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A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications
Computational catalyst discovery involves the development of microkinetic reactor models based on estimated parameters determined from density functional theory (DFT). For complex surface chemistries, the number of reaction intermediates can be very large, and the cost of calculating the adsorption energies by DFT for all surface intermediates even for one active site model can become prohibitive. In this paper, we have identified appropriate descriptors and machine learning models that can be used to predict a significant part of these adsorption energies given data on the rest of them. Furthermore, our investigations also included the case when the species data used to train the predictive model are of different size relative to the species the model tries to predict—this is an extrapolation in the data space which is typically difficult with regular machine learning models. Due to the relative size of the available data sets, we have attempted to extrapolate from the larger species to the smaller ones in the current work. Here, we have developed a neural network based predictive model that combines an established additive atomic contribution based model with the concepts of a convolutional neural network that, when extrapolating, achieves a statistically significant improvement over the previous models.
Correlating Optical and Structural Properties of CO on Transition Metal Surfaces
Not Available
Atomically precise control of rotational dynamics in charged rare-earth complexes on a metal surface
Abstract Complexes containing rare-earth ions attract great attention for their technological applications ranging from spintronic devices to quantum information science. While charged rare-earth coordination complexes are ubiquitous in solution, they are challenging to form on materials surfaces that would allow investigations for potential solid-state applications. Here we report formation and atomically precise manipulation of rare-earth complexes on a gold surface. Although they are composed of multiple units held together by electrostatic interactions, the entire complex rotates as a single unit when electrical energy is supplied from a scanning tunneling microscope tip. Despite the hexagonal symmetry of the gold surface, a counterion at the side of the complex guides precise three-fold rotations and 100% control of their rotational directions is achieved using a negative electric field from the scanning probe tip. This work demonstrates that counterions can be used to control dynamics of rare-earth complexes on materials surfaces for quantum and nanomechanical applications.
Dynamics of electrified liquid metal surface using shallow water model
A shallow water model that incorporates surface tension and electric field effects is developed to investigate the dynamics of an electrified liquid surface. The computational model is verified against the Zakharov–Kuznetsov equation and is applied to study the growth and damping of the electrified liquid surface. A linear wave analysis is performed under a shallow water theory assuming an analytic solution of the electric field, similar to the Tonks–Frenkel instability. The electrified liquid surface grows or dampens based on the balance of the electric field, surface tension, and gravitational forces. As a result, the numerical results obtained from the electrified shallow water solver are in good agreement with the theoretical analysis.
Thermal and electric field driven rf breakdown precursor formation on metal surfaces
The phenomenon of electric breakdown poses serious challenges to the design of devices that operate in high electric field environments. Experimental evidence points toward breakdown events that are accompanied by elevated temperatures and dark current spikes, which is attributed to high-asperity nanostructure formation that enhances the local electric field and triggers a runaway process. However, the exact mechanistic origin of such nanostructures under typical macroscopic operational conditions of electric field and magnetic-field-mediated heating remains poorly understood. In this work, we simulate the evolution of a copper surface under the combined action of the electric fields and elevated temperatures. Using a mesoscale curvature-driven surface evolution model, we show how a copper surface can undergo a type of dynamical instability that naturally leads to the formation of sharp asperities in realistic experimental conditions. Exploring the combined effect of fields and temperature rise, we identify the critical regimes that allow for the formation of breakdown precursors. The results show that thermoelastic stresses, while not essential, can significantly lower the critical electric field required for runaway surface instability, which is consistent with experimental observations that thermal effects can increase breakdown rates. Published by the American Physical Society 2024
Cooperative mechanisms behind nanoscale smoothing on metal surfaces: From adatom diffusion to step nucleation
Many technologies require stable or metastable surface morphology. Here, in this paper we study the factors that control the metastability of a common feature of rough surfaces: “hillocks.” We use low energy electron microscopy to follow the evolution of the individual atomic steps in hillocks on Pd(111). We show that the uppermost island in the stack often adopts a static, metastable configuration. Modeling this result shows that the degree of the metastability depends on the configuration of steps dozens of atomic layers lower. Our model allows us to link surface metastability to the atomic processes of surface evolution.
Unifying theory of electronic descriptors of metal surfaces upon perturbation
Not provided.
Evaluating Barcode Size and Metal Surface Treatment Options for a Global UF 6 Cylinder Identifier
A team at Oak Ridge National Laboratory tested various barcode sizes, materials, surface finishes, and marking techniques to determine suitable direct part marking techniques and barcode specifications for a new uranium hexafluoride (UF 6 ) cylinder global identifier. This paper describes testing those variables at different read distances and angles with several commercial off-the-shelf direct part mark or barcode readers. This research concluded that a 1.4 in. 2D Data Matrix barcode with a 0.1 in. quiet zone would be appropriate for the machine-readable feature on the proposed UF 6 cylinder global identifier. Testing suggests that this size barcode could be read from an angle of up to 30° over the range of 10–100 cm using multiple commercial off-the-shelf handheld direct part mark or barcode readers. Testing also suggested that barcodes marked on ball-blasted stainless steel with CerMark laser marking ink may be a good choice for the proposed UF 6 cylinder global identifier because they exhibited high contrast and were readable from a desirable range of distances and angles.