Engineering topics

Wei, Lingze

Publications and source records attributed to Wei, Lingze.

9 records

DOE OSTI2024

Modeling Diurnal and Annual Ethylene Generation from Solar-Driven Electrochemical CO 2 Reduction Devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards achieving net-negative carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Here, using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimental CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. We simulated diurnal product outputs with and without the effects of ambient temperature to determine gaseous product temperature sensitivity. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne/yr at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

Yap, Kyra M. K.↗

DOE OSTI2024

Tuning Two-Dimensional Phthalocyanine Dual Site Metal–Organic Framework Catalysts for the Oxygen Reduction Reaction

Metal-organic frameworks (MOFs) offer an interesting opportunity for catalysis, particularly for metal-nitrogen-carbon (M-N-C) motifs by providing an organized porous structural pattern and well-defined active sites for the oxygen reduction reaction (ORR), a key need for hydrogen fuel cells and related sustainable energy technologies. Here, in this work, we leverage electrochemical testing with computational models to study the electronic and structural properties in these systems and their relationship to ORR activity and stability based on dual transitional metal centers. These consists of two M1 metals with amine nodes coordinated to a single M2 metal with a phthalocyanine linker, where M1/M2 = Co, Ni, or Cu. Co-based metal centers, in particular Ni-Co, demonstrate the highest overall activity of all nine tested MOFs. Computationally, we identify the dominance of Co-sites, relative higher importance of the M2 site, and the role of layer M1 interactions on the ORR activity. Selectivity measurements indicate that M1 sites of MOFs, particularly Co, exhibits lowest (< 4%), and Ni demonstrates highest (>46%) two-electron selectivity, in good agreement with computational studies. Direct in-situ stability characterization, measuring dissolved metal ions, and calculations, using an alkaline stability metric, confirm that Co is the most stable metal in the MOF, while Cu exhibits notable instability at the M1. Overall, this study reveals how atomistic coupling of electronic and structural properties affects the ORR performance of dual site MOF catalysts and opens new avenues for tunable design and future development of these systems for practical electrochemical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Interpretable Machine Learning Models for Practical Antimonate Electrocatalyst Performance

Computationally predicting the performance of catalysts under reaction conditions is a challenging task due to the complexity of catalytic surfaces and their evolution in situ, different reaction paths, and the presence of solid-liquid interfaces in the case of electrochemistry. We demonstrate here how relatively simple machine learning models can be found that enable prediction of experimentally observed onset potentials. Inputs to our model are comprised of data from the oxygen reduction reaction on non-precious transition-metal antimony oxide nanoparticulate catalysts with a combination of experimental conditions and computationally affordable bulk atomic and electronic structural descriptors from density functional theory simulations. From human-interpretable genetic programming models, we identify key experimental descriptors and key supplemental bulk electronic and atomic structural descriptors that govern trends in onset potentials for these oxides and deduce how these descriptors should be tuned to increase onset potentials. Here, we finally validate these machine learning predictions by experimentally confirming that scandium as a dopant in nickel antimony oxide leads to a desired onset potential increase. Macroscopic experimental factors are found to be crucially important descriptors to be considered for models of catalytic performance, highlighting the important role machine learning can play here even in the presence of small datasets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗

DOE OSTI2023

Carbon flowers as electrocatalysts for the reduction of oxygen to hydrogen peroxide

Small-scale and decentralized production of H 2 O 2 via electrochemical reduction of oxygen is of great benefit, especially for sanitization, air and water purification, as well as for a variety of chemical processes. The development of low-cost and high-performance catalysts for this reaction remains a key challenge. Carbon-based materials have drawn substantial research efforts in recent years due to their advantageous properties, such as high chemical stability and high tunability in active sites and morphology. Deeper understanding of structure–activity relationships can guide the design of improved catalysts. We hypothesize that mass transport to active sites is of great importance, and herein we use carbon materials with unique flower-like superstructures to achieve high activity and selectivity for O 2 reduction to H 2 O 2 . The abundance of nitrogen active sites controlled by pyrolysis temperature resulted in high catalytic activity and selectivity for oxygen reduction reaction (ORR). The flower superstructure showed higher performance than the spherical nanoparticles due to greater accessibility to the active sites. Chemical activation improves the catalysts’ performances further, driving the production of H 2 O 2 to a record-setting rate of 816 mmol·g cat -1 ·h -1 using a bulk electrolysis setup. In conclusion, this work demonstrates the development of a highly active catalyst for the sustainable production of H 2 O 2 through rational design and synthetic control. The understanding from this work provides further insight into the design of future carbon-based electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Tracking the Dynamics of a Ag-MnO x Oxygen Reduction Catalyst Using In Situ and Operando X-ray Absorption Near-Edge Spectroscopy

