Metal-Core-Specific Screening with Machine Learning: Accelerating the Discovery of Metal Oxide Clusters for Enhanced EUV Lithography Resolution.

Obtaining effective extreme ultraviolet lithography (EUVL) materials for pragmatic applications remains challenging. The experimental design and conventional theoretical prediction are time-consuming and costly and hardly affordable to accelerate the discovery of commercial EUVL materials. In this work, we employed the machine learning (ML) technique to predict the ionization potential of promising EUVL materials, which is closely related to the photoresists' solubility switch.

Prediction of vibrational spectrum and thermodynamic properties for phosphorus mononitride.

In this work, an accurate potential energy curve (PEC) for the ground electronic state of phosphorus mononitride (PN) molecule has been determined from a variationally improved Hulburt-Hirschfelder (VIHH) oscillator model in conjunction with the experimental spectral constants (D,ω,ωx,B,α,r). We have numerically solved the Schrödinger equation for the VIHH potential using the LEVEL program, obtaining the pure vibrational spectrum that converges to the dissociation limit. In addition, the partition functions of PN molecule are calculated using the full rovibrational energies.

Investigation of the Oxidation Behavior of CrMnFeTaW and Microdefects Evolution Induced by Hydrogen Ions before and after Oxidation.

The oxidation behavior of body-centered cubic (bcc) structure CrMnFeTaW refractory high-entropy alloy (RHEA) and the microdefects induced by hydrogen ions before and after oxidation were investigated. The results revealed that compared with oxidizing CrMnFeTaW at 800 °C (6.7 °C/min) for 4 h (ST3, Ar:O = 3:1), the heating procedure of oxidizing CrMnFeTaW at 300 °C (6 °C/min) for 2 h and then increased to 800 °C (5 °C/min) for 4 h is more conducive to the production of oxides without spalling on the surface, i.

Investigation into surface composition of nitrogen-doped niobium for superconducting RF cavities.

Systematic analysis of the surface morphology, crystalline phase, chemical composition and elemental distribution along depth for nitrogen-doped niobium was carried out using different methods of characterization, including Scanning Electron Microscopy (SEM), Atomic-Force Microscopy (AFM), Grazing Incidence X-ray Diffraction (GIXRD), Rutherford Backscattering Spectrometry (RBS) and layer-by-layer X-ray Photoelectron Spectroscopy (XPS) analysis. The results showed that, after nitrogen doping, the surface was covered by densely distributed trigonal precipitates with an average crystallite size of 32 ± 8 nm, in line with the calculation result (29.9 nm) of nitrogen-enriched-NbN from GIXRD, demonstrating the phase composition of trigonal precipitates.