Quantitative Structure–Activity Relationship Studies on Alkane Chemistry Tuning Ice Nucleation

Abstract

Understanding how surface chemistry influences ice nucleation is essential for both forecasting icing phenomena and designing surfaces with desired ice-control abilities. Although alkylating is one of the most common and simplest ways for surface chemical modification, the effect of alkane chemistry on ice nucleation remains ambiguous as a result of the usually accompanying interferences of substrate morphology or heat transfer. Here, we decouple the effect of alkane chemistry on ice nucleation by investigating the ice nucleation behaviors on alkane self-assembled monolayers (SAMs) with atomic-level roughness and (sub)nanoscale thickness. Our results indicate that the introduction of alkane chemistry leads to decreased ice nucleation activities, i.e., increased anti-icing abilities, and the longer alkyl chain endows the SAM surface with the more inert ability to promote ice nucleation. The alkyl-chain-length-dependent ice nucleation activities are found to be correlated with the surface polarity. This work sheds light on a long-standing question of how alkane chemistry influences ice nucleation and offers a useful strategy for tuning ice nucleation.

SaPt-CNN-LSTM-AR-EA: a hybrid ensemble learning framework for time series-based multivariate DNA sequence prediction

“…Single prediction models mainly include autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), autoregressive Integrated moving average (ARIMA), SVM, ANN-based model, and machine learning-based model. Hybrid models can obtain more accurate prediction ( Bai et al, 2022 ; Han et al, 2019 ; James & Tripathi, 2021 ; Zhang et al, 2021 , 2023 ). For example, various meta-heuristic algorithms are used to optimize the weights and thresholds of ANN, such as differential evolution (DE), simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA) ( Chu et al, 2022 ; Gugler & Reiher, 2022 ; Torkey et al, 2021 , 2022 ; Xia et al, 2022 ; Zhang, Yan & Aasma, 2020 ).…”