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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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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A conceptual model for how to design for building envelope characteristics. Impact of thermal comfort intervals and thermal mass on commercial buildings in U.S. climates

The paper presents a simplified conceptual model for energy demand calculations based on building envelope characteristics, thermal mass and local climate. It is based on a network model and lumped analysis of the dynamic process. Characteristic parameters for the buildings are suggested; Driving temperature (DT), Driving temperature difference, (DTD), External Load Temperature (ELT), and Thermal Load Resistance (TLR). The Building Envelope Performance ( BEP 0 ), based on a controlled constant indoor temperature is introduced. Solution techniques using stable explicit forward differences based on analytical solutions are derived. The conceptual model has been used for mapping the Driving temperature difference and introduced two performance factors and . The first factor represents the effect of thermal comfort interval and thermal mass on the energy demand. The latter represents the ratio between cooling and heating energy demand. These three parameters and factors have been visualized on U.S. maps and enable a possibility to communicate the demand of energy, and cooling and the coupling to building characteristics, in a concise way.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Computational predictions of porosities, pore size distributions, and conductivities of aerosol deposited particulate films

The structure and resulting physical properties of aerosol deposited particulate films are governed by the size distribution and morphology of the depositing particles as well as the physics governing particle deposition. While particulate film deposition processes are qualitatively understood, the link between particle characteristics and deposition physics to film properties has not been probed systematically. Here we apply a combination of Langevin dynamics deposition simulations, Monte Carlo pore size distribution calculations, and predictions of thermal conductivities to better establish such process parameter-film property relationships. Furthermore, we account for partial coalescence, polydispersity, and aggregate deposition. We establish that the deposition of polydisperse and aggregated particles leads to broadening of the pore size distribution function and an increase in the mode pore size. Via a non-continuum gas conductivity model, we show that aerosol deposited films can achieve porosities and thermal conductivities similar to conventional aerogels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Demonstration and technoeconomic analysis of dodecanol production from acetate using metabolically engineered Escherichia coli

In a circular bioeconomy, the one-way conversion of petroleum to chemicals and CO 2 is replaced with processes that reduce CO 2 to energy carriers and useful materials that are returned to CO 2 upon combustion. A circular bioeconomy that relies on photosynthesis to generate sugars as the chief energy carrier and precursor to chemical building blocks has yet to overcome many recalcitrant aspects of plant-based photosynthesis, namely, high feedstock costs, arable land scarcity, food competition, and fertilizer overuse. Acetate is a potential sustainable energy carrier because it can be produced from CO 2 either electrocatalytically or by acetogens via the Wood-Ljungdahl pathway. Here, in this work, we conducted a metabolic engineering study of Escherichia coli 's ability to convert acetate into dodecanol as a model oleochemical product. We performed techno-economic and life cycle analyses to determine break-even points with alternative fossil fuel-based strategies and identified critical process performance parameters for supporting an industrial acetate-based bioprocess. These analyses showed that oleochemical yield is the primary driver of minimum oleochemical selling price and carbon intensity. Therefore, to increase yield on acetate, we deleted the aceBAK operon, which facilitates funneling of acetate into biomass instead of product. We performed additional strain engineering to increase flux towards dodecanol and increase acetate uptake. Finally, we demonstrated increased yield in controlled bioreactors, improving from 13% of the maximum theoretical yield to 37%. Rigorous uncertainty analyses assuming a range of market conditions and future technological performances resulted in 88% and 37% of simulated scenarios having lower carbon intensities than fossil fuel-based routes and lower minimum selling prices than the market price.

Acetate↗
DOE OSTI2021

Slope-Aspect Induced Climate Differences Influence How Water Is Exchanged Between the Land and Atmosphere

Cross-slope climate differences in the midlatitudes are ecologically important, and impact vegetation-mediated water balance between the earth surface and the atmosphere. We made high-resolution in situ observations of air temperature, relative humidity, soil moisture, insolation, and sap velocity observations on 14 Pacific madrone trees (Arbutus menziesii) spanning adjacent north and south slopes at the University of California's Angelo Coast Range Reserve. To understand the cross-slope response of sap velocity, a proxy for transpiration, to microclimate, we modeled the sap velocity on each slope using a transpiration model driven by ambient environment and parameterized with a Markov Chain Monte Carlo parameter estimation process. The results show that trees on opposing slopes do not follow a shared pattern of physiological response to transpiration drivers. This means that the observed sap velocity differences are not due entirely to observed microclimate differences, but also due to population-level physiological differences, which indicates acclimation to inhabited microclimate. While our present data set and analytical tools do not identify mechanisms of acclimation, we speculate that differing proportions of sun-adapted and shade-adapted leaves, differences in stomatal regulation, and cross-slope root zone moisture differences could explain some of the observed and modeled differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Parameters of the Lightning Attachment Processes in a Negative Cloud-To-Ground Stroke Observed on a Microsecond Timescale

