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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 109 records · Page 6

The Surface-Topography Challenge: A Multi-Laboratory Benchmark Study to Advance the Characterization of Topography

Surface performance is critically influenced by topography in virtually all real-world applications. The current standard practice is to describe topography using one of a few industry-standard parameters. The most commonly reported number is Ra, the average absolute deviation of the height from the mean line (at some, not necessarily known or specified, lateral length scale). However, other parameters, particularly those that are scale-dependent, influence surface and interfacial properties; for example the local surface slope is critical for visual appearance, friction, and wear. The present Surface-Topography Challenge was launched to raise awareness for the need of a multi-scale description, but also to assess the reliability of different metrology techniques. In the resulting international collaborative effort, 153 scientists and engineers from 64 research groups and companies across 20 countries characterized statistically equivalent samples from two different surfaces: a “rough” and a “smooth” surface. The results of the 2088 measurements constitute the most comprehensive surface description ever compiled. We find wide disagreement across measurements and techniques when the lateral scale of the measurement is ignored. Consensus is established through scale-dependent parameters while removing data that violates an established resolution criterion and deviates from the majority measurements at each length scale. Our findings suggest best practices for characterizing and specifying topography. The public release of the accumulated data and presented analyses enables global reuse for further scientific investigation and benchmarking.

42 ENGINEERING↗

Mineral Scale Formation during Crossflow Reverse Osmosis at Constant Flux and Constant Transmembrane Pressure Conditions

Mineral scale formation on membrane surfaces is a significant challenge in reverse osmosis water purification. Laboratory fouling experiments are typically run such that the transmembrane pressure (TMP) is fixed, and the permeate flux decreases over time as scales accumulate on the membrane surface. However, this change in flux means that the hydrodynamic conditions at the membrane surface are continuously changing, which could affect crystallization and foulant deposition processes. Operating under constant permeate flux conditions, in contrast, is advantageous because it keeps the hydrodynamic conditions relatively consistent, making it possible to compare how membrane properties (e.g., surface chemistry) affect fouling propensity. Industrial reverse osmosis operations are not run strictly in either constant TMP or constant flux mode; while they may start at a constant TMP, feed pressure may be periodically adjusted to maintain permeate water production within a specified range. Here, the scarcity of constant permeate flux reverse osmosis scaling experiments reported in the literature frustrates efforts to compare membrane fouling processes under constant TMP and constant flux conditions. For the first time, the evolution of the fouling layer resistance was compared as a function of cumulative permeate volume per membrane area during constant TMP and constant flux reverse osmosis filtrations. Scaling experiments were conducted by challenging commercial reverse osmosis membranes with a model feed solution nearly saturated with calcium sulfate dihydrate (gypsum). At low fluxes, the increase in fouling layer resistance was quantitatively similar for the two operational modes. In contrast, at high fluxes, the fouling layer resistance increased more rapidly in constant flux filtration than in constant TMP filtration. The mechanism of scale formation in constant TMP and constant flux operation was self-limiting and self-reinforcing, respectively.

36 MATERIALS SCIENCE↗

Ghost states and surface structures of the charge density wave kagome metal ScV 6 Sn 6

In this work, we investigate the high-temperature phase of the kagome metal ScV 6 Sn 6 using scanning tunneling microscopy/spectroscopy (STM/S) and density functional theory calculations. STM topographic images of the cleaved sample reveal two distinct surface terminations: flat islands with Sn termination and trenches terminated by kagome layers with Sn as the outermost atomic layer. STS measurements on the Sn-terminated and kagome-terminated surfaces show significant differences, in particular the presence of large density of states near the Fermi level in the former case. Our first-principles calculations reveal that the charge density on the kagome-terminated surface gives rise to “ghost states” which show intensity away from surface atoms, arising due to hybridization of orbitals above the surface. These states can obscure the intrinsic properties of the surface, potentially leading to misattribution of the surface termination. This underscores the need for careful interpretation in STM studies, especially when discerning surface states of localized states. Understanding the surface structure of this versatile quantum material provides essential information for interpreting surface-sensitive experiments, tailoring material properties, engineering interfaces, and controlling stability and reactivity. This knowledge paves the way for further exploration and potential applications of kagome lattice materials in various fields, including quantum computing, topological physics, and advanced electronic devices.

