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Wang, Sibo

Publications and source records attributed to Wang, Sibo.

11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Platinum Surface Water Orientation Dictates Hydrogen Evolution Reaction Kinetics in Alkaline Media

The fundamental understanding of sluggish hydrogen evolution reaction (HER) kinetics on a platinum (Pt) surface in alkaline media is a topic of considerable debate. Herein, we combine cyclic voltammetry (CV) and electrical transport spectroscopy (ETS) approaches to probe the Pt surface at different pH values and develop molecular-level insights into the pH-dependent HER kinetics in alkaline media. The change in HER Tafel slope from ~110 mV/decade in pH 7–10 to ~53 mV/decade in pH 11–13 suggests considerably enhanced kinetics at higher pH. The ETS studies reveal a similar pH-dependent switch in the ETS conductance signal at around pH 10, suggesting a notable change of surface adsorbates. Fixed-potential calculations and chemical bonding analysis suggest that this switch is attributed to a change in interfacial water orientation, shifting from primarily an O-down configuration below pH 10 to a H-down configuration above pH 10. This reorientation weakens the O–H bond in the interfacial water molecules and modifies the reaction pathway, leading to considerably accelerated HER kinetics at higher pH. Finally, our integrated studies provide an unprecedented molecular-level understanding of the nontrivial pH-dependent HER kinetics in alkaline media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Amorphous nickel hydroxide shell tailors local chemical environment on platinum surface for alkaline hydrogen evolution reaction

In analogy to natural enzymes, an elaborated design of catalytic systems with a specifically tailored local chemical environment could substantially improve reaction kinetics, effectively combat catalyst poisoning effect and boost catalyst lifetime under unfavourable reaction conditions. Here we report a unique design of ‘Ni(OH) 2 -clothed Pt-tetrapods’ with an amorphous Ni(OH) 2 shell as a water dissociation catalyst and a proton conductive encapsulation layer to isolate the Pt core from bulk alkaline electrolyte while ensuring efficient proton supply to the active Pt sites. This design creates a favourable local chemical environment to result in acidic-like hydrogen evolution reaction kinetics with a lowest Tafel slope of 27 mV per decade and a record-high specific activity and mass activity in alkaline electrolyte. The proton conductive Ni(OH) 2 shell can also effectively reject impurity ions and retard the Oswald ripening, endowing a high tolerance to solution impurities and exceptional long-term durability that is difficult to achieve in the naked Pt catalysts. Furthermore, the markedly improved hydrogen evolution reaction activity and durability in an alkaline medium promise an attractive catalyst material for alkaline water electrolysers and renewable chemical fuel generation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data

Conservation tillage practices can bring benefits to agricultural sustainability. Accurate spatial and temporal resolved information of field-scale crop residue cover, which reflects tillage intensity, is highly valuable for evaluating the outcomes of government conservation programs and voluntary ecosystem service markets, as well as facilitating agroecosystem modeling to quantify cropland biogeochemical processes. Remote sensing has the potential to cost-effectively detect crop residue cover, however, existing regional-scale studies were limited by insufficient ground truth data, scale mismatch between coarse satellite pixels and ground data, and the lack of key spectral data for detecting crop residues. Therefore, this study developed an innovative cross-sensing framework to integrate proximal sensing, airborne hyperspectral imaging, and satellite Earth Observation through deep learning to quantify field-level crop residue cover fractions at the regional scale. Specifically, we have collected intensive ground orthographic photos and conducted airborne hyperspectral surveys at corn and soybean fields of Champaign and nearby counties in Illinois, the heartland of the U.S. Corn Belt. Through semi-automatic labeling aided by ResNet-50 and superpixel image segmentation, we obtained 6719 records of ground residue fractions. With these ground data, we developed the 1-dimensional convolution neural network (CNN) model using airborne hyperspectral reflectance, which has 0.5m spatial resolution and 3–5 nm spectral resolution from 400 to 2400 nm, to predict residue fractions. By applying the CNN model to airborne pixels, we augmented “ground truth” data of crop residues and further combined them with Harmonized Landsat and Sentinel-2 (HLS) satellite data to quantify regional residue fractions at 30 m resolution. Results show that airborne hyperspectral imagery with CNN can accurately detect residue fractions (R 2 = 0.82, relative RMSE = 11.73%) to effectively generate quasi “ground truth” data to support satellite upscaling to all fields. With independent ground data for testing, we found that the ground-airborne-satellite integrative framework achieved better predictions in estimating crop residue cover (R 2 = 0.67, relative RMSE = 17.53%) than the conventional ground-satellite upscaling (R 2 = 0.22, relative RMSE = 32.09%). Here we also found that the shortwave infrared wavelengths, particularly 2100–2300 nm, are vital for predicting crop residue cover. Sentinel-2 and Landsat-8 data have a comparable capability to track residue fractions due to similar shortwave infrared wavelengths. This study highlights the high accuracy of hyperspectral imaging to detect agroecosystem tillage management practices and the advantages of cross-scale sensing to cost-effectively integrate multi-source data to quantify field-level agroecosystem variables across scales.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The role of alkali metal cations and platinum-surface hydroxyl in the alkaline hydrogen evolution reaction

