Probing Atmospheric Aerosols by Multimodal Mass Spectrometry Techniques: Revealing Aging Characteristics of Its Individual Molecular Components
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54 ENVIRONMENTAL SCIENCES↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Insights into Nucleation and Growth of Colloidal Quaternary Nanocrystals by Multimodal X-ray Analysis
Copper chalcogenide nanocrystals find applications in photovoltaic inks, bio labels, and thermoelectric materials. We reveal insights in the nucleation and growth during synthesis of anisotropic Cu 2 ZnSnS 4 nanocrystals by simultaneously performing in situ X-ray absorption spectroscopy (XAS) and small-angle X-ray scattering (SAXS). Real-time XAFS reveals that upon thiol injection into the reaction flask, a key copper thiolate intermediate species is formed within fractions of seconds, which decomposes further within a narrow temperature and time window to form copper sulfide nanocrystals. These nanocrystals convert into Cu 2 ZnSnS 4 nanorods by sequentially incorporating Sn and Zn. Real-time SAXS and ex situ TEM of aliquots corroborate these findings. Our work demonstrates how combined in situ X-ray absorption and small-angle X-ray scattering enables the understanding of mechanistic pathways in colloidal nanocrystal formation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy
Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.
atomic force microscopy↗
Imaging from Macro to Nanoscale: Multimodal Advances in Chemical and Biomedical Imaging
Imaging increasingly serves as a multiscale framework for linking molecular mechanisms to cellular behavior, tissue architecture, and organ phenotypes in biology and unraveling fundamental processes in chemistry, physics and materials science. This Perspective highlights recent advances in chemical and biomedical imaging across macro-, micro-, and nanoscales, using representative examples published in Chemical and Biomedical Imaging (CBMI). At the macroscale, we discuss chemically selective MRI, including endogenous and exogenous CEST strategies, together with photoacoustic imaging as a hybrid modality with functional and chemical contrast. At the microscale, we consider fluorescence, label-free optical and vibrational imaging, and selected X-ray approaches that expand sensitivity, specificity, and temporal resolution in biological and materials systems. At the nanoscale, we highlight super-resolution fluorescence microscopy, single-molecule methods, tip-enhanced Raman spectroscopy, and correlative imaging strategies that resolve local heterogeneity and molecular organization. Across scales, a common theme emerges that advances in probes, contrast mechanisms, instrumentation, and sample handling are enabling chemically informed imaging that connects molecular specificity with biological context.
multiscale imaging↗
Multimodal Structure Solution with F-19 NMR Crystallography of Spin Singlet Molybdenum Oxyfluorides
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Ding, Fenghua↗
Understanding the Stability of Manganese Chromium Antimonate Electrocatalysts through Multimodal In Situ and Operando Measurements
Herein, we utilize an on-line electrochemical flow cell coupled with an inductively coupled plasma-mass spectrometer (ICP-MS) to characterize the impact of composition and reactant gas on the multielement dissolution of Mn(-Cr)-Sb-O electrocatalysts. Compared to Mn 2 O 3 and Cr 2 O 3 oxides, we find that the antimonate framework stabilizes Mn at OER potentials and Cr at both ORR and OER potentials. Furthermore, dissolution of Mn and Cr from Mn(-Cr)-Sb-O is found to be driven by ORR reaction rate, with minimal dissolution under N 2 . We observe preferential dissolution of Cr totaling 13% over 10 minutes at 0.3, 0.6, and 0.9 V vs RHE, with only 1.5% loss of Mn, indicating an enrichment of Mn at the surface of the particles. Despite this asymmetric dissolution, in situ X-ray absorption spectroscopy (XAS) showed no measurable changes in the Mn K-edge at comparable potentials. This lack of change could suggest that modification to the Mn oxidation state in the surface layer is too small or that layer is too thin to be measured with the bulk XAS measurement. Lastly, on-line ICP-MS was used to assess the effects of applied potential, scan rate, and current of Mn-Cr-Sb-O during cyclic voltammetry and accelerated stress tests. With this deeper understanding of the interplay between oxygen reduction and dissolution, testing procedures were identified to maximize both activity and stability. This work highlights the use of multi-modal in situ characterization techniques in tandem to build a more complete model of stability and develop protocols for optimizing catalyst performance.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multimodal In Situ Characterization Uncovers Unexpected Stability of a Cobalt Electrocatalyst for Acidic Sustainable Energy Technologies
