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Open Access Publications from the University of California

Scholarly Works (17 results)

  • Article
  • Peer Reviewed
UCLA Previously Published Works (2022)
Graphene has received tremendous interest in both chemical and physical fields. Among different edges of the graphene system, the zigzag edge terminated graphene nanoribbons (ZGNRs) show unique magnetic properties in the antiferromagnetic (AFM) state. However, to date, the understanding of ZGNR chemical properties is mainly based on the partial radical concept, and in previous studies, the energy differences between the ferromagnetic (FM) and AFM states are smaller than experimental evidence. Here, we report that the strongly constrained and appropriately normed functional gives a significantly larger energy difference, which matches the experimental observation. Furthermore, utilizing the energetics in the large difference case, we propose a conceptual supplement to the previous partial radical concept: the overall stabilization of the AFM state compared to the nonmagnetic (NM) state consists of two parts that affect the adsorption energy conversely. The NM-FM energy differences will strengthen the adsorption, being in line with the previous partial radical concept. The FM-AFM energy differences will instead weaken the adsorption. We perform calculations of H, OH, and LiS radical adsorption energies on ZGNRs to show that this weakening effect is numerically non-negligible: at least a ∼0.2 eV difference in the adsorption energies is found. We expect that this refinement of the partial radical concept can provide a more comprehensive understanding of the chemical properties of ZGNRs. The differences in adsorption energies for the H, OH, and LiS radicals found here lead to significant changes in the predicted reactivity of the ZGNR models.
  • 1 supplemental PDF
Cover page: Revisiting the link between magnetic properties and chemisorption at graphene nanoribbon zigzag edge
  • Article
  • Peer Reviewed
UCLA Previously Published Works (2022)
Copper (Cu) remains the most important metal catalyst for the carbon dioxide reduction reaction (CO2 RR) into C2 products. Due to limited evidence from in situ experiments, mechanistic studies are often performed in the framework of density functional theory (DFT), using functionals at the generalized gradient approximation (GGA) level, which have fundamental difficulties to correctly describe CO adsorption and surface stability. We employ the adiabatic connection fluctuation dissipation theorem within the random phase approximation (RPA), in combination with the linearized Poisson-Boltzmann equation to describe solvation effects, to investigate the mechanism of CO2 RR on the Cu(100) facet. Qualitatively different from the DFT-GGA results, RPA results propose the formation of *OCCHO as the potential determining step towards C2 products. The results suggest that it is important to use more accurate methods like RPA when modeling reactions involving multiple CO-related species like CO2 RR.
  • 1 supplemental PDF
Cover page: Improving the Accuracy of Modelling CO2 Electroreduction on Copper Using Many‐Body Perturbation Theory
  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2022)

Electrocatalysis plays a key role in sustainable energy conversion and storage. Although tremendous efforts from the experimental side have been devoted to elucidating the reaction mechanism, the detailed reaction pathways are still controversial due to intrinsic difficulty of in situ spectroscopy under electrochemical conditions. Therefore, computational studies based on density functional theory (DFT) energetics serve as an important tool to clarify the reaction mechanism. However, several aspects such as solvation effects and the electrochemical potential effects are important for the electrochemical systems while such effects are often absent in the simulations. Moreover, current DFT exchange correlation functionals present certain qualitative and quantitative errors, while the combination of solvation treatments and the more advanced computational methods are not established. To address these concerns, this thesis work on two different levels, stressing on incorporating the necessary effects to model the electrochemical processes. At the DFT level, we model the complicated sulfur reduction reaction process on heteroatom doped holey graphene framework. Specifically, we elucidate the electrocatalytic origin of the improved battery performance with these catalysts and decipher the complex 16-electron process. At the more advanced many-body perturbation theory (MBPT) level, we focus on the random phase approximation (RPA), as a promising approach to address certain DFT errors such as the carbon monoxide (CO) adsorption puzzle: the commonly used functionals give incorrect prediction of the CO adsorption site and energy on transition metal catalysts, which is key for several catalytic processes including the industrial catalysis for methanol synthesis from synthesis gas, the water-gas shift reaction, and the electrochemical carbon dioxide reduction reaction. Nevertheless, the cost of RPA for surface systems is often unaffordable, and the combination of RPA with implicit solvation and further the grand canonical treatment of electrons to describe the electrochemical potential, is generally not established. In this thesis, to pave the way to further electrochemical applications using RPA, we exploit a k-space extrapolation scheme to reduce the cost for surface calculations. Then we further combine the RPA framework for electrified interfaces, including implicit solvation described using the linearized Poisson-Boltzmann equation and the grand canonical treatment of electrons. We show that the RPA results are qualitatively and quantitatively different from commonly used functionals and match better with the experimental results.