We present time-correlated ultra-high-speed video camera and electromagnetic field measurements of the attachment processes in a natural negative cloud-to-ground stroke. The video camera frame exposure time and pixel resolution were 740 ns and 0.91 m/pixel, respectively. The common streamer zone (CSZ) was first observed 2.52 µs preceding the first frame showing the return stroke (RS) in progress, when the upward and downward leader-tips were 9.8 m apart. In the next frame, the two leaders were observed to have propagated toward each other within the CSZ, with their tips being 0.91 m apart. Our observations show with unprecedented precision/clarity that (a) the slow front in the field waveform is associated with the CSZ, and (b) the “proper” start of the RS is marked by the onset of the fast transition in the field waveform which occurs at the completion of the attachment processes (when the upward and downward leaders have merged).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Future Intensity‐Duration‐Frequency Curves of Extreme Precipitation in the Midwest United States From Convection‐Permitting Modeling

Abstract During the last four decades, global warming has statistically significant intensified extreme precipitation events in the Midwestern United States (defined here as the region covering Illinois, Indiana, Ohio, and Kentucky), leading to increased risks to human life, property, and infrastructure. To enable climate change adaptation and resilience across various economic and social sectors in this region, updated information about future climate changes, specifically at finer spatial scales, is essential. Leveraging a new 150‐year dynamical downscaling data set at convection‐permitting resolution, this study introduces a framework to construct the projected future intensity‐duration‐frequency (IDF) curves of heavy precipitation, which are prominent tools for infrastructure design and water resources management. This framework generates IDF curves at both sub‐daily and multi‐day duration utilizing hourly in situ observations as well as quantile‐based statistical techniques in bias‐correction and return levels selection. The assumption of non‐stationarity in the distribution parameter fitting process is also implemented in this workflow. Compared to historical IDF curves for 1980–2022, future projected IDF curves for 2058–2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicate an average intensity increase of approximately 15% and 25%, respectively, across 74 stations, considering both annual and seasonal timescales. Future projections suggest that extreme precipitation events may become more severe across six investigated return periods, with longer return periods showing a greater increase. The frequency of future extreme precipitation events in the Midwest region is also projected to double. Furthermore, current results reveal spatial heterogeneity of future trends across stations owing to the high‐resolution input data set. Plain Language Summary This study investigates the evolving nature of extreme precipitation events in the Midwestern United States under a changing climate. By leveraging a high‐resolution dynamical downscaling data set, we construct projected intensity‐duration‐frequency (IDF) curves for future extreme rainfall events. These curves serve as vital tools for infrastructure planning and water resource management. Our analysis reveals a significant increase in both the intensity and frequency of extreme precipitation events in the region. Future projected IDF curves for the late century indicate an average intensity increase of approximately 15%–25% compared to historical values. Moreover, the frequency of such events is expected to double. Spatial heterogeneity in future trends is observed across different stations within the Midwest, highlighting the importance of high‐resolution modeling in capturing localized climate variability. These findings underscore the urgent need for climate adaptation strategies to mitigate the increasing risks associated with extreme precipitation events in the region. Key Points This study introduces a workflow to construct future intensity‐duration‐frequency (IDF) curves over the Midwest United States using a new convection‐permitting modeling data set The current IDF construction workflow reproduces well the historical observed IDF 30 curves in summer months with median relative errors of 2.4% among 74 stations and 6 investigated durations The projected IDF curves show diverse future trends of extreme precipitation across stations, with intensity increases of approximately 15% and 25% under RCP4.5 and RCP8.5 climate scenarios, respectively, and a doubling of frequency on average