36 MATERIALS SCIENCE↗

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗

In Situ Exploration of Dipole Field Effects on Weak Hysteresis in 3D/2D Perovskites

This research delves into the effects of 2D layers on the functionality of 3D perovskite using lock-in amplifier-based in situ surface photovoltage (SPV) and its phase spectroscopy, with an emphasis on elucidating the connection between the tuning of dipole moments and the photocurrent hysteresis. Conventionally, the SPV of a perovskite/hole transport layer is observed to diminish as positive bias escalates. However, this trend is reversed in the case of 3D perovskite samples, where an augmentation in SPV is noted under positive bias. Notably, 3D/2D perovskite structures initially show a decrease, then an increase in SPV as bias intensifies, a phenomenon more pronounced with larger dipole moments in 2D. However, there is no linear relationship between the dipole moment and the hysteresis factor. Furthermore, using in situ light-chopping-frequency-modulated SPV and Kelvin Probe Force Microscopy, it is revealed that the dipole fields of 2D layers can hinder ion migration. This leads to efficient hole transfer and minimal photocurrent hysteresis in 3D/2D perovskites, providing strong evidence for the underlying cause of hysteresis. Additionally, these findings suggest intricate interplays among the external electric field, interface dipole moments, and surface photovoltaics, offering significant insights into perovskite optoelectronics.

3D/2D perovskite↗

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗

CeO2 Nanoparticle Doping as a Probe of Active Site Speciation in the Catalytic Hydrolysis of Organophosphates

Organophosphate hydrolysis is important for degrading environmentally harmful compounds and recovering phosphate ions in biological molecules. CeO2 nanocrystals have been well-studied for dephosphorylation via hydrolysis owing to the accessible and tunable distribution of Ce3+ and Ce4+ ions. However, there remains uncertainty in the literature regarding which surface defect properties direct catalytic activity, such as the Ce3+/Ce4+ distribution, oxygen vacancies, faceting, and dopants, and to what degree they contribute to efficient hydrolysis. Trivalent (M3+) dopants serve as a tool for manipulating defects, including the concentration of Ce3+ and oxygen vacancies, thereby influencing the hydrolytic activity of CeO2. Herein, trivalent metal ions (M = Y3+, Cr3+, In3+, and Gd3+) were employed to modulate the active sites on the CeO2 nanocrystal surface, and the effects of each metal dopant on the cerium oxide active sites for organophosphate hydrolysis were investigated. M-doped CeO2 nanoparticles were synthesized via hydrothermal methods, followed by annealing to remove ligands and prime the nanocrystal surface for catalysis. Catalytic performance was evaluated using dimethyl-p¬-nitrophenyl phosphate (DMNP) as a model organophosphate substrate, with degradation monitored over time using UV-visible absorption spectroscopy. Powder X-ray diffraction (PXRD), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy revealed successful doping of CeO2 in all cases, albeit with distinctive characteristics demonstrating how M3+ dopants affect catalysis. We show that CeO2 exhibits high sensitivity to dopants that generate lattice strain, Ce3+ ions, and oxygen vacancy defects. Consequently, achieving high catalytic efficiency within CeO2 requires a balanced active site ensemble, wherein defects are maintained at optimal concentrations and distributions on the nanocrystal surface.

