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Yiheng Dai

Publications and source records attributed to Yiheng Dai.

4 recordsLinked to original sources

Tracking atomic-scale interdiffusion in immiscible bimetallic nanoparticles via four-dimensional electron tomography

The interdiffusion of immiscible elements is generally considered both thermodynamically unfavorable and kinetically hindered. At the nanoscale, however, the mixing behavior of multielements materials often diverges from bulk equilibrium, yet a quantitative, atomically resolved description of this transformation has remained challenging. Using ex situ four dimensional atomic resolution electron tomography combined with in situ scanning transmission electron microscopy, here we reveal the atomic scale miscible transition driven by interdiffusion in immiscible PdIr nanoparticles at temperatures far below the melting point. The pathway involves surface reconstruction atom hopping at 200oC and surface flattening at 300oC, followed by a critical transition at 400oC where Ir interfacial diffusion and discrete Ir intermediates drive miscible intermixing. Upon reaching the nanoscale melting point 900oC, collective inward Ir diffusion yields the thermodynamically stable IrPd configuration. Our findings provide quantitative atomic scale insights into how metastable nanostructures evolve through distinct intermediates, offering a design framework for advanced multielement materials.

cond-mat.mtrl-sci

Tracking four-dimensional atomic evolutions of single nanocatalysts throughout the life cycles

Structural changes induced by chemical reactions critically determine the catalytic performance and mechanism. However, precise tracking of the three-dimensional (3D) atomic structural evolution of individual bimetallic nanocatalysts remains challenging. Here we develop four-dimensional electrocatalytic atomic-resolution electron tomography, a method for directly tracking 3D atomic rearrangements in identical nanoparticles by electrocatalytic reactions. Using Pd-Pt bimetallic nanoparticles as a model system, we capture the atomic evolution of single nanocatalysts throughout electrocatalytic cycles. We observe two stages of evolutions: surface reconstruction and atom leaching, which are corroborated with the voltage-dependent behaviors probed by in situ electrochemical transmission electron microscopy. We identify chemical short-range order at atomic level and further reveal anisotropic chemical redistributions across different crystallographic orientations. These findings highlight the necessity of incorporating 3D spatiotemporal and chemical evolutions into the rational design of functional nanocatalysts in the future.

cond-mat.mtrl-sci

MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows

Machine learning (ML) is increasingly becoming a common tool in computational chemistry. At the same time, the rapid development of ML methods requires a flexible software framework for designing custom workflows. MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows. This open-source package provides plenty of choice to the users who can run simulations with the command line options, input files, or with scripts using MLatom as a Python package, both on their computers and on the online XACS cloud computing at XACScloud.com. Computational chemists can calculate energies and thermochemical properties, optimize geometries, run molecular and quantum dynamics, and simulate (ro)vibrational, one-photon UV/vis absorption, and two-photon absorption spectra with ML, quantum mechanical, and combined models. The users can choose from an extensive library of methods containing pre-trained ML models and quantum mechanical approximations such as AIQM1 approaching coupled-cluster accuracy. The developers can build their own models using various ML algorithms. The great flexibility of MLatom is largely due to the extensive use of the interfaces to many state-of-the-art software packages and libraries.

physics.chem-ph

Janus icosahedral particles: amorphization driven by three-dimensional atomic misfit and edge dislocation compensation

Icosahedral nanoparticles composed of fivefold twinned tetrahedra have broad applications. The strain relief mechanism and angular deficiency in icosahedral multiply twinned particles are poorly understood in three dimensions. Here, we resolved the three-dimensional atomic structures of Janus icosahedral nanoparticles using atomic resolution electron tomography. A geometrically fivefold face consistently corresponds to a less ordered face like two hemispheres. We quantify rich structural variety of icosahedra including bond orientation order, bond length, strain tensor; and packing efficiency, atom number, solid angle of each tetrahedron. These structural characteristics exhibit two-sided distribution. Edge dislocations near the axial atoms and small disordered domains fill the angular deficiency. Our findings provide new insights how the fivefold symmetry can be compensated and the geometrically-necessary internal strains relived in multiply twinned particles.

cond-mat.mtrl-sci