Nguyen, Trung↗
DOE OSTI2024

Source size of x rays from self-modulated laser wakefield accelerators

A comparative study of x-ray sources generated with different mechanisms from self-modulated laser wakefield acceleration (SM-LWFA) electrons was performed to compare the source size or spatial resolution for use in high energy density science applications. We examine the source size of betatron, inverse Compton scattering, and bremsstrahlung radiation with a Fresnel diffraction based formalism and a modified x-ray ray tracing model. We observe the dependence of source size on the radiation generation process, laser parameters, and compare to what is possible in other regimes of LWFA, as well as current methods. This information is significant as we begin to explore the use of light sources driven by SM-LWFA for use as a diagnostic at large-scale laser facilities where blowout regime LWFA is not possible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Critical parameters in the faculty application process: A data-driven analysis

We report the process of applying for science and engineering faculty positions requires a significant time investment for both the applicant and hiring committees. Applicants face the daunting task of sifting through a seemingly endless amount of information related to crafting their application packages in preparation for a review process that is inherently highly subjective. Furthermore, while scientific supervisors are often the most valuable resource during this stage of career development, many years may have passed since they went through this process themselves, and they may not have experience with recent developments in the application process. Because expectations and job responsibilities of new faculty members are rapidly evolving, certain guidelines are often not clearly specified, and it is therefore becoming difficult for applicants to most effectively prepare their application documents. Without access to adequate information and assistance, early-career researchers in particular can be placed at a significant disadvantage in the hiring process. Several recent articles can help prospective applicants in materials science and engineering land a faculty position,1,2,3 but there is nevertheless a need for clarification on expectations for different aspects of the faculty application materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing rutile solid-phase crystallization of atomically mixed Mn-alloyed TiO 2 coatings through XANES analysis

Phase transformation via dopant introduction is an emerging strategy for tuning the electronic and catalytic properties of oxides. However, developing a general theory of ternary alloys and their microstructure evolution remains challenging due to the knowledge gaps in how point defects such as dopants lead to the formation of complex or metastable phases. We investigate the influence of Mn concentration and annealing temperature on the microstructure evolution of amorphous Mn-alloyed TiO 2 synthesized via Atomic Layer Deposition. In conclusion, our findings reveal a new crystallization pathway resulting in a direct amorphous TiO 2 to rutile transformation without an intermediate anatase phase and our multi-parameter thermal processing conditions show potential for AI-assisted data acquisition and analysis for studying complex oxide coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2024

xesn: Echo state networks powered by Xarray and Dask

Xesn is a Python package that allows scientists to easily design Echo State Networks (ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture introduced by Jaeger (2001) that are part of a class of techniques termed Reservoir Computing. One defining characteristic of these techniques is that all internal weights are determined by a handful of global, scalar parameters, thereby avoiding problems during backpropagation and reducing training time significantly. Because this architecture is conceptually simple, many scientists implement ESNs from scratch, leading to questions about computational performance. Xesn offers a straightforward, standard implementation of ESNs that operates efficiently on CPU and GPU hardware. The package leverages optimization tools to automate the parameter selection process, so that scientists can reduce the time finding a good architecture and focus on using ESNs for their domain application. Importantly, the package flexibly handles forecasting tasks for out-of-core, multi-dimensional datasets, eliminating the need to write parallel programming code. Xesn was initially developed to handle the problem of forecasting weather dynamics, and so it integrates naturally with Python packages that have become familiar to weather and climate scientists such as Xarray (Hoyer & Hamman, 2017). However, the software is ultimately general enough to be utilized in other domains where ESNs have been useful, such as in signal processing (Jaeger & Haas, 2004).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Thermal Instability in the Manufacturing of Wind Turbine Blade Spar Caps

As wind turbine blades continue to scale in length and total mass, the acceptability of traditional approaches for the engineering of processes to build these products has reached a limit. The continued need to reduce the levelized cost of energy (LCOE) drives manufacturing cycle times lower and the net mass of critical components challenges even the most experienced fabricators to meet the quality requirements for safe operating performance over the 25-year design life of the blade. In trying to reduce cycle time for key components of wind turbines, manufacturers discovered occasional buckling of fibers in wind turbine blade spar caps. The cause of the buckling was unknown. The goal of this project was to show that a comprehensive simulation, which considered all of the physics of the VARTM process, could identify the cause of the fiber buckling in spar caps that has been observed during the manufacturing process. Ultimately, the simulation determined the manufacturing process and parameters could lead to significant compressive stresses in the fibers eventually causing buckling. Simulation results suggest that the stress introduced from friction is the largest source of compressive stress in the fibers, the stress from the weight of gravity is significant but secondary, and the compressive stress from cure shrinkage does not play a significant role in the buckling of fibers. This report provides details of the testing and simulation methodology used to identify the cause of the fiber buckling.