Sustainable electricity generation via hydrogen fuel cells requires the development of efficient oxygen reduction reaction (ORR) catalysts. In situ/operando experiments are necessary to uncover the extent of dynamic material changes during catalysis. Herein, we use in situ/operando X-ray absorption near-edge spectroscopy to track Mn valence changes of a promising, ultrathin, porous MnO x layer on a Ag thin film. Mn–K-edge measurements as a function of electrochemical environment and ORR conditions reveal that, interestingly, when driving the ORR at 0.8 VRHE, the Mn is distinctively more reduced and the MnO x redox is nonreversible in contrast to measurements in N 2 -saturated electrolyte. Ex situ inductively coupled plasma mass spectrometry, atomic force microscopy, and X-ray photoelectron spectroscopy indicate that these phenomena do not correlate to metal dissolution but might be associated with morphological surface reconstruction related to Ag valency. Furthermore, this study highlights how the microenvironment and catalysis play a key role in the in situ/operando surface structure and chemical state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Insights into Active Sites and Mechanisms of Benzyl Alcohol Oxidation on Nickel–Iron Oxyhydroxide Electrodes

The electrochemical oxidation of bio-derived molecules has recently garnered interest for its potential in opening electrified synthetic pathways toward value-added products. Herein, we investigate the electrochemical conversion of benzyl alcohol (BA) to benzaldehyde and benzoate on nickel–iron (Fe ~ 7–18%) electrodes as a model system to understand reaction mechanisms and environmental conditions that can transform these molecules. Our results indicate a strong correlation between benzyl alcohol oxidation (BAO) onset potentials and Ni(II/III) redox peak positions, highlighting the potential role that lower oxidation states of nickel, i.e., Ni 3+ , can play in BAO catalysis. Our work on the Ni 2+/3+ system complements mechanisms that involve higher oxidation states of Ni as reported by others. We note that the Ni redox position and thus BAO onset is impacted by Fe incorporation during electrochemistry from unpurified electrolytes, which can resemble standard reactor operating conditions. We perform a systematic computational investigation into BAO and provide density functional theory (DFT) insights into how the redox mechanism has been such a prominent focus of alcohol oxidations. This includes the mode of BA adsorption and the nature of the adsorption site; upon conversion of the Ni 2+ surface to active Ni 3+ via hydroxyl deprotonation, BAO is thermodynamically downhill. Our DFT study also introduces the possibility of a vacancy-driven mechanism, though expected to be less prevalent during catalysis than the redox mechanism for a Ni 3+ surface. Through the systematic investigation of experimental reaction conditions and computational free energy thermodynamics, we have gained valuable insights into BAO reaction mechanisms that inform catalytic activity. Our study opens avenues for further design and development of catalyst active sites for the oxidation of related organic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Understanding the Stability of Manganese Chromium Antimonate Electrocatalysts through Multimodal In Situ and Operando Measurements

Herein, we utilize an on-line electrochemical flow cell coupled with an inductively coupled plasma-mass spectrometer (ICP-MS) to characterize the impact of composition and reactant gas on the multielement dissolution of Mn(-Cr)-Sb-O electrocatalysts. Compared to Mn 2 O 3 and Cr 2 O 3 oxides, we find that the antimonate framework stabilizes Mn at OER potentials and Cr at both ORR and OER potentials. Furthermore, dissolution of Mn and Cr from Mn(-Cr)-Sb-O is found to be driven by ORR reaction rate, with minimal dissolution under N 2 . We observe preferential dissolution of Cr totaling 13% over 10 minutes at 0.3, 0.6, and 0.9 V vs RHE, with only 1.5% loss of Mn, indicating an enrichment of Mn at the surface of the particles. Despite this asymmetric dissolution, in situ X-ray absorption spectroscopy (XAS) showed no measurable changes in the Mn K-edge at comparable potentials. This lack of change could suggest that modification to the Mn oxidation state in the surface layer is too small or that layer is too thin to be measured with the bulk XAS measurement. Lastly, on-line ICP-MS was used to assess the effects of applied potential, scan rate, and current of Mn-Cr-Sb-O during cyclic voltammetry and accelerated stress tests. With this deeper understanding of the interplay between oxygen reduction and dissolution, testing procedures were identified to maximize both activity and stability. This work highlights the use of multi-modal in situ characterization techniques in tandem to build a more complete model of stability and develop protocols for optimizing catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Electro-assisted regeneration of pH-sensitive ion exchangers for sustainable phosphate removal and recovery

Removal and recovery of phosphate from wastewater can minimize deleterious environmental impacts and supplement fertilizer supply. Hybrid anion exchangers (HAIX, with doped ferric oxide nanoparticles (FeOnp)) can remove phosphate from complex wastewaters and recover concentrated phosphate solutions. Here, we integrate HAIX with a weak acid cation exchanger (WAC) to enrich phosphate and calcium in mild regenerants and precipitate both elements for recovery. We demonstrated an electro-assisted regeneration approach to avoid strong acid and base input. Based on demonstrated pH sensitivities of both materials, electrochemically produced mild electrolytes (pH 3 and pH 11), which are 100–1000 times less concentrated than typical regenerants, preserved 80% WAC and 50% HAIX capacities over five batch adsorption-regeneration cycles. FeOnp in HAIX facilitated regeneration due to pH sensitivity and their likely distribution on the resin particle surface, which reduced intraparticle diffusion path length. In column tests, repeatable phosphate removal (> 95%) from synthetic wastewater (3 mg P/L) was achieved with 20 kWh/kg P specific energy consumption. After removal, a similar 50% HAIX regeneration efficiency as batch experiments was achieved. In spent regenerant, more than 95% phosphorus was recovered as hydroxyapatite. This novel approach enhances ion exchange by minimizing chemical inputs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