Operando monitoring of single-particle kinetic state-of-charge heterogeneities and cracking in high-
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Merryweather, Alice J.↗
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Results for “Heterogeneity”
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Bifunctional hydroformylation on heterogeneous Rh-WOx pair site catalysts
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Science & Technology - Other Topics↗
High-resolution mapping of spatial heterogeneity in ice wedge polygon geomorphology near Prudhoe Bay, Alaska
It is well known that microtopography associated with ice wedge polygons drives pronounced, meter-scale spatial gradients in hydrologic and ecological processes on the tundra. However, highresolution maps of polygonal geomorphology are rarely available, due to the complexity and subtlety of ice wedge polygon relief at landscape scales. Here we present a sub-meter resolution map of >106 discrete ice wedge polygons across a ~1200 km2 landscape, delineated within a lidar-derived digital elevation model. The delineation procedure relies on a convolutional neural network paired with a set of common image processing operations and permits explicit measurement of relative elevation at the center of each ice wedge polygon. The resulting map visualizes meter- to kilometer-scale spatial gradients in polygonal geomorphology across an extensive landscape with unprecedented detail. This high-resolution inventory of polygonal geomorphology provides rich spatial context for extrapolating observations of environmental processes across the landscape. The map also represents an extensive baseline dataset for quantifying contemporary land surface deformation (i.e., thermokarst) at the survey area, through future topographic surveys.
54 ENVIRONMENTAL SCIENCES↗
Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction
Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.
47 OTHER INSTRUMENTATION↗
Heterogeneous estimations of non-pharmaceutical mitigation behavior during the COVID-19 pandemic
The COVID-19 pandemic highlighted the importance of human behavior in mitigating the spread of disease. Nonetheless, human behavior is often overlooked in models of disease spread, particularly by underutilizing real-world data. We address this by estimating probabilities that individuals engage in behaviors that influence SARS-CoV-2 transmission risk during the COVID-19 pandemic, between September 2020 and June 2022. These behaviors include wearing a mask, using public transportation, spending time with others, avoiding contact with others, and going to work. Our estimates account for the age and sex of individuals and are generated for every county in the United States. We utilized multiple open-source datasets and United States Census data to produce these estimates. Multiple datasets were used for validation, showing our estimates demonstrated comparable accuracy and robustness. Our estimates aid in understanding human behavior dynamics during the COVID-19 pandemic and could be used to inform monthly or longer-term behavior in simulations of COVID-19. Moreover, the methods presented can be applied to other behaviors and features for future simulations of infectious disease.
97 MATHEMATICS AND COMPUTING↗
The influence of δ-(Al,Fe)OOH on seismic heterogeneities in Earth’s lower mantle
The high-pressure phases of oxyhydroxides (δ-AlOOH, ε-FeOOH, and their solid solution), candidate components of subducted slabs, have wide stability fields, thus potentially influencing volatile circulation and dynamics in the Earth’s lower mantle. Here, we report the elastic wave velocities of δ-(Al,Fe)OOH (Fe/(Al + Fe) = 0.13, δ-Fe13) to 79 GPa, determined by nuclear resonant inelastic X-ray scattering. At pressures below 20 GPa, a softening of the phonon spectra is observed. With increasing pressure up to the Fe 3+ spin crossover (~ 45 GPa), the Debye sound velocity (vD) increases. At higher pressures, the low spin δ-Fe 13 is characterized by a pressure-invariant vD. Using the equation of state for the same sample, the shear-, compressional-, and bulk-velocities (v S , v P , and v Φ ) are calculated and extrapolated to deep mantle conditions. The obtained velocity data show that δ-(Al,Fe)OOH may cause low-v Φ and low-v P anomalies in the shallow lower mantle. At deeper depths, we find that this hydrous phase reproduces the anti-correlation between v S and v Φ reported for the large low seismic velocity provinces, thus serving as a potential seismic signature of hydrous circulation in the lower mantle.
