Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions....Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions.The potential of LNNs in telecommunications is explored in this paper.First,we illustrate the mechanisms of LNNs and highlight their unique advantages over traditional networks.Then we explore the opportunities that LNNs bring to future wireless networks.Furthermore,we discuss the challenges and design directions for the implementation of LNNs.Finally,we summarize the performance of LNNs in two case studies.展开更多
Three kinds of rare earth nitrates were adopted to sodium molybdate to get three kinds of LnN-M compounded inhibitors （La（NO3）3＋Na2MoOa（LaN-M）, Ce（NO3）3＋Na2MoOn（CeN-M）, Pr（NO3）3＋Na2MoO4（PrN-M））. The c...Three kinds of rare earth nitrates were adopted to sodium molybdate to get three kinds of LnN-M compounded inhibitors （La（NO3）3＋Na2MoOa（LaN-M）, Ce（NO3）3＋Na2MoOn（CeN-M）, Pr（NO3）3＋Na2MoO4（PrN-M））. The combination of weight-loss method and the electrochemical test, was used to evaluate and analyze the corrosion inhibition efficiency of these LnN-M inhibitors to make the research on their corrosion inhibition performance, and the sequential order of their performance was found as follows： CeN-M〉 LaN-M〉PrN-M, among which, the inhibition efficiency of CeN-M for the X70 steel could reach 98.21%. The synergism parameters were calculated by weight-loss method, these computational data indicated that the synergistic effect between rare earth nitrates and sodium molybdate was obvious and significant. Surface morphology, chemical composition and phase components of the precipitation films were tested for discussing the mechanism of LnN-M inhibitors. The outer electronic configuration of the lanthanide was found to have an important influence on the inhibition efficiency. The CeN-M inhibitor was discovered to have the best inhibition effect with the amorphous cerium oxides. The results of this research revealed that the precipitation films formed on the surface of the steel samples had a crucial influence on the inhibition efficiencies after adding LnN-M inhibitors.展开更多
基金supported by the China National Key R&D Program under Grant Nos.2021YFA1000500 and 2023YFB2904804National Natural Science Foundation of China under Grant Nos.62331023,62101492,62394292 and U20A20158+1 种基金Zhejiang Provincial Natural Science Foundation of China under Grant No.LR22F010002Zhejiang Provincial Science and Technology Plan Project under Grant No.2024C01033。
文摘Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions.The potential of LNNs in telecommunications is explored in this paper.First,we illustrate the mechanisms of LNNs and highlight their unique advantages over traditional networks.Then we explore the opportunities that LNNs bring to future wireless networks.Furthermore,we discuss the challenges and design directions for the implementation of LNNs.Finally,we summarize the performance of LNNs in two case studies.
基金Foundation of Material Corrosion and Protection Key Laboratory of Sichuan Province(2012CL04)Innovative Research Team of Southwest Petroleum University(2012XJZT002) for financial support
文摘Three kinds of rare earth nitrates were adopted to sodium molybdate to get three kinds of LnN-M compounded inhibitors （La（NO3）3＋Na2MoOa（LaN-M）, Ce（NO3）3＋Na2MoOn（CeN-M）, Pr（NO3）3＋Na2MoO4（PrN-M））. The combination of weight-loss method and the electrochemical test, was used to evaluate and analyze the corrosion inhibition efficiency of these LnN-M inhibitors to make the research on their corrosion inhibition performance, and the sequential order of their performance was found as follows： CeN-M〉 LaN-M〉PrN-M, among which, the inhibition efficiency of CeN-M for the X70 steel could reach 98.21%. The synergism parameters were calculated by weight-loss method, these computational data indicated that the synergistic effect between rare earth nitrates and sodium molybdate was obvious and significant. Surface morphology, chemical composition and phase components of the precipitation films were tested for discussing the mechanism of LnN-M inhibitors. The outer electronic configuration of the lanthanide was found to have an important influence on the inhibition efficiency. The CeN-M inhibitor was discovered to have the best inhibition effect with the amorphous cerium oxides. The results of this research revealed that the precipitation films formed on the surface of the steel samples had a crucial influence on the inhibition efficiencies after adding LnN-M inhibitors.
