benefits to meet the I/O challenges at exascale. ALPINE developed a new lightweight in situ infrastructure, Ascent.

97 MATHEMATICS AND COMPUTING↗