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At least 1,351 records · Page 75

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗

Σ3(111) Grain Boundaries Accelerate Hydrogen Insertion into Palladium Nanostructures

Grain boundaries (GBs) are frequently implicated as key defect structures facilitating metal hydride formation, yet their specific role remains poorly understood due to their structural complexity. Here, we investigate hydrogen insertion in Pd nanostructures enriched with well-defined Σ3(111) GBs (Pd GB ) synthesized via electrolysis-driven nanoparticle assembly. In situ synchrotron X-ray diffraction reveals that Pd GB exhibits dramatically accelerated hydriding and dehydriding kinetics compared with ligand-free and ligand-capped Pd nanoparticles with similar crystallite sizes. Strain mapping using environmental transmission electron microscopy shows that strain is highly localized at GBs and intensifies upon hydrogen exposure, indicating preferential hydrogen insertion along GB sites. Density functional theory calculations provide mechanistic insight supporting these findings, showing that hydrogen insertion near Σ3(111) GBs is energetically more favorable and that tensile strain lowers insertion barriers. Furthermore, these results provide atomic-level insights into the role of GBs in hydride formation and suggest new design strategies for GB-engineered Pd-based functional materials.

Anions↗

Can Dithiolate Ligands Report Electronic Communication in Transuranium Complexes?

The actinide elements, and in particular the transuranic elements, are some of the least studied elements on the periodic table. The degree of covalent bonding between the actinide elements and ligands in is not well understood. Dithiolene/dithiolate ligands provided a revolution in understanding the bonding in transition metals through the geometric differences the ligands exhibit when interacting with electron deficient or abundant metal centers. To test if dithiolene/dithiolate ligands can be utilized to provide an analogous understanding of transuranic element bonding, density functional theory calculations have been performed on U, Np, and Pu complexes of the formula Cp 2 AnS 2 C 2 H 2 . These calculations show that the dithiolate maintains its non-innocent redox active nature when bonding with actinides. In stark contrast with the transition metals, the direction of electron donation is reversed, in the actinide series the direction of electron flow in high fold cases is from the metal center to the ligand. In conclusion, this suggests the communication is between the π* system of the ligand interacting with the f orbitals of the metal center.

Prange, Micah P. [Pacific Northwest National Labor↗

Assembly of Metalloporphyrin Peptoids into Crystalline Nanomaterials as a Multifunctional System for Biomimetic Catalysis and Sensing

While natural enzymes excel at catalysis and sensing, they often suffer from high cost and low stability in applications outside living systems. Among tremendous efforts made toward the design and synthesis of catalytic biomimetic materials, the approach of using crystalline nanomaterials assembled from sequence-defined polymers has emerged as a promising strategy. Herein, we report the assembly of metalloporphyrin peptoids into crystalline nanomaterials as a multifunctional system for biomimetic catalysis and sensing. The precise spatial positioning of covalently attached porphyrins within crystalline peptoid nanomaterials enables the mimicry of several enzyme active sites, including phosphotriesterase and horseradish peroxidase, for efficient catalytic hydrolysis and oxidation reactions. Additionally, the high programmability of these peptoid crystalline materials enables the creation and tuning of the active site microenvironment for enhanced catalytic activity. We further demonstrate the integration of responsive organic dyes into catalytic peptoid assemblies to achieve both detection and degradation of chemical warfare agent (CWA) mimics, even in the vapor phase. In conclusion, we expect this multifunctional system to provide tremendous opportunities in biomimetic catalysis and sensing, including the detoxification and detection of CWAs.

Catalysts↗

How Solvent Mediates the Catalytic Fate of 2-Methoxyphenol in Hydrodeoxygenation Catalysis?