17 WIND ENERGY↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Hydropower Black Start: A Guidebook for Retrofitting Grid Dependent Hydropower

Not all United States (US) hydropower plants were designed to provide black start, but they are increasingly needed to uphold resilience in the evolving electric grid. This guidance is designed to help understand the minimal retrofits required for grid dependent hydropower (GDH) plants behind the point of interconnection (POI). For distribution connected hydropower plants or those with dedicated cranking paths, such upgrades can be sufficient for the plant to provide black start. For others, more coordination with the transmission system operator will be needed. This guidebook answers a number of questions relevant to retrofitting hydropower plants with black start capabilities. For example, the guidebook answers: • How flexible do the wicket gate controls need to be? • Who needs to do hydro governor model validation, why, and how? • How robust and flexible do the excitation and AVR controls need to be? • What protection settings need to be adjusted? • What relay(s) will need to be bypassed or overridden and at what risk? • What is the electrical energy demand of the station load or auxiliary power systems? • What should the strategy to energize transformer(s) along cranking path to address inrush currents be? • How should the critical load restoration be sequenced? In addition to outlining the specifications that hydropower plants need to meet for each component to be able to perform black start, this guidebook provides a set of case studies for specific upgrades needed at actual plants. Between the case studies of plants that have already performed black start retrofits and the examples of how this guidebook can be applied to scope future retrofits, five key themes have been identified for retrofit needs. 1. Protection needs “black start” mode: hydropower plants that are not designed with black start capabilities will have protections that prevent them from interconnecting to a “dead bus.” These protections will need to be overridden in every retrofit case and a separate black start mode should be established so that operators can safely switch between black start and grid connected modes, minimizing the risk to the plant. 2. Wicket gates need modern controls: digital governors accelerate the parameter tuning process and gate position sensors improve controllability, so plants with mechanical governors should be upgraded. Furthermore, a black start and islanding mode should be established for controls to maximize plant performance. 3. Robust excitation support: the DC system or excitation generator needs to be reliable enough to form and sustain the rotor electromagnetic field. These systems are typically undersized in plants that were not designed for black start, so they will need to be upgraded. 4. Turbine-governor model validation and operator training: validation of a standard hydro governor model is needed to characterize the dynamic response (i.e., inertial and primary frequency response) of the GDH. This is required for control development and old hydropower plants often have outdated or incorrect models. Operator training is also typically required to ensure the hardware retrofits are utilized correctly during the black start process. 5. Transformer and cranking path energization: any upgradation and control adjustment in front of the POI will depend upon the existing interconnection. Coordination with the transmission or distribution operator may be required.

13 HYDRO ENERGY↗
DOE OSTI2026

Qualitative Risk Assessment of Legacy Wells within the Estimated Prairie State Generating Company Area of Review

This report details the digitization of a legacy wellbore database, including data processing assumptions, parameter estimation, and risk assessment methodology. The database, comprising 6,454 documents, was provided by ISGS. It includes valuable data from the Prairie State Generating Company (PSGC) and One Earth Energy (OEE) sites of the CarbonSAFE Phase III – Illinois Storage Corridor project. The report focuses on wells within a 15-mile radius from the Lively Grove #1 (LG#1) well at PSGC site, evaluating subsurface conditions and potential risks. A total of 4,386 wellbores within 15 miles of the LG#1 well were filtered based on depth and formation codes. LG#1 is the stratigraphic well at the PSGC site drilled in 2021. Ninety-four (94) wells penetrating the Maquoketa Shale Group (the primary confining unit) within the estimated area-of-review (AoR) for the PSGC site were evaluated using a qualitative risk assessment (QRA) methodology. The QRA developed by Arbad et al. 2022 focuses on legacy wells within the AoR and categorizes them based on well construction details. The QRA identifies wells that need immediate attention by categorizing them based on penetration depth and protection. Wells within the AoR were categorized into nine groups based on penetrations and protections. These categories range from Type 1 wells, with no documentation, to Type 9 wells, which do not penetrate the primary confining unit or storage reservoir (unit). Well accessibility within the AoR varies based on well status, including Dry & Abandoned (DA), Plugged & Abandoned (PA), Injection (INJ), Oil/Gas Producing (PROD), and Observation (Obs) wells. Accessibility levels were determined by well construction, with DA wells being the least accessible and Observation wells the most accessible, impacting gas leakage detection possibilities. Remedial action priority of wells decreases from Type 1 to Type 9 wells. Type 1 to Type 6 wells with status DA and PA require immediate attention, while Type 7 and Type 8 wells are low priority. A risk matrix used to prioritize corrective actions for legacy wells is proposed to categorize wells within an AoR based on penetrations, protections, and accessibility. The methodology involves data acquisition, well categorization into nine types, and determining CO 2 leakage pathways using well schematics and geospatial mapping. This approach is particularly useful for managing the integrity of legacy wells throughout the lifecycle of a Carbon Capture and Storage (CCS) project. A qualitative risk assessment of 94 wells within the AoR of the PSGC site identified 54 wells with high priority for corrective action due to penetration of the primary containment seal. The assessment utilizes color-coded maps to categorize well types and prioritize corrective actions, providing a comprehensive analysis. Schematics of wells penetrating the primary confining unit were drawn, and leakage pathways were identified. Details of all wells penetrating the confining zone are provided in the appendix, including information on well types, plugging, and casing status.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Epitaxial Growth of Ga2O3: A Review