Miura-Stempel, Emily L.↗

Tailoring Pore Architecture and Heteroatom Functionality of Polymeric Waste-Derived Nanoporous Carbon for CO 2 Capture Applications

This study proposes upcycling polymeric waste, i.e., waste floral foam, into high-performance nanoporous carbon that efficiently captures CO 2 . This paper presents strategies for improving the properties of nanoporous carbon, which aid in a superior CO 2 capture performance. Initially, pristine nanoporous carbon was produced from waste floral foam using various KOH impregnation ratios. The nanoporous carbon with a 1:2 (waste floral foam:KOH) ratio exhibiting optimal CO 2 capture capability was further advanced through single and dual atom doping. The doping of N and codoping of N,S atoms into the nanoporous carbon altered its textural and surface chemical properties, making them efficient for CO 2 capture. Comparative CO 2 capture studies of pristine nanoporous carbon (NC-x), N-doped nanoporous carbon (N-NC2), and N,S-codoped nanoporous carbon (N,S-NC2) demonstrate the superiority of N-doping. N-doped nanoporous carbon exhibited the largest ultramicroporosity (0.3100 cm3/g, 63.43%) and highest heteroatom content (34.94 atomic %), contributing to its enhanced CO 2 capture capability (4.54 mmol/g). Finally, implementing the “waste-to-depollution” approach, this research lays the groundwork for producing low-cost, environmentally friendly nanoporous carbon with remarkable CO 2 capture attributes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Electron Spectro-Microscopy (ESM) Beamline at NSLS-II

Photoelectron spectroscopy is a primary tool for the study of the electronic structure of materials and the chemical composition of surfaces. High-resolution angle-resolved photoemission spectroscopy (ARPES) has the unique ability to map the energy bands in momentum space. Furthermore, going beyond the single particle picture, the self-energy corrections caused by correlations in solids can be extracted from the analysis of the emission line shape. The current level of refinement, in terms of energy and angular resolution (ΔE < 1 meV, Δθ < 0.1°), makes the technique sensitive to the lowest energy excitations and the dynamics of electrons, which in turn virtually determine all the macroscopic properties of any system and govern the chemical, electrical, magnetic, and physical processes. Similarly important, X-ray photoelectron microscopy (XPEEM), combined with the low-energy electron microscopy (LEEM), is indispensable in probing the complexity of chemical, structural, electronic and magnetic properties of surfaces and shallow interfaces, with the spatial resolution of few tens of nanometer (nm). The Electron-Spectro-Microscopy beamline (ESM) has been recently commissioned at NSLS-II and is now in operation. The primary spectroscopic technique is photoemission, performed over a wide energy range with control of light polarization and in a variety of flux/resolution conditions. The beamline has two experimental end stations that allow to perform ARPES and XPEEM/LEEM, separately. The ARPES end station focuses on high energy-resolution work, with spot-size of a few microns. The XPEEM/LEEM end station is a full-field microscope (XPEEM) operating either with the synchrotron generated X-rays (XPEEM), or with an internal electron gun (LEEM). Spatial resolution is crucial in studies of newly synthesized complex materials since they are often initially available only as small specimens (typically micron size). Furthermore, chemical inhomogeneities on surfaces are often an integral part of surface chemical processes. Finally, the ESM beamline with X-ray spots of few microns is optimized to study the electronic structure of novel materials with microscopy capabilities.

47 OTHER INSTRUMENTATION↗

A mapped dataset of surface ocean acidification indicators in large marine ecosystems of the United States

Mapped monthly data products of surface ocean acidification indicators from 1998 to 2022 on a 0.25° by 0.25° spatial grid have been developed for eleven U.S. large marine ecosystems (LMEs). The data products were constructed using observations from the Surface Ocean CO 2 Atlas, co-located surface ocean properties, and two types of machine learning algorithms: Gaussian mixture models to organize LMEs into clusters of similar environmental variability and random forest regressions (RFRs) that were trained and applied within each cluster to spatiotemporally interpolate the observational data. The data products, called RFR-LMEs, have been averaged into regional timeseries to summarize the status of ocean acidification in U.S. coastal waters, showing a domain-wide carbon dioxide partial pressure increase of 1.4 ± 0.4 μatm yr -1 and pH decrease of 0.0014 ± 0.0004 yr -1 . RFR-LMEs have been evaluated via comparisons to discrete shipboard data, fixed timeseries, and other mapped surface ocean carbon chemistry data products. Regionally averaged timeseries of RFR-LME indicators are provided online through the NOAA National Marine Ecosystem Status web portal.

