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Nimmo, Bill (Ed.)This manuscript reports on the combustion of powdered iron, for the purpose of utilizing it as an environmentally friendly circular energy carrier. The conducted research investigated the spectral emissivity and temperature of iron particles, burned either individually or in groups. Combustion experiments were conducted under high heating rates in an externally-heated drop tube furnace. The pressure was atmospheric and the axial temperature was nearly-constant at ~1350 K. The oxidizer gas contained 15-100% oxygen in nitrogen diluent. Iron particles were sieve-classified in the 44-53 µm range. Results showed that, depending on the oxygen concentration, and consequently the particle temperature, the average spectral emissivities of single burning particles varied between 0.18 and 0.46, in the 600-1000 nm wavelength range. Corresponding temperatures of single particles varied between 2300 K and 2800 K, increasing with increasing oxygen concentration in the gas. In the case of groups of iron particles burning in air at different particle number densities, average spectral emissivities were found to be in the range of 0.42-0.45, with the upper value associated with denser particle clouds. Corresponding peak temperatures of particle burning in groups were found to be in the range of 2160 K to 2100 K, with the lower value attributed to denser particle clouds.more » « lessFree, publicly-accessible full text available November 1, 2025
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Abstract Biodegradable plastics, perceived as ‘environmentally friendly’ materials, may end up in natural environments. This impact is often overlooked in the literature due to a lack of assessment methods. This study develops an integrated life cycle impact assessment methodology to assess the climate-change and aquatic-ecotoxicity impacts of biodegradable microplastics in freshwater ecosystems. Our results reveal that highly biodegradable microplastics have lower aquatic ecotoxicity but higher greenhouse gas (GHG) emissions. The extent of burden shifting depends on microplastic size and density. Plastic biodegradation in natural environments can result in higher GHG emissions than biodegradation in engineered end of life (for example, anaerobic digestion), contributing substantially to the life cycle GHG emissions of biodegradable plastics (excluding the use phase). A sensitivity analysis identified critical biodegradation rates for different plastic sizes that result in maximum GHG emissions. This work advances understanding of the environmental impacts of biodegradable plastics, providing an approach for the assessment and design of future plastics.
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Free, publicly-accessible full text available November 1, 2025
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Free, publicly-accessible full text available September 1, 2025
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This work aims to generate natural and diverse group motions of multiple humans from textual descriptions. While singleperson text-to-motion generation is extensively studied, it remains challenging to synthesize motions for more than one or two subjects from in-the-wild prompts, mainly due to the lack of available datasets. In this work, we curate human pose and motion datasets by estimating pose information from large-scale image and video datasets. Our models use a transformer-based diffusion framework that accommodates multiple datasets with any number of subjects or frames. Experiments explore both generation of multi-person static poses and generation of multiperson motion sequences. To our knowledge, our method is the first to generate multi-subject motion sequences with high diversity and fidelity from a large variety of textual prompts.more » « lessFree, publicly-accessible full text available October 4, 2025
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ABSTRACT We present a novel approach to extracting dwarf galaxies from photometric data to measure their average halo mass profile with weak lensing. We characterize their stellar mass and redshift distributions with a spectroscopic calibration sample. By combining the ${\sim} 5000\,\mathrm{deg}^2$ multiband photometry from the Dark Energy Survey and redshifts from the Satellites Around Galactic Analogs Survey with an unsupervised machine learning method, we select a low-mass galaxy sample spanning redshifts $z\lt 0.3$ and divide it into three mass bins. From low to high median mass, the bins contain [146 420, 330 146, 275 028] galaxies and have median stellar masses of $\log _{10}(M_*/\text{M}_\odot)=\left[8.52\substack{+0.57 -0.76},\, 9.02\substack{+0.50 -0.64},\, 9.49\substack{+0.50 -0.58}\right]$ . We measure the stacked excess surface mass density profiles, $\Delta \Sigma (R)$, of these galaxies using galaxy–galaxy lensing with a signal-to-noise ratio of [14, 23, 28]. Through a simulation-based forward-modelling approach, we fit the measurements to constrain the stellar-to-halo mass relation and find the median halo mass of these samples to be $\log _{10}(M_{\rm halo}/\text{M}_\odot)$ = [$10.67\substack{+0.2 -0.4}$, $11.01\substack{+0.14 -0.27}$, $11.40\substack{+0.08 -0.15}$]. The cold dark matter profiles are consistent with NFW (Navarro, Frenk, and White) profiles over scales ${\lesssim} 0.15 \, {h}^{-1}$ Mpc. We find that ${\sim} 20$ per cent of the dwarf galaxy sample are satellites. This is the first measurement of the halo profiles and masses of such a comprehensive, low-mass galaxy sample. The techniques presented here pave the way for extracting and analysing even lower mass dwarf galaxies and for more finely splitting galaxies by their properties with future photometric and spectroscopic survey data.