58 GEOSCIENCES↗
Efficient and assured reinforcement learning-based building HVAC control with heterogeneous expert-guided training
Abstract Building heating, ventilation, and air conditioning (HVAC) systems account for nearly half of building energy consumption and $$20\%$$ of total energy consumption in the US. Their operation is also crucial for ensuring the physical and mental health of building occupants. Compared with traditional model-based HVAC control methods, the recent model-free deep reinforcement learning (DRL) based methods have shown good performance while do not require the development of detailed and costly physical models. However, these model-free DRL approaches often suffer from long training time to reach a good performance, which is a major obstacle for their practical deployment. In this work, we present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the knowledge from domain experts in various forms . Specifically, the algorithm stages include learning expert functions from existing abstract physical models and from historical data via offline reinforcement learning, integrating the expert functions with rule-based guidelines, conducting training guided by the integrated expert function and performing policy initialization from distilled expert function. Moreover, to ensure that the learned DRL-based HVAC controller can effectively keep room temperature within the comfortable range for occupants, we design a runtime shielding framework to reduce the temperature violation rate and incorporate the learned controller into it. Experimental results demonstrate up to 8.8 X speedup in DRL training from our approach over previous methods, with low temperature violation rate.
Xu, Shichao↗
Modeling the impact of structure and coverage on the reactivity of realistic heterogeneous catalysts
Adsorbates often cover the surfaces of catalysts densely as they carry out reactions, dynamically altering their structure and reactivity. Understanding adsorbate-induced phenomena and harnessing them in our broader quest for improved catalysts is a substantial challenge that is only beginning to be addressed. Here, in this work, we chart a path toward a deeper understanding of such phenomena by focusing on emerging in silico modeling methodologies, which will increasingly incorporate machine learning techniques. We first examine how adsorption on catalyst surfaces can lead to local and even global structural changes spanning entire nanoparticles, and how this affects their reactivity. We then evaluate current efforts and the remaining challenges in developing robust and predictive simulations for modeling such behavior. Last, we provide our perspectives in four critical areas—integration of artificial intelligence, building robust catalysis informatics infrastructure, synergism with experimental characterization, and adaptive modeling frameworks—that we believe can help surmount the remaining challenges in rationally designing catalysts in light of these complex phenomena.
catalytic mechanisms↗
Electron leakage through heterogeneous LiF on lithium–metal battery anodes
The solid–electrolyte interphase (SEI) that forms on lithium ion battery (LIB) anodes prevents degradation-causing transfer of electrons to the electrolyte. Grain boundaries (GBs) between different SEI components, like LiF, have been suggested to accelerate Li+ transport. However, using the non-equilibrium Green's function technique with density functional theory (NEGF-DFT), we find that GBs enhance electron tunneling in thin LiF films by 1–2 orders of magnitude, depending on the bias. Extrapolating to thicker films using the Wentzel–Kramers–Brillouin (WKB) method emphasizes that safer batteries require passivation of GBs in the SEI.
25 ENERGY STORAGE↗
CO 2 hydrogenation over heterogeneous catalysts at atmospheric pressure: from electronic properties to product selectivity
The fundamental insights into the relationships among the electronic properties of active metals, the binding strengths of key intermediates, and the CO 2 hydrogenation selectivity are provided.
Wang, Yaning↗
Double Membrane Formation in Heterogeneous Vesicles
Lipids are capable of forming a variety of structures, including multi-lamellar vesicles. Layered lipid membranes are found in cell organelles, such as autophagosomes and mitochondria. Here, we present a mechanism for the formation of a double-walled vesicle (i.e., two lipid bilayers) from a unilamellar vesicle through the partitioning and phase separation of a small molecule. Using molecular dynamics simulations, we show that double membrane formation proceeds via a nucleation and growth process – i.e., after a critical concentration of the small molecules, a patch of double membrane nucleates and grows to cover the entire vesicle. In this paper, we discuss the implications of this mechanism and theoretical approaches for understanding the evolution and formation of double membranes.