Kinetic and isotopic assessments combined with theoretical calculations shed light on the mechanistic differences in terms of the number of hydrogen addition steps and the electronic charges of reactive hydrogen in the catalytic sequence leading to the Ar−OCH 3 scission of 2-methoxyphenol occurring at various interfaces of vapor−Ru, cyclohexane−Ru, and water−Ru. At vapor−Ru and cyclohexane−Ru interfaces, the initial hydrogen adatom (H*) additions on the phenyl ring disrupt its aromaticity, as a step required to occur before kinetically relevant Ar−OCH 3 scission on an ensemble of Ru sites. The number of H* addition events prerequisite to the formation of the kinetically relevant Ar−OCH 3 scission transition state, however, is larger at the cyclohexane−Ru interface than those at the vapor−Ru and water−Ru interfaces. The preferential solvation of 2-methoxyphenol derived reaction precursors and H* weakens their adsorption on Ru sites, which leads to a decrease in the activation barrier for the third H* addition step and in turn a larger number of H* additions. At the water−Ru interface, water as a polar protic solvent promotes the Ar−OCH 3 scission by enabling a mechanistically distinct catalytic route an adjacent water molecule from the solvent layer assists with the intramolecular proton shuttling from the hydroxyl group (−OH) to the vicinal methoxy group (−OCH 3 ) of 2-methoxyphenol, evolving a highly charged transition state that is further stabilized by the water solvent layer, thereby leading to Ar−OCH 3 scission rate constants that are much higher than those at the vapor−Ru interface and, when comparing at the same H 2 chemical potential, higher Ar−OCH 3 scission turnovers. Furthermore, these distinct mechanistic details of the Ar−OCH 3 scission at various reaction interfaces, inferred from experiment and theory, illustrate how a solvent either solvates reaction intermediates and transition states or directly participates in the formation of kinetically relevant transition states, leading to changes in the free energy landscape, thus rewriting the catalytic fates in hydrodeoxygenation reactions.

09 BIOMASS FUELS↗

In Situ Atmospheric Plume Thermometry via Carbon Monoxide Spectral Profile: Laboratory and Field Validation

For small molecules with large rotational constants, knowing the relative intensities of the ro-vibrational transitions can be used to determine the temperature within a gas plume. We demonstrate the use of carbon monoxide (CO) as an in situ spectroscopic probe of gas plume temperature by application of both laboratory and standoff Fourier transform infrared spectroscopy to monitor the CO spectral response at different temperatures. Here, the measured CO rotational contours were analyzed using a simple Boltzmann model to deduce the population distribution of the J-levels, from which the in-plume temperature is deduced. The method was vetted by comparing deduced temperatures in both static laboratory measurements of known temperatures, as well as field measurements using a simulated smokestack release. For the smokestack experiments, spectroscopically deduced temperatures were compared to readings from a series of thermocouples placed at strategically sampled distances along the plume trajectory. Both the spectroscopically-derived and thermocouple-measured temperatures revealed an expansion-induced (mixing) rapid cooling of the plume, with the infrared thermometry values displaying greater temperature values which are believed to better represent the actual plume temperatures.

Analysis of rotational structure↗

Synchronized Breathing in Anion-Derived Interphases

Anion-derived interphases are crucial for extending the cycle life of lithium metal batteries. While their benefits are often attributed to crystalline inorganic species like LiF and Li 2 O, the role of amorphous inorganic species and the interplay between the anode-electrolyte interphase (SEI) and the cathode-electrolyte interphase (CEI) remain largely unexplored. Here, in this study, we examine two model electrolyte systems─one with solvent-derived interphases and the other with anion-derived interphases─using advanced X-ray scattering and spectroscopy techniques. Our findings reveal that anion-derived interphases contain substantial amounts of amorphous inorganic species, leading to a unique synchronization of "breathing" between SEI and CEI. During charging, the SEI grows while the CEI shrinks; during discharging, these roles reverse. This distinctive interfacial behavior originates from the competition of deposition and dissolution of amorphous inorganics during cycling. The study highlights the unique role of amorphous inorganics in anion-derived interphases, providing new insights into improving battery performance and durability.

25 ENERGY STORAGE↗

Quantification of Shallow Defect Suppression in Aminosilane-Passivated Lead Halide Perovskites via Optical and Electrochemical Methods

We combine fluence-dependent photoluminescence (PL) and electrochemical characterization to estimate defect-dependent trapping rates, energetic distributions, and densities of defects, in lead halide perovskite films Cs 0.1 FA 0.9 PbI 3 and Cs 0.17 FA 0.83 Pb­(I 0.75 Br 0.25 ) 3 , before and after trap passivation with vapor-deposited (3-aminopropyl)­trimethoxysilane (APTMS). For both compositions, the PL studies show that energetically shallow subgap near-valence defect densities lead to bimolecular nonradiative recombination which is reduced by 92% after APTMS treatment. Electrochemical characterization of these same active layers shows for the first time that APTMS passivation impacts mainly on near-valence (mobile anionic) defects that decrease in density by 4 orders of magnitude, from 10 18 cm –3 to 10 14 cm –3 , as a result of silane modification. Here, the combination of PL and electrochemical characterization promises a unique approach to speciation and quantification of a broader distribution of trap states in perovskites and provides straightforward assessments of the efficacy of defect mitigation strategies.