    Cover page: Computational Modeling of Electrochemical Systems for Energy Conversion Using Density Functional Theory and Many-Body Perturbation Theory
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2021)
    First-principles calculations play a key role in understanding the interactions of molecules with transition-metal surfaces and the energy profiles for catalytic reactions. However, many of the commonly used density functionals are not able to correctly predict the surface energy as well as the adsorption site preference for a key molecule such as CO, and it is not clear to what extent this shortcoming influences the prediction of reaction or diffusion pathways. Here, we report calculations of carbon monoxide diffusion on the Cu(001) surface along the [100] and [110] pathways, as well as the surface energy of Cu(001), and CO-adsorption energy and compare the performance of the Perdew-Burke-Ernzerhof (PBE), PBE + D2, PBE + D3, RPBE, Bayesian error estimation functional with van der Waals correlation (BEEF-vdW), HSE06 density functionals, and the random phase approximation (RPA), a post-Hartree-Fock method based on many-body perturbation theory. We critically evaluate the performance of these methods and find that RPA appears to be the only method giving correct site preference, overall barrier, adsorption enthalpy, and surface energy. For all of the other methods, at least one of these properties is not correctly captured. These results imply that many density functional theory (DFT)-based methods lead to qualitative and quantitative errors in describing CO interaction with transition-metal surfaces, which significantly impacts the description of diffusion pathways. It is well conceivable that similar effects exist when surface reactions of CO-related species are considered. We expect that the methodology presented here will be used to get more detailed insights into reaction pathways for CO conversion on transition-metal surfaces in general and Cu in particular, which will allow us to better understand the catalytic and electrocatalytic reactions involving CO-related species.
    • 1 supplemental PDF
    Cover page: Diffusion Barriers for Carbon Monoxide on the Cu(001) Surface Using Many-Body Perturbation Theory and Various Density Functionals
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2023)
    Despite the wide applications, the ab initio modeling of the ceria based catalyst is challenging. The partial occupation in the 4f orbitals creates a fundamental challenge for commonly used density functional theory (DFT) methods, including semilocal functionals with Hubbard U correction to force localization and hybrid functionals. In this work, we benchmark the random phase approximation (RPA) for ceria surface properties, including surface energy and hydrogenation energy, compared to the results utilizing the DFT + U approach or hybrid functionals. We show that, for the latter approaches, different surface properties require opposite directions of parameter tuning. This forms a dilemma for the parameter based DFT methods, as the improvement of a certain property by tuning parameters will inevitably lead to the worsening of other properties. Our results suggest that the parameter-free many-body perturbation theory methods exemplified by RPA are a promising strategy to escape the dilemma and provide highly accurate descriptions, which will allow us to better understand the catalytic reactions in ceria related systems.
