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Open Access Publications from the University of California

Scholarly Works (5 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2024)

Nanoclusters, with their atomically-precise structures that have metal cores and molecular-like electronic structures, are interesting materials with a broad range of applications in energy and chemical industries. Gold clusters are of specific interest due to their high quantum efficiency, bio-compatibility, catalytic activity and selectivity. Current characterization techniques lack the temporal and spatial resolution required to understand the behavior of nanoclusters in relevant environments, and as such, synthetic efforts to design new nan- oclusters largely rely on trial and error. This thesis describes several approaches to better understand the synthesis and stability of nanoclusters using theory and modeling.

As with all modeling, there are trade-offs between model complexity and efficiency. In this thesis, nanoclusters and nanoparticles are simulated with appropriate modeling techniques to answer the relevant questions that are posed at different length and time-scales. In the first part of this thesis, density functional theory (DFT) simulations are employed to map the potential energy surfaces of gold nanoclusters stabilized by ligands. Considering ensembles of clusters was very important in this work, and over 10,000 phosphine-stabilized gold clusters were generated with a ligation algorithm and their stabilities as a function of environment were calculated. These simulations give insight into the importance of ligands in determining stable cluster conformations, as well as the impact of cluster size and ligation on electronic structure and bonding. Next, simulations over longer time periods than would be tractable to calculate with DFT are performed, made possible by the development of an interatomic potential for thiolate-protected gold nanoclusters. The interatomic potential is fitted to many examples of DFT calculated nanoclusters and learns the energy-structure relationships that are present in all thiolate-protected gold nanoclusters. The potential is used to perform long (∼0.1μs) simulations of Au25(SR)18, a known nanocluster that is remarkably stable. Interesting mechanisms are uncovered in the simulations which are not yet possible to observe experimentally. Finally, in order to understand the surprising miscibility of the immiscible elements Au and Rh in ultra-small nanoparticles, I developed a continuum model informed by DFT calculations but applicable to any size of nanoparticle that depends on the enthalpy and entropy of mixing as well as surface energies and surface affinities to adsorbate species present in the synthesis conditions. The unusual mixing behavior observed experimentally is in fact due to the nature of the surface environment of the particle. Overall, at any length scale, the conclusion remains the same: the surface environment has a remarkable impact on nanocluster and nanoparticle energetics and behavior, and care must be taken to model them appropriately to achieve the goal of synthesis by design.

    Cover page: Modeling Surface Stabilization in Nanoclusters and Nanoparticles
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2023)
    Nanoclusters are promising materials for catalysis and sensing due to their large surface areas and unique electronic structures which can be tailored through composition, geometry, and chemistry. However, relationships correlating synthesis parameters directly to outcomes are limited. While previous computational studies have mapped the potential energy surface of specific systems of bare nanoclusters by generating and calculating the energies of reasonable structures, it is known that environmental ions and ligands crucially impact the final shape and size. In this work, phosphine-stabilized gold is considered as a test system and DFT calculations are performed for clusters with and without ligands, producing a database containing >10000 structures for Aun(PH3)m (n ≤ 12). We find that the ligation of phosphines affects the thermodynamic stability, bonding, and electronic structure of Au nanoclusters, specifically such that "hidden" ground state cluster geometries are stabilized that are dynamically unstable in the pure gold system. Further, the addition of phosphine introduces steric effects that induce a transition from planar to nonplanar structures at 4-5 Au atoms rather than up to 13-14 Au atoms, as previously predicted for bare clusters. This work highlights the importance of considering the ligand environment in the prediction of nanocluster morphology and functionality, which adds complexity as well as a rich opportunity for tunability.
      Cover page: Phosphine-Stabilized Hidden Ground States in Gold Clusters Investigated via a Au n (PH3) m DatabaseCreative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2024)
      Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Aun(SCH3)m). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 μs time scale) reveal a mechanism explaining the thermal instability of neutral Au25(SR)18 clusters. Specifically, we observe multiple stages of isomerization of the Au25(SR)18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au25(SR)18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S]n rings.
        Cover page: Gold–Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic PotentialCreative Commons 'BY' version 4.0 license
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2022)
        The recent rise of computational, data-driven research has significant potential to accelerate materials discovery. Automated workflows and materials databases are being rapidly developed, contributing to high-throughput data of bulk materials that are growing in quantity and complexity, allowing for correlation between structural-chemical features and functional properties. In contrast, computational data-driven approaches are still relatively rare for nanomaterials discovery due to the rapid scaling of computational cost for finite systems. However, the distinct behaviors at the nanoscale as compared to the parent bulk materials and the vast tunability space with respect to dimensionality and morphology motivate the development of data sets for nanometric materials. In this review, we discuss the recent progress in data-driven research in two aspects: functional materials design and guided synthesis, including commonly used metrics and approaches for designing materials properties and predicting synthesis routes. More importantly, we discuss the distinct behaviors of materials as a result of nanosizing and the implications for data-driven research. Finally, we share our perspectives on future directions for extending the current data-driven research into the nano realm.
          Cover page: Big Data in a Nano World: A Review on Computational, Data-Driven Design of Nanomaterials Structures, Properties, and SynthesisCreative Commons 'BY' version 4.0 license
          • Article
          • Peer Reviewed
          UC Berkeley Previously Published Works (2024)
          Understanding the mixing behaviour of elements in a multielement material is important to control its structure and property. When the size of a multielement material is decreased to the nanoscale, the miscibility of elements in the nanomaterial often changes from its bulk counterpart. However, there is a lack of comprehensive and quantitative experimental insight into this process. Here we explored how the miscibility of Au and Rh evolves in nanoparticles of sizes varying from 4 to 1 nm and composition changing from 15% Au to 85% Au. We found that the two immiscible elements exhibit a phase-separation-to-alloy transition in nanoparticles with decreased size and become completely miscible in sub-2 nm particles across the entire compositional range. Quantitative electron microscopy analysis and theoretical calculations were used to show that the observed immiscibility-to-miscibility transition is dictated by particle size, composition and possible surface adsorbates present under the synthesis conditions.
            Cover page: Complete miscibility of immiscible elements at the nanometre scale
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