54 ENVIRONMENTAL SCIENCES↗

Ground surface temperature derived Snow Cover Properties, Seward Peninsula, Alaska, 2019-2023

Snow-ground interface temperatures have been collected at the Teller mile marker 27 and Kougarok mile marker 64 field sites on the Seward Peninsula, Alaska from 2019 through 2023 (with data missing from Fall 2020 through Summer 2021 due to COVID). Temperatures were measured using iButton Link DS1921G-F5# Thermochron miniature temperature sensors and Tinytag TGP-4017 internal sensors deployed across the Kougarok 64 and Teller 27 field sites. These sensors are a cost-efficient way to collect snow-ground interface temperatures at a high spatial resolution, and when paired with air temperature data these measurements can provide insight into fine-scale variability in snowpack characteristics across the study sites. From this data, snow process metrics were calculated at each sensor location based on the methods outlined in Staub and Delaloye, 2017. Metrics are calculated daily for each sensor as well as over the entire season. These metrics include ground surface temperature (°C), the number of days under snow cover (number of days), the insulation effect of snow (unitless), the length of the transitional snow periods (number of days), as well as intermediaries such as temperature variability. Calculating these snow processes relies on the assumption that when snow covers a temperature sensor, it is buffered from diurnal fluctuations in air temperature by the insulating snow layer. More information on the calculated metrics can be found in the User Guide of this dataset, as well as in Staub and Delaloye’s 2017 publication Using Near-Surface Ground Temperature Data to Derive Snow Insulation and Melt Indices for Mountain Permafrost Applications. This dataset includes one daily and one seasonal *.csv file of metrics for every year of data, a daily and a seasonal *.csv data dictionary, and one User Guide document (*.pdf) describing data collection and processing.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Artificial intelligence driven laser parameter search: Inverse design of photonic surfaces using greedy surrogate-based optimization

Photonic surfaces designed with specific optical characteristics are becoming increasingly crucial for novel energy harvesting and storage systems. The design of these surfaces can be achieved by texturing materials using lasers. The optimal adjustment of laser fabrication parameters to achieve target surface optical properties is an open challenge. Thus, we develop a surrogate-based optimization approach. Our framework employs the Random Forest algorithm to model the forward relationship between the laser fabrication parameters and the resulting optical characteristics. During the optimization process, we use a greedy, prediction-based exploration strategy that iteratively selects batches of laser parameters to be used in experimentation by minimizing the predicted discrepancy between the surrogate model’s outputs and the user-defined target optical characteristics. This strategy allows for efficient identification of optimal fabrication parameters without the need to model the error landscape directly. We demonstrate the efficiency and effectiveness of our approach on two synthetic benchmarks and two specific experimental applications of photonic surface inverse design targets. By calculating the average performance of our algorithm compared to other state of the art optimization methods, we show that our algorithm performs, on average, twice as well across all benchmarks. Additionally, a warm starting inverse design technique for changed target optical characteristics enhances the performance of the introduced approach.

97 MATHEMATICS AND COMPUTING↗

Unequal {110} Facets: The Potential Role of Intraparticle Heterogeneity and Facet Termination in Photoelectrochemical Activity of Single BiVO 4 Particles

