Engineering topics

Liu, Bin [Kansas State Univ., Manhattan, KS (United States)] (ORCID:0000000178907612)

Publications and source records attributed to Liu, Bin [Kansas State Univ., Manhattan, KS (United States)] (ORCID:0000000178907612).

4 records

All sources NASA NTRS DOE OSTI

DOE OSTI2025

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗

DOE OSTI2025

Atomistic Simulations of Thermal and Chemical Expansions of PrNi x Co 1‐x O 3‐δ Accelerated by Machine Learning Potentials

The electrodes and solid-state electrolytes in protonic ceramic electrochemical cells (PCECs) experience significant lattice expansions when exposed to high steam concentrations at elevated temperatures. In this paper, phonon calculations based on a new machine learning potential (MLP) are employed to elucidate the volume expansions of the proton-conducting PrNi x Co 1-x O 3-δ (PNC) lattices, manifested under a combined influence of oxygen vacancies (V$^{\cdot\cdot}_O$ ) and proton uptake (OH$^{\cdot}_O$ ) in the bulk at varying Ni/Co occupancies. It is revealed that the Ni/Co occupancy contributes to thermal and chemical expansions differently, where thermal expansions are related to Co occupancy. In contrast, chemical expansions are more closely associated with the Ni occupancy. Both V$^{\cdot\cdot}_O$ and OH$^{\cdot}_O$ lead to higher thermal expansions when compared to the pristine PNC. The temperature increase will negatively impact the hydration-induced chemical expansions. For combined thermal and chemical expansions, it is predicted that the strategies that boost the PCEC's electrochemical performance may harm the electrode–electrolyte interfacial stability, when the Ni occupancy is high, due to severe chemical expansions. Mitigating chemical expansions of the Ni-abundant PNC will benefit the interfacial stability. Finally, the presented computational methods for phonon calculations, based on emerging machine learning interatomic potential techniques are anticipated to have a lasting impact on future PCEC development.

computational prediction↗

DOE OSTI2025

Promotional Effect of ZnO and ZrO 2 in K-Doped Fe Catalysts for CO 2 Hydrogenation to Light Olefins

Promoters play a critical role in tuning the activity and selectivity of Fe catalysts in CO 2 hydrogenation to produce light olefins, which are key building blocks in the petrochemical industry. Herein, by a combined experimental and theoretical approach, we show that high and stable performance of Fe catalysts could be achieved by taking advantage of the promotional effect of both Zn and Zr. Structural characterization indicates that ZnO could improve the dispersion and reducibility of Fe oxides and facilitate the formation of active Fe carbide species, whereas ZrO 2 could stabilize the structure and catalytic performance, especially the selectivity of hydrocarbon products. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments suggest that carbonate, bicarbonate, formate, and methoxy are essential intermediates in the CO 2 hydrogenation to hydrocarbon products, including paraffins and olefins. The conversion kinetics of each intermediate species are dependent on the type of promoters as well as the phase structure of the active Fe species. DFT calculations revealed a strong correlation between the formation energy of surface oxygen vacancies and that of Fe carbide species in promoted Fe oxides, in accordance with experimental results. Moreover, the calculated energy profiles of CO 2 hydrogenation over different catalysts indicate that Zn could promote the activation of CO 2 and its transformation to the oxygenate intermediates, while Zr could facilitate the conversion of oxygenates to hydrocarbon precursors. Finally, the discrepancies in the evolution trend of various intermediate species on promoted Fe catalysts in the transient DRIFTS experiments can be rationalized by the differences in energy barriers of elementary or rate limiting steps.

CO2 conversion↗

DOE OSTI2025

Data-Driven Approach for Controlled Icosahedral Boron- Rich Compound Growth

This final technical report summarizes the research accomplishments and research highlights at the end of the funding period. This project aimed to leverage existing and new computational data produced from first-principles and molecular dynamics simulations to understand the thermodynamic, mechanical, and electronic properties of icosahedral boron compounds. The goal is to achieve targeted material properties by controlling the synthesis routes of these boron-rich compounds.

36 MATERIALS SCIENCE↗