59 BASIC BIOLOGICAL SCIENCES↗
Quantification of heterogeneous, irreversible lithium plating in extreme fast charging of lithium-ion batteries
Realization of extreme fast charging (XFC, ≤15 minutes) of lithium-ion batteries is imperative for the widespread adoption of electric vehicles. However, dramatic capacity fading is associated with XFC, limiting its implementation. To quantitatively elucidate the effects of irreversible lithium plating and other degradation mechanisms on the cell capacity, it is important to understand the links between lithium plating and cell degradation at both the local and global (over the full cell) scales. Here, we study the nature of local lithium plating after hundreds of XFC cycles (charging C-rates ranging from 4C to 9C) in industrially-relevant pouch cells using spatially resolved X-ray diffraction. Our results reveal a spatial correlation at the mm scale between irreversible lithium plating on the anode, inactive lithiated graphite phases, and local state-of-charge of the cathode. In regions of plated lithium, additional lithium is locally and irreversibly trapped as lithiated graphite, contributing to the loss of lithium inventory (LLI) and to a local loss of active anode material. The total LLI in the cell from irreversibly plated lithium is linearly correlated to the capacity loss in the batteries after XFC cycling, with a non-zero offset originating from other parasitic side reactions. Finally, at the global (cell) scale, LLI drives the capacity fade, rather than electrode degradation. We anticipate that the understanding of lithium plating and other degradation mechanisms during XFC gained in this work will help lead to new approaches towards designing high-rate batteries in which irreversible lithium plating is minimized.
25 ENERGY STORAGE↗
IR linewidth and intensity amplifications of nitrile vibrations report nuclear-electronic couplings and associated structural heterogeneity in radical anions
Quantification of the intensity and linewidth of the ν (CN) IR band in a series of neutral and anionic nitrile-functionalized oligophenylenes reveals that the CN vibration is coupled to nuclear and electronic structural changes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Why halides enhance heterogeneous metal ion charge transfer reactions
Halide-induced rate enhancements are correlated with the desorption barriers of aqueous metal–anion complexes on electrodes, which can guide electrode and electrolyte selection to enhance redox kinetics of metal ion charge transfer reactions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Multi-scale investigation of heterogeneous swift heavy ion tracks in stannate pyrochlore
Er 2 Sn 2 O 7 pyrochlore was irradiated with swift heavy Au ions (2.2 GeV), and the induced structural modifications were systematically examined using complementary characterization techniques including transmission electron microscopy (TEM), X-ray diffraction (XRD), and neutron total scattering with pair distribution function (PDF) analysis. Each technique probes different aspects and length scales of the transformed material regions. TEM revealed a core–shell ion track structure—an amorphous core surrounded by a disordered, anion-deficient fluorite shell—which was confirmed by XRD. Neutron total scattering, with sensitivity to the oxygen sublattice, provided relative fractions of amorphous and disordered fluorite phases and confirmed the presence of a defective pyrochlore phase, which largely maintains its structural ordering but is clearly distinct from the pristine pyrochlore matrix. This defect-rich pyrochlore phase forms a halo extending radially beyond the well-characterized core–shell track morphology observed in electron micrographs. Despite their differing long-range periodicity, the short-range structures of the amorphous, disordered, and defective pyrochlore phases are all modeled well with a weberite-type configuration. Evolution of the phase fractions with increasing ion fluence was examined to ascertain the phase-to-phase pathways that occur during primary and secondary ion impact. Furthermore, this approach extends knowledge about the multi-scale response of stannate pyrochlores to swift heavy ion irradiation in the electronic energy loss regime and improves existing track-overlap models.
36 MATERIALS SCIENCE↗
Trends and descriptors of heterogeneous hydroformylation activity and selectivity of RhM 3 (M = Fe, Co, Ni, Cu and Zn) catalysts
Here monometallic Rh/MCM-41 and bimetallic RhM 3 /MCM-41 (M = Fe, Co, Ni, Cu, or Zn) catalysts are synthesized and tested for vapor-phase ethylene hydroformylation reaction. Co is found to exhibit a significant promotion effect on the selectivity of hydroformylation to C 3 oxygenates, followed by Fe and Cu, with Ni and Zn showing a negative effect. DFT calculations reveal that the addition of a secondary metal can provide a new type of site, being able to selectively tune the binding energies of reaction intermediates, and thus lead to different catalytic performances.
30 DIRECT ENERGY CONVERSION↗
The effect of dynamically heterogeneous interphases on the particle dynamics of polymer nanocomposites
The entanglements of dynamically asymmetric polymer layers influence relaxations of nanoparticles in polymer nanocomposites.
Wu, Di↗