An accelerated development of durable and affordable sustainable energy technologies is often hindered by a limited understanding of how non-precious materials within these systems degrade. In acidic proton exchange membrane fuel cells and water electrolyzers, metallic cobalt (Co) is considered an unstable component that is often combined with precious metals or other stabilizers. To understand the mechanisms behind Co instability, we employ an experimental platform that quantifies dissolution with on-line inductively coupled plasma mass spectrometry and product formation with electrochemical mass spectrometry during electrochemical testing, along with ex- situ characterization. Under varied conditions (electrocatalysis, time, gas-type saturation, and ion concentration), windows of Co stability are observed that are different than predicted with classical chemical thermodynamics, suggesting new stabilization and degradation mechanisms than previously understood. Notably, Co is active for the hydrogen evolution reaction (HER), with prolonged stability that is ~300 mV different than thermodynamically projected. Additionally, in an oxygenated environment, Co concurrently performs the HER and oxygen reduction reaction (ORR) yet undergoes different morphology changes and dissolution mechanisms. Interestingly, in the absence of electrocatalysis, there is a 22x decrease in dissolution in an oxygen-free environment, proposing a route to decrease Co losses during device shutdown protocols. Lastly, under more extreme operating conditions, Co becomes stable after a substantial amount of dissolution, suggesting that high concentrations of Co 2+ ions in the microenvironment induce the formation of a stable CoHO 2 surface. Altogether, these results can be leveraged to improve the design and development of more robust and cost-effective sustainable energy technologies, as well as promote strategic strategies for prolonged material utilization.
Dissolution↗
Air, surface, and wastewater surveillance of SARS-CoV-2; a multimodal evaluation of COVID-19 detection in a built environment
Environmental surveillance of infectious organisms holds tremendous promise to reduce human-to-human transmission in indoor spaces through early detection. In this study we determined the applicability and limitations of wastewater, indoor high-touch surfaces, in-room air, and rooftop exhaust air sampling methods for detecting SARS-CoV-2 in a real world building occupied by residents recently diagnosed with COVID-19. We concurrently examined the results of three 24-hour environmental surveillance techniques, indoor surface sampling, exhaust air sampling and wastewater surveillance, to the known daily census fluctuations in a COVID-19 isolation dormitory. Additionally, we assessed the ability of aerosol samplers placed in the large volume lobby to detect SARS-CoV-2 multiple times per day. Our research reveals an increase in the number of individuals confirmed positive with COVID-19 as well as their estimated human viral load to be associated with statistically significant increases in viral loads detected in rooftop exhaust aerosol samples (p = 0.0413), wastewater samples (p = 0.0323,), and indoor high-touch surfaces (p < 0.001)). We also report that the viral load detected in lobby aerosol samples was statistically higher in samples collected during presence of occupants whose COVID-19 diagnostic tests were confirmed positive via qPCR compared to periods when the lobby was occupied by either contact-traced (suspected positive) individuals or during unoccupied periods (p = 0.0314 and <2e–16). We conclude that each daily (24h) surveillance method, rooftop exhaust air, indoor high-touch surfaces, and wastewater, provide useful detection signals for building owner/operator(s). Furthermore, we demonstrate that exhaust air sampling can provide spatially resolved signals based upon ventilation exhaust zones. Additionally, we find that indoor lobby air sampling can provide temporally resolved signals useful during short duration sampling periods (e.g., 2-4 hours) even with intermittent occupancy by occupants diagnosed with COVID-19.
60 APPLIED LIFE SCIENCES↗
Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data
Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.
97 MATHEMATICS AND COMPUTING↗
A multimodal approach to revisiting oxidation defects in Cr 2 O 3
The oxidation of chromium in air at 700 °C was investigated with a focus on point defect behavior and transport during oxide layer growth. A comprehensive set of characterization techniques targeted characteristics of chromium oxide microstructure and chemical composition analysis. TEM showed that the oxide was thicker with longer oxidation times and that, for the thicker oxides, voids formed at the metal/oxide interface. PAS revealed that the longer the oxidation time, there was an overall reduction in vacancy-type defects, though chromium monovacancies were not found in either case. EIS found that the longer oxidized material was more electrochemically stable and that, while all oxides displayed p-type character, the thicker oxide had an overall lower charge carrier density. Together, the results suggest anion oxygen interstitials and chromium vacancy cluster complexes drive transport in an oxidizing environment at this temperature, providing invaluable insight into the mechanisms that regulate corrosion.