BiVO 4 photoanodes are promising for solar water splitting, with photogenerated electrons and holes preferentially reacting at top {010} and lateral {110} facets, respectively. However, the mechanisms driving this facet-dependent reactivity remain unclear. Here, in this study, we investigate facet-dependent photocurrent and material heterogeneity using correlative scanning photoelectrochemical microscopy (SPCM), electron beam induced current (EBIC) mapping, and mid-IR scattering scanning near-field optical microscopy (s-SNOM). SPCM measurements of 62 BiVO 4 particles confirmed higher photocurrents at lateral {110} facets compared to top {010} facets, but unexpectedly revealed variations in photocurrent among lateral facets within the same particle. Variations in lateral facet surface termination could explain the intraparticle-level reactivity heterogeneity, consistent with theoretical predictions. Nano-FTIR spectroscopy and Raman microspectroscopy indicated significant materials chemistry heterogeneity within individual particles and facets that could be attributed to variations in lattice vibration distortions that enhance the overlap between Bi 6s and O 2p orbitals. The increased orbital overlap is significant as it potentially increases hole mobility in the valence band and potentially explains the lateral facet-dependent charge separation efficiency observed in photocurrent maps. Facet-dependent electrical and EBIC measurements showed no space charge regions at interfacet junctions or metal-BiVO 4 contacts under vacuum, suggesting that photogenerated holes beneath top {010} facets are unlikely to transport to lateral {110} facets to drive water/sulfite oxidation. These findings indicate the potential influence of distinct bulk properties and surface termination chemistries across different particles and facets, highlighting the importance of carefully controlling defects and surface chemistry during sample growth to optimize photocatalytic performance.

BiVO4↗

Artificial Replication of Field Soiling Losses on PV Modules

In this paper, we experimentally demonstrate an improved replication of field soiling losses using an indoor artificial soiling chamber and tests on anti-soiling coated PV modules and coupons. The primary focus is to use site-specific soil collected from module surface and replicate the natural soiling processes including dust concentration in the air, slow and gradual dust accumulation and sedimentation on the module surface during the dominant soiling season of the site of interest. The experiments were conducted on two sample sets having different anti-soiling properties. The first set contains commercial modules with two different surface properties retrieved after three years of exposure from a single PV plant in a mid-Atlantic location; the other set contain glass coupons with three different coating materials that were installed and exposed over 4 months, at Lemoore, California. Major field-representative factors considered here for the close replication in the chamber include: the use of dust collected from modules surfaces at the outdoor sites to give the same dust chemistry; dust particle size distribution and concentration; the charge size of dust (< 0.15 g per injection); field humidity, and module temperature. The effectiveness of antisoiling coatings (or surface properties) for both sample sets were ranked in the artificial testing and were found to be closely matching with the field rank orders of the respective sites and sample sets. This paper provides the rank ordering results to objectively demonstrate the replication of field soiling losses in the artificial soiling chamber.

artificial soiling↗

Unraveling Exciton Trap Dynamics and Nonradiative Loss Pathways in Quantum Dots via Atomistic Simulations

Surface defects in colloidal quantum dots are a major source of nonradiative losses, yet the microscopic mechanisms underlying exciton trapping and recombination remain elusive. Here, we develop a model Hamiltonian based on atomistic electronic calculations to investigate exciton dynamics in CdSe/CdS core/shell QDs containing a single hole trap introduced by an unpassivated sulfur atom. By systematically varying the defect depth and reorganization energy, we uncover how defect-induced excitonic states mediate energy relaxation pathways. Our simulations reveal that a single localized defect can induce a rich spectrum of excitonic states, leading to multiple dynamical regimes, from slow, energetically off-resonant trapping to fast, cascaded relaxation through in-gap defect states. Crucially, we quantify how defect-induced polaron shifts and exciton-phonon couplings govern the balance between efficient radiative emission and rapid nonradiative decay. These insights clarify the microscopic origin of defect-assisted loss channels and suggest pathways for tailoring QD optoelectronic properties via surface and defect engineering.

Defects↗

Characteristics of graphene oxide-like materials prepared from different deashed-devolatilized coal chars and comparison with graphite-based graphene oxide, with or without the ultrasonication treatment