The platinum-catalysed hydrogen evolution reaction (HER) generally shows poorer kinetics in alkaline electrolyte and represents a key challenge for alkaline water electrolysis. In the presence of alkali metal cations and hydroxyl anions, the electrode–electrolyte (platinum–water) interface in an alkaline electrolyte is far more complex than that in an acidic electrolyte. Here we combine electrochemical impedance spectroscopy and an electrical transport spectroscopy approach to probe and understand the fundamental role of different cations (Li + , Na + and K + ) in HER kinetics. Our integrated studies suggest that the alkali metal cations play an indirect role in modifying the HER kinetics, with the smaller cations being less destabilizing to the hydroxyl adsorbate (OH ad ) species in the HER potential window, which favours a higher coverage of OH ad on the platinum surface. Here, the surface OH ad species are highly polar and act as both electronically favoured proton acceptors and geometrically favoured proton donors to promote water dissociation in alkaline media, thus boosting the Volmer-step kinetics and the HER activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Determining the hydronium pKα at platinum surfaces and the effect on pH-dependent hydrogen evolution reaction kinetics

Electrocatalytic hydrogen evolution reaction (HER) is critical for green hydrogen generation and exhibits distinct pH-dependent kinetics that have been elusive to understand. A molecular-level understanding of the electrochemical interfaces is essential for developing more efficient electrochemical processes. Here we exploit an exclusively surface-specific electrical transport spectroscopy (ETS) approach to probe the Pt-surface water protonation status and experimentally determine the surface hydronium pK a = 4.3. Quantum mechanics (QM) and reactive dynamics using a reactive force field (ReaxFF) molecular dynamics (RMD) calculations confirm the enrichment of hydroniums (H 3 O + * ) near Pt surface and predict a surface hydronium pK a of 2.5 to 4.4, corroborating the experimental results. Importantly, the observed Pt-surface hydronium pK a correlates well with the pH-dependent HER kinetics, with the protonated surface state at lower pH favoring fast Tafel kinetics with a Tafel slope of 30 mV per decade and the deprotonated surface state at higher pH following Volmer-step limited kinetics with a much higher Tafel slope of 120 mV per decade, offering a robust and precise interpretation of the pH-dependent HER kinetics. These insights may help design improved electrocatalysts for renewable energy conversion.

Zhong, Guangyan↗
DOE OSTI2020

STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product

Remote sensing datasets with both high spatial and high temporal resolution are critical for monitoring and modeling the dynamics of land surfaces. However, no current satellite sensor could simultaneously achieve both high spatial resolution and high revisiting frequency. Therefore, the integration of different sources of satellite data to produce a fusion product has become a popular solution to address this challenge. Many methods have been proposed to generate synthetic images with rich spatial details and high temporal frequency by combining two types of satellite datasets—usually frequent coarse-resolution images (e.g., MODIS) and sparse fine-resolution images (e.g., Landsat). In this paper, we introduce STAIR 2.0, a new fusion method that extends the previous STAIR fusion framework, to fuse three types of satellite datasets, including MODIS, Landsat, and Sentinel-2. In STAIR 2.0, input images are first processed to impute missing-value pixels that are due to clouds or sensor mechanical issues using a gap-filling algorithm. The multiple refined time series are then integrated stepwisely, from coarse- to fine- and high-resolution, ultimately providing a synthetic daily, high-resolution surface reflectance observations. We applied STAIR 2.0 to generate a 10-m, daily, cloud-/gap-free time series that covers the 2017 growing season of Saunders County, Nebraska. Moreover, the framework is generic and can be extended to integrate more types of satellite data sources, further improving the quality of the fusion product. View Full-Text