36 MATERIALS SCIENCE↗
Deciphering electrocatalysts with multimodal operando approaches
Here, the electrocatalytic processes of a copper catalyst during nitrate electroreduction are unveiled by correlated operando microscopy and spectroscopy. Catalysts are vital to the modern chemical industry, yet their development has largely relied on trial-and-error approaches. Optimizing catalysts requires a fundamental understanding of their structure–chemical property behaviour under operational conditions. However, operando characterization remains challenging, especially for reactions occurring in the complex and dynamic liquid environments of electrochemical systems. Over the past decade, the rapid development of in situ and operando environmental transmission electron microscopy (ETEM) and microelectromechanical system (MEMS)-based closed-cell holders, enabling environmental studies within the vacuum environment of transmission electron microscopy (TEM), has substantively advanced understanding of heterogeneous catalysis, notably for gas-phase reactions. In situ ETEM enables the direct observation of the catalyst evolution in terms of structure, morphology and chemical state at the nano-to-atomic scale, providing insights into their correlation with catalytic performance.
36 MATERIALS SCIENCE↗
Three-dimensional characterization of modifications in sapphire exposed to laser-induced damage using multimodal spectral microimaging
Sapphire (Al 2 O 3 ) is a commonly used dielectric material with many applications in lasers and optical systems. Owing to its high resistivity to laser induced damage, it is particularly suitable for use in high power laser systems. This work focuses on developing techniques to characterize material modifications in sapphire. These techniques were applied following localized laser induced ablation, commonly referred to as laser-damage, resulting from exposure to single 100-ps and 6-ns pulses. Measurements of fluorescence-based piezospectroscopy and confocal Raman microscopy were performed with spatial resolution on the order of 1 μ m. Raman microscopy reveals that the relaxation of material exposed to the rapid laser heating, elastic and viscoplastic deformation, melting, and solidification leads to the formation of a polycrystalline material phase. In addition, narrowband fluorescence lines, referred to as R 1 and R 2 , exhibit pressure-sensitive changes to their spectral profiles, allowing 3D internal stresses to be recorded with spatial resolution of the order of a few micrometers.
Laser-damage↗
In situ plant materials hyperspectral imaging by multimodal scattering near-field optical microscopy
Plant cells are elaborate three-dimensional polymer nano-constructs with complex chemistry. The bulk response of plants to light, in the far-field, is ultimately encoded by optical scattering from these nano-constructs. Their chemical and physical properties may be acquired through their interaction with a modulated nano-tip using scattering scanning near-field optical microscopy. Here, using this technique, we present 20 nm spatial resolution mechanical, spectral and optical mappings of plant cell walls. We first address the problem of plant polymers tracking through pretreatment and processing. Specifically, cellulose and lignin footprints are traced within a set of delignified specimen, establishing the factors hindering complete removal of lignin, an important industrial polymer. Furthermore, we determine the frequency dependent dielectric function ${\epsilon }(\omega)={(n+ik)}^{2}$ of plant material in the range 28 ≤ ω ≤ 58 THz, and show how the environmental chemical variation is imprinted in the nanoscale variability of n and k . This nanometrology is a promise for further progress in the development of plant-based (meta-)materials.
36 MATERIALS SCIENCE↗
Multimodal electrochemistry coupled microcalorimetric and X-ray probing of the capacity fade mechanisms of Nickel rich NMC – progress and outlook
Combining calorimetry with hard and soft X-ray characterization elucidates bulk and surface phenomena responsible for capacity fade in LiNi 0.8 Mn 0.1 Co 0.1 O 2 cathodes.
Quilty, Calvin D.↗
Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials
Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Pursuing theranostics: a multimodal architecture approach
Theranostics is a field of nuclear medicine which uses the same targeting vector and chelating system for both a diagnostic and therapeutic radionuclide, allowing for uniformity in imaging and treatment.
Bender, Aidan A. [Nuclear Engineering Program, Uni↗
Detection of photon statistics and multimode field correlations by Raman processes
Glauber’s g (2) -function provides a common measure of quantum field statistics through two-photon coincidence counting in Hanbury Brown–Twiss measurements. Here, we propose to use nonlinear optical signals as a tool for the characterization of quantum light. In particular, we show that Raman measurements provide an alternative direct probe for a different component of the four-point correlation function underlying the g (2) -function. We illustrate this capacity for a specific quantum state obtained from a frequency conversion process. Our work points out how the analysis of controlled optical nonlinear processes can provide an alternative window toward the analysis of quantum light sources.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