Beta-phase gallium oxide (β-Ga2O3) is a cutting-edge ultrawide bandgap (UWBG) semiconductor, featuring a bandgap energy of around 4.8 eV and a highly critical electric field strength of about 8 MV/cm. These properties make it highly suitable for next-generation power electronics and deep ultraviolet optoelectronics. Key advantages of β-Ga2O3 include the availability of large-size single-crystal bulk native substrates produced from melt and the precise control of n-type doping during both bulk growth and thin-film epitaxy. A comprehensive understanding of the fundamental growth processes, control parameters, and underlying mechanisms is essential to enable scalable manufacturing of high-performance epitaxial structures. This review highlights recent advancements in the epitaxial growth of β-Ga2O3 through various techniques, including Molecular Beam Epitaxy (MBE), Metal-Organic Chemical Vapor Deposition (MOCVD), Hydride Vapor Phase Epitaxy (HVPE), Mist Chemical Vapor Deposition (Mist CVD), Pulsed Laser Deposition (PLD), and Low-Pressure Chemical Vapor Deposition (LPCVD). This review concentrates on the progress of Ga2O3 growth in achieving high growth rates, low defect densities, excellent crystalline quality, and high carrier mobilities through different approaches. It aims to advance the development of device-grade epitaxial Ga2O3 thin films and serves as a crucial resource for researchers and engineers focused on UWBG semiconductors and the future of power electronics.

Chemistry↗
DOE OSTI2022

Global simulations of monoterpene-derived peroxy radical fates and the distributions of highly oxygenated organic molecules (HOMs) and accretion products

Abstract. We evaluate monoterpene-derived peroxy radical (MT-RO2) unimolecular autoxidation and self- and cross-reactions with other RO2 species in the GEOS-Chem global chemical transport model. The formation of associated highly oxygenated organic molecules (HOMs) and accretion products are tracked in competition with other bimolecular reactions. Autoxidation is the dominant fate up to 6–8 km for first-generation MT-RO2, which can undergo unimolecular H shifts. Reaction with NO can be a more common fate for H-shift rate constants < 0.1 s−1 or at altitudes higher than 8 km due to the imposed Arrhenius temperature dependence of unimolecular H shifts. For MT-derived HOM-RO2, generated by multistep autoxidation of first-generation MT-RO2, reaction with other RO2 species is predicted to be the major fate throughout most of the boreal and tropical forest regions, whereas reaction with NO dominates in the temperate and subtropical forests of the Northern Hemisphere. The newly added reactions result in an approximate 4 % global average decrease in HO2 and RO2, mainly due to faster self-/cross-reactions of MT-RO2, but the impact upon HO2, OH, and NOx abundances is only important in the planetary boundary layer (PBL) over portions of tropical forests. Predicted HOM concentrations in MT-rich regions and seasons can exceed total organic aerosol predicted by the standard version of the GEOS-Chem model depending on the parameters used. Comparisons to observations reveal that large uncertainties remain for key reaction parameters and processes, especially with respect to the photochemical lifetime and volatility of HOMs as well as the rates and branching of associated RO2 accretion products. Further observations and laboratory studies related to MT-RO2-derived HOMs and gas-phase RO2 accretion product formation kinetics – especially their atmospheric fate, such as gas–particle partitioning, multiphase chemistry, and net secondary organic aerosol formation – are needed.

54 ENVIRONMENTAL SCIENCES↗