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Colloidal gels assembled from nanoparticles (NPs) are a versatile class of soft network-based materials capable of rich dynamic, mechanical, and even optical or magnetic responses to stimuli. Their behaviors are governed by dynamics of heterogeneous structures coupled across multiple length and timescales. Observable dynamics range from nanoparticle diffusion and clustering to mesoscopic cluster dynamics and interactions to localized or collective network relaxations. Understanding how these hierarchically organized processes relate to macroscopic network properties remains a broad and unresolved problem in soft matter physics. The mechanisms of gel formation can depend sensitively on the pathway and the nature of NP interactions, thus far preventing a unified theoretical bridge between nanoscopic interactions, structural evolution, and network dynamics. Indirect measurement of dynamics using light-scattering techniques provides an experimental means to quantify underlying particle and network motion. The rich dynamic behavior of NP gels warrants consideration of a broad range of models to help interpret nonlinear relaxation phenomena such as anomalous diffusion, nonergodicity, and intrinsically nonequilibrium or mechanically driven dynamics. X-ray photon correlation spectroscopy (XPCS) has emerged as a powerful tool for probing nanoscopic motion in nanoparticle gels but alone cannot resolve the full spatiotemporal spectrum of dynamics that drive gelation, aging, and network mechanical properties. While rheo-XPCS enables simultaneous probing of nanoscale and bulk mechanical responses, complementary light scattering, microscopy, or simulations can extend spatiotemporal characterization and, consequently, understanding of NP gel network physics. Implementing a modular model platform with tunable primary nanoparticle features allows systematic variation of nanoscopic characteristics that drive emergent gel responses and inform the development of theoretical models for a wide range of soft, dynamic, nanostructured materials. Gels formed from particles with unique structural proxies, such as electromagnetic coupling in plasmonic NPs, provide additional metrics for model validation and offer opportunities to develop computational methods for the efficient and accurate replication of NP gel properties. The rapid expansion of XPCS capabilities at fourth-generation light sources, combined with complementary tools and robust model systems, positions the field to move beyond descriptive fundamental studies toward the design of nanoparticle gels with adaptive and programmable behaviors. 

Abstract PSR J1928+1815 is a 10.55 ms millisecond pulsar in a 3.6 hr orbit with a massive (1.0–1.6M_⊙) companion that produces extended radio eclipses. The companion, proposed to be a stripped helium star, is undetected in optical and infrared surveys. We present deep near-infrared imaging using Keck/NIRC2 with laser guide star adaptive optics. No source is detected at the pulsar position down to a 5σlimit ofK_s ≈ 21.3. Using stripped-star atmosphere models and conservative extinction estimates, we show that any plausible helium star companion would have been detected, ruling out this interpretation. A massive white dwarf (WD) companion remains consistent with the non-detection. We consider two possible origins for the eclipses: (1) absorption in a wind driven by a young, hot WD, and (2) material ablated from the WD by the pulsar. The former can naturally arise following Case BB mass transfer, which produces ∼1.2M_⊙WDs capable of sustaining winds of $\dot{M}\gtrsim 10^{-12}$–10⁻¹³M_⊙yr⁻¹for ∼10⁴–10⁵yr, sufficient to obscure the pulsar at GHz frequencies. The latter requires efficient coupling of the pulsar’s spin-down luminosity to the companion to drive the needed mass loss, which may be difficult to achieve. If the eclipse is powered by a WD wind, the system is likely observed in a short-lived phase; alternatively, if the companion is an older WD, the origin of the eclipsing material remains unclear. The apparent uniqueness of PSR J1928+1815 is consistent with a short detectability lifetime, though formation rate estimates remain uncertain. 

Not AvailableMethane emissions from Kentucky underground coal mines were measured using near-infrared spectrometers deployed on a vehicle, an airplane, and a small uncrewed aerial system (sUAS), offering insights into the effectiveness of these methods under real-world conditions. From 2021–2022, surveys covered 14 active, 4 inactive, and 4 abandoned mines across Kentucky’s coal-producing basins. Vehicle-based surveys at 13 active mines detected methane anomalies at 9 sites with anomaly lengths spanning tens to hundreds of meters and peak emissions of 665 ± 229 kg h–1 from two Cardinal mine fans. Airborne GHGSat surveys identified anomalies at 3 sites, including a peak of 1062 ± 386 kg h–1 at Cardinal, consistent with the EPA’s Greenhouse Gas Reporting Program (GHGRP) ranges. sUAS emissions measured at Straight Creek were 65 ± 22 kg h–1 (below the GHGRP reporting threshold). Aeris vehicle-based estimates more closely matched GHGRP values than GHGSat estimates and exhibited smaller uncertainties. For example, at Cardinal Nebo, Aeris reported 228 ± 142 kg h–1 versus GHGRP’s 360 kg h–1, while GHGSat reported 716 ± 355 kg h–1. These results have important implications, where terrain and road access permit, vehicle-based methods can yield emissions estimates comparable to aircraft- and satellite-based approaches. Additionally, the higher detection rate of vehicle-based surveys suggests superior performance in identifying methane anomalies. This study highlights the spatial and temporal variability of methane emissions from underground coal mines and emphasizes the importance of integrating multiple observational strategies to improve monitoring in underrepresented regions. It also provides a transferable framework for areas where limited data availability has hindered effective methane tracking and mitigation planning. 

Dynamic covalent cross-links impart hydrogels with viscoelastic and self-healing properties, motivating applications as biomimetic cell scaffolds and injectable materials. The long bond lifetime results in complex rheological behavior including shear thickening. We hypothesized that this behavior applies broadly across dynamic covalent hydrogels and can be engineered through reaction rate constants. Thus, we synthesized multiarm poly(ethylene glycol) (PEG) hydrogels with conjugate addition, boronate ester, or terpyridine-zinc cross-links, which tune bond dissociation kinetics and hydrogel relaxation times over four orders of magnitude. All formulations exhibited shear thickening, with the onset dictated by the relaxation time. Although multiple mechanisms may underlie this behavior, chain stretching is hypothesized to contribute to shear thickening, as the cross-linking concentration remained constant under shear and networks with more defects correlated with increased shear thickening. These molecular and structural drivers of shear thickening apply across dilute dynamic covalent tetra-PEG hydrogels, clarifying their suitability for applications under shear.