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Enhancing ZnO nanowire gas sensors using Au/Fe 2 O 3 hybrid nanoparticle decoration

Heterojunctions are an important strategy for designing high performance electrical sensor materials and related devices. Herein, a new type of metal-semiconductor hybrid nanoparticle has been successfully used to remarkably sensitize the surface of ZnO nanowires for detecting NO 2 with high responses over a broad temperature window ranging from room temperature to 600 °C. These hybrid nanoparticles are comprised of iron oxide nanowires with well dispersed single crystalline Au nanoparticles. The hybrid nanoparticle decorated ZnO nanowires have achieved a giant response, as high as 74 500 toward NO 2 gas, about 42 times that of Au decorated ZnO nanowire sensors. This dramatic enhancement may be attributed to the efficient charge transfer across the Au–Fe 2 O 3 Schottky and Fe 2 O 3 –ZnO semiconductor heterojunction interfaces. Due to the incorporation of thermally-stable Fe 2 O 3 nanoparticles as the support of Au nanoparticles, the working temperature of nanowire sensors was successfully extended to higher temperatures, with an increase of 200 °C, from 400 °C to 600 °C. Such a combination of semiconductor heterojunction and semiconductor-metal Schottky contact presents a new strategy for designing high performance electrical sensors with high sensitivity, stability, selectivity, and wide operation temperature window, which are potentially suitable for advanced energy systems such as automotive engines and power plants.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

BESS-STAIR: a framework to estimate daily, 30m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

Abstract. With increasing crop water demands and drought threats, mapping andmonitoring of cropland evapotranspiration (ET) at high spatial and temporalresolutions become increasingly critical for water management andsustainability. However, estimating ET from satellites for precise waterresource management is still challenging due to the limitations in bothexisting ET models and satellite input data. Specifically, the process of ETis complex and difficult to model, and existing satellite remote-sensing datacould not fulfill high resolutions in both space and time. To address theabove two issues, this study presents a new high spatiotemporal resolution ETmapping framework, i.e., BESS-STAIR, which integrates a satellite-drivenwater–carbon–energy coupled biophysical model, BESS (Breathing Earth SystemSimulator), with a generic and fully automated fusion algorithm, STAIR(SaTallite dAta IntegRation). In this framework, STAIR provides daily 30'mmultispectral surface reflectance by fusing Landsat and MODIS satellite datato derive a fine-resolution leaf area index and visible/near-infrared albedo,all of which, along with coarse-resolution meteorological and CO 2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET.We applied BESS-STAIR from 2000 through 2017 in six areas across the US CornBelt and validated BESS-STAIR ET estimations using flux-tower measurementsover 12 sites (85 site years). Results showed that BESS-STAIR daily ETachieved an overall R2=0.75, with root mean square error RMSE=0.93 mm d -1 and relative error RE =27.9 % when benchmarkedwith the flux measurements. In addition, BESS-STAIR ET estimations capturedthe spatial patterns, seasonal cycles, and interannual dynamics well indifferent sub-regions. The high performance of the BESS-STAIR frameworkprimarily resulted from (1) the implementation of coupled constraints onwater, carbon, and energy in BESS, (2) high-quality daily 30 m data from theSTAIR fusion algorithm, and (3) BESS's applicability under all-skyconditions. BESS-STAIR is calibration-free and has great potentials to be areliable tool for water resource management and precision agricultureapplications for the US Corn Belt and even worldwide given the globalcoverage of its input data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Activating low-temperature diesel oxidation by single-atom Pt on TiO 2 nanowire array

Supported metal single atom catalysts (SACs) present an emerging class of low-temperature catalysts with high reactivity and selectivity, which, however, face challenges on both durability and practicality. Herein, we report a single-atom Pt catalyst that is strongly anchored on a robust nanowire forest of mesoporous rutile titania grown on the channeled walls of full-size cordierite honeycombs. This Pt SAC exhibits remarkable activity for oxidation of CO and hydrocarbons with 90% conversion at temperatures as low as ~160 °C under simulated diesel exhaust conditions while using 5 times less Pt-group metals than a commercial oxidation catalyst. Such an excellent low-temperature performance is sustained over hydrothermal aging and sulfation as a result of highly dispersed and isolated active single Pt ions bonded at the Ti vacancy sites with 5 or 6 oxygen ions on titania nanowire surfaces.

36 MATERIALS SCIENCE↗