Defects↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗

Subdiffraction Imaging of Carrier Dynamics in Halide Perovskite Semiconductors: Effects of Passivation, Morphology, and Ion Motion

In this article, we spatially resolve photocarrier dynamics in halide perovskites using time-resolved electrostatic force microscopy (trEFM) to map surface potential equilibration during photoexcitation. We present a unified interpretation of trEFM, which measures the evolution of the surface potential in response to photoexcitation. We show that trEFM measurements correlate with surface recombination velocity and carrier lifetimes, validated with time-resolved photoluminescence imaging. We further validate the interpretation of trEFM through wavelength- and intensity-dependent measurements and with drift-diffusion simulations. We compare several passivation agents, including (3-aminopropyl)trimethoxysilane (APTMS), [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS), and phenethylammonium iodide (PEAI). The results reveal heterogeneity in surface potential equilibration times that correlates with perovskite film morphology and nanoscale variations in recombination dynamics following surface passivation. Not only do our results highlight the potential for further improvement of passivation strategies, but also the necessity of high spatial and temporal resolution methods, like trEFM, to evaluate next-generation semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Expanding Parameter Space to Enable Low-Temperature Synthesis of Crystalline Indium Phosphide Quantum Dots

Established methods to synthesize indium phosphide quantum dots (QDs) require high temperatures (>180 °C) to make high-quality material for optoelectronic applications. Nonpolar solvent environments are overwhelmingly used in InP QD synthesis to reach the necessary high temperatures and for compatibility with the reactive precursors. In this study, we explored InP QD synthesis in polar aprotic solvent environments to dramatically decrease the temperature required for InP crystallization by imparting ionicity to the precursors and stabilizing charged reaction intermediates. A custom air-free 96- well plate setup was employed to identify key factors impacting low-temperature QD formation, including an increased percentage of polar solvent, carboxylic acid choice, and inclusion of polar additives. Guided by these insights, we developed a synthesis of crystalline, green-emitting InP QDs at 60 °C in a toluene-dimethylformamide mixture. Here's, the QDs withstood established Zn 2+ and HF surface treatments, which increased the photoluminescence quantum yield to 25%. Additionally, we demonstrated the rapid synthesis of quasi-wurtzite InP QDs at room temperature in a polar solvent environment using an acid-free indium myristate precursor.

absorption↗

Probing Plasmonic Near-Fields in Oxide-Modified Aluminum Nanocubes Using Photon-Induced Near-Field Electron Microscopy

Plasmonic nanoparticles generate strong electric fields near their surface upon photoexcitation, enabling applications in sensing, spectroscopy, and photocatalysis. Electron microscopy techniques – such as cathodoluminescence and electron energy loss spectroscopy – have been leveraged to produce nanoscale maps of localized surface plasmon (LSP) modes. More recently, photon-induced near-field electron microscopy (PINEM) has emerged as a powerful technique for imaging evanescent near-fields generated by ultrafast laser excitation. In this work, we employ PINEM within an ultrafast electron microscope, complemented by numerical calculations to investigate how optical polarization, surface modification, and light intensity affect the evanescent fields associated with LSPs on oxide-modified aluminum nanocubes. Polarization control of the incident light field enables spatial mapping of the nanocube’s LSPs at the single particle level. Systematic variation of the oxide layer thickness reveals that increased coating thickness correlates with a stronger PINEM signal and a greater energy gain of probing electrons. Additionally, higher light intensities at fixed polarization and oxide coating further amplify the PINEM signal. These findings demonstrate the utility of PINEM as a high-resolution technique for optical near-field imaging and spectroscopy of single plasmonic nanoparticles. The ability to probe single particle behavior offers new opportunities for advancing the design and characterization of nanophotonic and plasmonic materials.