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Abstract We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW’s measured halo mass and concentration, (ii) accrete a Large Magellanic Cloud (LMC)-like (≈1011
M ⊙) subhalo within the last 2 Gyr on a realistic orbit, placing them near 50 kpc from the host center atz ≈ 0, and (iii) undergo a >1:5 sub-to-host halo mass ratio merger with a Gaia–Sausage–Enceladus (GSE)-like system at early times (0.67 <z < 3). Hosts satisfying these LMC and GSE constraints constitute <1% of all halos in the MW’s mass range, and their total masses grow rapidly at late times due to LMC analog accretion. Compared to hosts of a similar final halo mass that are not selected to include LMC and GSE analogs, Milky Way-est hosts contain 22% more subhalos with present-day virial masses above 108M ⊙throughout the virial radius, on average. This enhancement reaches ≈80% in the inner 100 kpc and is largely, if not entirely, due to LMC-associated subhalos. These systems also induce spatial anisotropy in Milky Way-est subhalo populations, with ≈60% of the total subhalo population within 100 kpc found in the current direction of the LMC. Meanwhile, we find that GSE-associated subhalos do not significantly contribute to present-day Milky Way-est subhalo populations. These results provide context for our Galaxy’s dark matter structure and subhalo population and will help interpret a range of measurements that are currently only possible in the MW. -
Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing the decarbonization, environmental, and economic implications of these technologies and strategies is critical to identifying pathways to a more sustainable industrial future. This study reviews recent advancements and integration of systems analysis models, including process analysis, material flow analysis, life cycle assessment, techno-economic analysis, and machine learning. These models are categorized based on analytical methods and application scales (i.e., micro-, meso-, and macroscale) for promising decarbonization technologies (e.g., carbon capture, storage, and utilization, biomass feedstock, and electrification) and circular economy strategies. Incorporating forward-looking, data-driven approaches into existing models allows for optimizing complex industrial systems and assessing future impacts. Although advances in industrial ecology–, economic-, and planetary boundary–based modeling support a more holistic systems-level assessment, more effects are needed to consider impacts on ecosystems. Effective applications of these advanced, integrated models require cross-disciplinary collaborations across chemical engineering, industrial ecology, and economics.
Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering , Volume 15 is June 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Free, publicly-accessible full text available June 7, 2025 -
Abstract We present Data Release 3 (DR3) of the Satellites Around Galactic Analogs (SAGA) Survey, a spectroscopic survey characterizing satellite galaxies around Milky Way (MW)-mass galaxies. The SAGA Survey DR3 includes 378 satellites identified across 101 MW-mass systems in the distance range of 25–40.75 Mpc, and an accompanying redshift catalog of background galaxies (including about 46,000 taken by SAGA) in the SAGA footprint of 84.7 deg2. The number of confirmed satellites per system ranges from zero to 13, in the stellar mass range of 106−10
M ⊙. Based on a detailed completeness model, this sample accounts for 94% of the true satellite population down toM ⋆= 107.5M ⊙. We find that the mass of the most massive satellite in SAGA systems is the strongest predictor of satellite abundance; one-third of the SAGA systems contain LMC-mass satellites, and they tend to have more satellites than the MW. The SAGA satellite radial distribution is less concentrated than the MW's, and the SAGA quenched fraction below 108.5M ⊙is lower than the MW's, but in both cases, the MW is within 1σ of SAGA system-to-system scatter. SAGA satellites do not exhibit a clear corotating signal as has been suggested in the MW/M31 satellite systems. Although the MW differs in many respects from the typical SAGA system, these differences can be reconciled if the MW is an older, slightly less massive host with a recently accreted LMC/SMC system.