22:T438,Potential of zero charge (PZC) is an important reference for understanding the interface charge and structure at a given potential, and its difference from the work function of metal surface (Φ_M) is defined as the Volta potential difference (ΔΦ). In this work, we model 11 metal/water interfaces with ab initio molecular dynamics. Interestingly, we find ΔΦ is linearly correlated with the adsorption energy of water (E_ads) on the metal surface. It is revealed that the size of E_ads directly determines the coverage of chemisorbed water on the metal surface and accordingly affects the interface potential change caused by electron redistribution (ΔΦ_el). Moreover, ΔΦ is dominated by the electronic component ΔΦ_el with little orientational dipole contributing, which explains the linear correlation between ΔΦ and E_ads. Finally, it is expected that this correlation can be helpful for effectively estimating the ΔΦ_el and PZC of other metal surfaces in the future work.23:T479,Although autonomous driving technology has made tremendous progress in recent years, it is still challenging to predict the intentions and trajectories of pedestrians. The state-of-the-art methods suffer from two problems. (1) Existing works consider these two tasks separately, ignoring the connection between them. (2) The selection and integration of inputs for these tasks are not well designed. In this paper, these two tasks are taken into consideration in a unified model. In this way, the information provided by the labels of each other is shared, improving the performance of both tasks. Besides, in addition to the bounding boxes and speeds, orientation and road semantic segmentation features are taken into consideration to show the potential intention and road context of the pedestrian. And all the inputs are weighted by an attention module before integration. Meanwhile, a Transformer encoder is applied in our method to extract the temporal information from the fused feature sequence. Our method outperforms all previous models for both trajectory prediction and intention prediction tasks on the JAAD dataset and PIE dataset.

#	Concept	H-Index	Publications	Citations
1	Engineering	4	4	308
2	Medicine	2	2	258
3	Applied Physics	1	1	14
4	Biomedical Engineering	1	1	189
5	Chemistry	1	1	14

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