PINEM↗

Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model

Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large‐eddy simulation (LES). Our approach involves representing the cloud size distribution and the total cloud area using a revised Lotka‐Volterra model and ridge linear model, respectively. The physical interpretation of the total cloud area and coefficients obtained from the optimization of the models reveals three stages probably interpreted by dominant processes: the formation of new clouds, the growth of single clouds, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale‐aware parameterizations of shallow‐convective clouds in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

Coupled Lake‐Atmosphere‐Land Physics Uncertainties in a Great Lakes Regional Climate Model

Abstract This study develops a surrogate‐based method to assess the uncertainty within a convective permitting integrated modeling system of the Great Lakes region, arising from interacting physics parameterizations across the lake, atmosphere, and land surface. Perturbed physics ensembles of the model during the 2018 summer are used to train a neural network surrogate model to predict lake surface temperature (LST) and near‐surface air temperature (T2m). Average physics uncertainties are determined to be 1.5C for LST and T2m over land, and 1.9C for T2m over lake, but these have significant spatiotemporal variations. We find that atmospheric physics parameterizations alone are the dominant sources of uncertainty (45%–53%), while lake and land parameterizations account for 33% and 38% of the uncertainty of LST and T2m over land respectively. Interactions of atmosphere physics parameterizations with those of the land and lake contribute to an additional 13%–17% of the total variance. LST and T2m over the lake are more uncertain in the deeper northern lakes, particularly during the rapid warming phase that occurs in late spring/early summer. The LST uncertainty increases with sensitivity to the lake model's surface wind stress scheme. T2m over land is more uncertain over forested areas in the north, where it is most sensitive to the land surface model, than the more agricultural land in the south, where it is most sensitive to the atmospheric planetary boundary and surface layer scheme. Uncertainty also increases in the southwest during multiday temperature declines with higher sensitivity to the land surface model.

54 ENVIRONMENTAL SCIENCES↗

Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection

Abstract In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526 ), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime‐mean cloud‐base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass‐flux parameterizations need to (a) accurately predict the size and number of the deep‐mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.

54 ENVIRONMENTAL SCIENCES↗

Impact of Turbulence Representation on the Relationship Between Cloud Feedback and Aerosol‐Cloud Interaction in an E3SMv2 Perturbed Parameter Ensemble

Recent studies reveal an anti‐correlation between global cloud feedback (CF) and effective radiative forcing due to aerosol‐cloud interaction (ERFaci) in Earth system models, but the physical mechanisms underlying it remain uncertain. Here we investigate how different turbulence representations contribute to this relationship over the global ocean using an ensemble of Energy Exascale Earth System Model version 2 simulations with perturbed turbulence parameters. The anti‐correlation appears only in the tropical ascent regime. In the Northern Hemisphere midlatitude and high latitude regimes, there is no significant correlation, and in the tropical marine low cloud and Southern Ocean regimes, the correlation is positive. These opposite correlations are primarily driven by opposing CF responses to perturbed parameters. We find that the mean‐state turbulent mixing strength affects both CF and ERFaci, enabling strong correlations in certain regimes. This study highlights the complex linkages between CF and ERFaci through turbulent processes across diverse cloud regimes.

54 ENVIRONMENTAL SCIENCES↗

Radiative, Hydrologic, and Circulation Responses to Warming in Cess‐Potter Simulations Using the Global 3.25‐km SCREAM

Using the global 3.25-km Simple Cloud Resolving E3SM Atmosphere Model (SCREAM 3 km), a pair of 13-month Cess-Potter simulations are performed to quantify the radiative feedbacks and the hydrologic and circulation responses to warming. Large-scale aspects of SCREAM 3 km's top-of-atmosphere radiative fluxes, precipitation rates, and circulations are in good agreement with observations and reanalysis, with notable differences, including a drier lower free-troposphere in the Tropics, reduced precipitation and humidity over the Tropical West Pacific, and poleward shifted Southern Hemisphere midlatitude jet. In response to warming, SCREAM 3 km predicts a total radiative feedback within the top 15% of the CMIP5 and CMIP6 models, which puts it substantially higher than the feedback reported by other kilometer-scale models. SCREAM 3 km's high radiative feedback stems from a strongly positive shortwave cloud feedback, most prominent over the mid- and high-latitudes. SCREAM 3 km's high precipitation response also puts it among the highest of CMIP models, whereas its circulation response is within the spread of CMIP models. An ensemble of five perturbed initial condition Cess-Potter simulations with a 12 km version of SCREAM (SCREAM 12 km) is performed to characterize uncertainty and resolution sensitivity. It suggests that the uncertainty from analyzing a pair of 1-year simulations is small compared to the inter-model spread in feedbacks and precipitation response. SCREAM 12 km also produces a strong precipitation response to warming but a much lower cloud feedback and total radiative feedback. The results from these experiments suggest that the spread in climate feedbacks will likely persist in the next generation of kilometer-scale models.

54 ENVIRONMENTAL SCIENCES↗