    • 1 supplemental PDF
    Cover page: Toward more accurate surface properties of ceria using many-body perturbation theory.Creative Commons 'BY-NC-ND' version 4.0 license
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2023)
    • 1 supplemental PDF
    Cover page: Photoelectron Storage at the WO3/TiO2 Interface: Modeling in Ambient Conditions from First-Principles CalculationsCreative Commons 'BY-NC-ND' version 4.0 license
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2022)
    Electrocatalysis plays a key role in sustainable energy conversion and storage. It is critical to model the grand canonical treatment of electrons, which accounts for the electrochemical potential explicitly, at the atomic scale and understand these reactions at electrified interfaces. However, such a grand canonical treatment for electrocatalytic modeling is in practice restricted to a treatment of electronic structure with density functional theory, and more accurate methods are in many cases desirable. Here, we develop an original workflow combining the grand canonical treatment of electrons with many-body perturbation theory in its random phase approximation (RPA). Using the potential dependent adsorption of carbon monoxide on the copper (100) facet, we show that the grand canonical RPA energetics provide the correct on-top Cu geometry for CO at reducing potential. The match with experimental results is significantly improved compared to the functionals at the generalized gradient approximation level, which is the most commonly used approximation for electrochemical applications. We expect this development to pave the way to further electrochemical applications using RPA.
    • 1 supplemental PDF
    Cover page: Modeling Electrochemical Processes with Grand Canonical Treatment of Many-Body Perturbation Theory.
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2021)
    • 1 supplemental PDF
    Cover page: Atomic Environments in N‑Containing Graphitic Carbon Probed by First-Principles Calculations and Solid-State Nuclear Magnetic Resonance
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2022)
    The rearrangement of Cu surfaces under electrochemical conditions is known to play a key role in the surface activation for major electrocatalytic reactions. Despite the extensive experimental insights into such rearrangements, from surface-sensitive spectroscopy and microscopy, the spatial and temporal resolution of these methods is insufficient to provide an atomistic picture of the electrochemical interface. Theoretical characterization has also been challenged by the diversity of restructuring configurations, surface stoichiometry, adsorbate configurations, and the effect of the electrode potential. Here, atomistic insight into the restructuring of the electrochemical interface is gained from first principles. Cu(100) restructuring under varying applied potentials and adsorbate coverages is studied by grand canonical density functional theory and global optimization techniques, as well as ab initio molecular dynamics and mechanistic calculations. We show that electroreduction conditions cause the formation of a shifted-row reconstruction on Cu(100), induced by hydrogen adsorption. The reconstruction is initiated at 1/6 ML H coverage, when the Cu-H bonding sufficiently weakens the Cu-Cu bonds between the top- and sublayer, and further stabilized at 1/3 ML when H adsorbates fill all the created 3-fold hollow sites. The simulated scanning tunneling microscopy (STM) images of the calculated reconstructed interfaces agree with experimental in situ STM. However, compared to the thermodynamic prediction, the onsets of reconstruction events in the experiment occur at more negative applied voltages. This is attributed to kinetic effects in restructuring, which we describe via different statistical models, to produce the potential- and pH-dependent surface stability diagram. This manuscript provides rich atomistic insight into surface restructuring in electroreduction conditions, which is required for the understanding and design of Cu-based materials for electrocatalytic processes. It also offers the methodology to study the problem of in situ electrode reconstruction.
      Cover page: Hydrogen-Induced Restructuring of a Cu(100) Electrode in Electroreduction Conditions
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2023)
      The dynamic restructuring of Cu surfaces in electroreduction conditions is of fundamental interest in electrocatalysis. We decode the structural dynamics of a Cu(111) electrode under reduction conditions by joint first-principles calculations and operando electrochemical scanning tunneling microscopy (ECSTM) experiments. Combining global optimization and grand canonical density functional theory, we unravel the potential- and pH-dependent restructuring of Cu(111) in acidic electrolyte. At reductive potential, Cu(111) is covered by a high density of H atoms and, below a threshold potential, Cu adatoms are formed on the surface in a (4×4) superstructure, a restructuring unfavorable in vacuum. The strong H adsorption is the driving force for the restructuring, itself induced by the electrode potential. On the restructured surface, barriers for hydrogen evolution reaction steps are low. Restructuring in electroreduction conditions creates highly active Cu adatom sites not present on Cu(111).
      • 1 supplemental PDF
      Cover page: Restructuring and Activation of Cu(111) under Electrocatalytic Reduction ConditionsCreative Commons 'BY-NC-ND' version 4.0 license
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