42 citations · 83 across the 9 of their papers we have counts for
9 papers
A machine-learning-driven dataset of 144,111 polycyclic aromatic hydrocarbon infrared spectra for interpreting aromatic infrared bands
Xinghong Mai, Zu-Jia Lu, Zhao Wang
The interpretation of interstellar aromatic infrared bands (AIBs) relies on reference spectral libraries, but the chemical space covered by existing databases remains incomplete re…
Graph Neural Network Prediction of Infrared Spectra of Interstellar Polycyclic Aromatic Hydrocarbons
Guoqing Tang, Jiang He, Zhao Wang +1
Polycyclic aromatic hydrocarbons (PAHs) are recognized as the primary contributors to the aromatic infrared bands (AIBs) widely observed in space. However, analyzing these AIBs rem…
Full-spectrum infrared fingerprinting: A transformative AI paradigm for interstellar polycyclic aromatic hydrocarbons
Zhao Wang
In the era of high-sensitivity infrared (IR) astronomy, traditional manual diagnostics are no longer sufficient to harvest the complex physical insights hidden within interstellar…
Evolution of Fullerenes in Circumstellar Envelopes by Carbon Condensation: Insights from Reactive Molecular Dynamics Simulations
Zhisen Meng, Zhao Wang
Fullerenes, including \ce{C60} and \ce{C70}, have been detected in various astronomical environments. Understanding how their structures evolve over time is essential for gaining i…
Machine-learning identified molecular fragments responsible for infrared emission features of polycyclic aromatic hydrocarbons
Zhisen Meng, Yong Zhang, Enwei Liang +1
Machine learning feature importance calculations are used to determine the molecular substructures that are responsible for mid and far-infrared (IR) emission features of neutral p…
Catalytic role of HI in the interstellar synthesis of complex organic molecule
Shuming Yang, Peng Xie, Enwei Liang +1
Using quantum chemical calculations, we model the pathways for synthesizing two purine nucleobases, adenine and guanine, in the gas-phase interstellar environment, surrounded by ne…
Optical Properties of Crich (C, SiC and FeC) Dust Layered Structure of Massive Stars
Ruiqing Wu, Mengqiu Long, Xiaojiao Zhang +9
The composition and structure of interstellar dust are important and complex for the study of the evolution of stars and the \textbf{interstellar medium} (ISM). However, there is a…
Machine Learning interpretation of the correlation between infrared emission features of interstellar polycyclic aromatic hydrocarbons
Zhisen Meng, Xiaosi Zhu, Peter Kovacs +2
Supervised machine learning models are trained with various molecular descriptors to predict infrared emission spectra of interstellar polycyclic aromatic hydrocarbons. We demonstr…
Machine-learning prediction of infrared spectra of interstellar polycyclic aromatic hydrocarbons
Peter Kovacs, Xiaosi Zhu, Jesus Carrete +2
We design and train a neural network (NN) model to efficiently predict the infrared spectra of interstellar polycyclic aromatic hydrocarbons (PAHs) with a computational cost many o…