Deashed-devolatilized coal chars were prepared from anthracite, bituminous, subbituminous, and lignite coals, then oxidized to prepare graphene oxide (GO)-like materials that were extensively characterized and compared with a pristine graphite-based GO sample (CGO). Coal-based GO-like materials and CGO were then subjected to ultrasonication treatment for delamination, which also impacted their physicochemical properties. The surface oxygen contents of CGO and coal-based samples were ~32 % and ~26–35 %, respectively, that were reduced to ~27 % and ~21–24 %, respectively, after ultrasonication. The Fourier transform infrared and X-ray photoelectron spectroscopy spectra of all samples showed different profiles before and after the ultrasonication, suggesting a change in chemical functionalities. The Raman spectra of CGO and coal-based samples exhibited similar D and G bands with D/G intensity ratios (I D /I G ) of 0.93 and 0.88–0.92, respectively. The I D /I G ratio of CGO and most of the coal-based samples increased after the ultrasonication due to creation of more defects. The main X-ray diffraction (XRD) peak for CGO and coal-based samples were observed at ~11° and ~22–24°, respectively. Ultrasonication of the samples resulted in a reduction of crystallite size and number of layers for all CGO and coal-based samples, confirming both splitting and delamination of carbon layers. Additionally, different coal-based samples exhibited almost overlapping XRD profiles after the ultrasonication.

36 MATERIALS SCIENCE↗

Adsorption of Mixed Micelles of Polysorbate 80 and Oleic Acid to the Air–Water Interface

The solubilization of long chain amphiphiles with limited solubility into mixed micelles composed of highly soluble surfactants plays a crucial role in modulating the stability and functionality of formulations in pharmaceutical and food systems. Subsequently, the mixed micelles adsorb from solution to the air−water surface, defining the transport mechanism of the insoluble amphiphiles to the interface. We use X-ray reflectivity to measure the composition and provide insight into the structure of these mixed monolayers, and, alongside interfacial tension measurements, we provide an understanding of how the bulk composition determines the surface composition and the dynamics of tension reduction. We use a model system consisting of an insoluble fatty acid, oleic acid (OA), and a soluble micelle-forming surfactant, polysorbate 80 (PS80). PS80 forms spherical micelles, and, above the critical micelle concentration (cmc), OA is readily solubilized inside the micelles. We show that the adsorption of PS80/OA mixed micelles to the air−water interface rapidly reduces the tension and lowers the equilibrium tension in proportion to the OA concentration. X-ray reflectivity data, fit using Parratt-slab models, quantitively demonstrates that the monolayers become enriched with OA, and we show how the OA intercalates into the PS80 monolayers.

36 MATERIALS SCIENCE↗

Constructing Highly Durable Fuel Cell Catalysts Through Integrating Graphitic Shell‐Protected Composite Carbon Support with Gaseous Co Deposition‐Driven PtCo Intermetallics

Metal dissolution, nanoparticle agglomeration, and carbon support corrosion cause significant performance degradation of current PtCo catalysts under acidic and oxidative oxygen reduction reaction. Here, in this study, an integrated strategy is presented to design high-performance Pt 3 Co intermetallic catalysts by regulating gaseous Co deposition-driven diffusion into Pt nanoparticles supported on a composite carbon. The composite carbon is derived from ZIF-8/polyaniline, consisting of a high-surface-area (HSC) core and a protective graphitic shell (GS), which is employed to design 40 wt.% Pt/HSC@GS catalyst. The corresponding membrane electrode assemblies (MEAs) can maintain 1.09 A cm −2 at 0.7 V (20. 7% loss) after 10 000 cycles (1.0–1.5 V for carbon stability) and 1.15 A cm −2 (16.1% loss) after 150 000 cycles (0.60–0.95 V for catalyst stability). A ordered Pt 3 Co intermetallic is synthesized via a gaseous Co-deposition process, which yields a homogeneous Co-rich layer onto the Pt nanoparticles on the composite support, thereby facilitating Co diffusion into Pt crystal during subsequent ordering annealing to form the ordered intermetallic structure. This gaseous deposition leads to a thin carbon layer on PtCo nanoparticles, inhibiting particle growth during the annealing and mitigating Co dissolution under dynamic electrochemical conditions. The PtCo catalyst achieves impressive MEA performance and long-term durability (1.45 A cm −2 at 0.7 V after 120 000 cycles) under heavy-duty conditions.

30 DIRECT ENERGY CONVERSION↗