The development of more environment-friendly ways to dispose of oil sludge is currently regarded as a hot topic.In this context,gasification technologies are generally seen as a promising way to combine oil sludge wit...The development of more environment-friendly ways to dispose of oil sludge is currently regarded as a hot topic.In this context,gasification technologies are generally seen as a promising way to combine oil sludge with coal–water slurry(CWS)and generate resourceful fuel.In this study,a novel five-nozzle gasifier reactor was analyzed by means of a CFD(Computational fluid dynamic)method.Among several influential factors,special attention was paid to the height-to-diameter ratio of the gasifier and the mixing ratio of oil sludge,which are known to have a significant impact on the flow field,temperature distribution and gasifier performances.According to the numerical results,the optimal height-to-diameter ratio and oil mixing ratio are about 2.4:1 and 20%,respectively.Furthermore,the carbon conversion rate can become as high as 98.55%with the hydrolysis rate reaching a value of 53.88%.The consumption of raw coal and oxygen is generally reduced,while the effective gas production is increased to 50.93 mol/%.展开更多
Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system non...Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system nonlinearity.Here we report a dual-ferroelectric gate-tunable memristor with a dipole coupling effect,achieving enlarged hysteresis,rich temporal dynamics,and nonvolatile heterosynaptic plasticity.By harnessing the dynamic nonlinearity of the dual-ferroelectric memristor,multimodal reservoir computing with an in-material fusion strategy has been achieved,which is demonstrated with a multimodal object recognition task.By exploring the static nonlinearity of the dual-ferroelectric memristor,nonlinear in-memory computing is realized with gate-tunable nonlinear functions,which successfully accelerates the Euclidean distance computation in the K-means clustering task.This work achieves strong coupling between the intrinsic physical dynamics and computational functionalities,offering new opportunities for more efficient hardware-accelerated systems.展开更多
基金Enterprise Horizontal Project(Project Contract No.2021K2450)Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX22_1437).
文摘The development of more environment-friendly ways to dispose of oil sludge is currently regarded as a hot topic.In this context,gasification technologies are generally seen as a promising way to combine oil sludge with coal–water slurry(CWS)and generate resourceful fuel.In this study,a novel five-nozzle gasifier reactor was analyzed by means of a CFD(Computational fluid dynamic)method.Among several influential factors,special attention was paid to the height-to-diameter ratio of the gasifier and the mixing ratio of oil sludge,which are known to have a significant impact on the flow field,temperature distribution and gasifier performances.According to the numerical results,the optimal height-to-diameter ratio and oil mixing ratio are about 2.4:1 and 20%,respectively.Furthermore,the carbon conversion rate can become as high as 98.55%with the hydrolysis rate reaching a value of 53.88%.The consumption of raw coal and oxygen is generally reduced,while the effective gas production is increased to 50.93 mol/%.
基金National Natural Science Foundation of China,Grant/Award Numbers:92164302,8206100486,62404007Guangdong Provincial Key Laboratory of In-Memory Computing Chips,Grant/Award Number:2024B1212020002+5 种基金Shenzhen Science and Technology Program,Grant/Award Number:JCYJ20241202125907011Beijing Natural Science Foundation,Grant/Award Numbers:L234026,L257010,25D40029,25FY3314111 Project,Grant/Award Number:B18001Fok Ying-Tong Education FoundationTencent FoundationChina Postdoctoral Science Foundation,Grant/Award Number:2023M740051。
文摘Nonlinear physical systems hold great promise for energy-efficient and lowhardware-cost information processing.However,their computational capabilities remain constrained by the complexity and tunability of system nonlinearity.Here we report a dual-ferroelectric gate-tunable memristor with a dipole coupling effect,achieving enlarged hysteresis,rich temporal dynamics,and nonvolatile heterosynaptic plasticity.By harnessing the dynamic nonlinearity of the dual-ferroelectric memristor,multimodal reservoir computing with an in-material fusion strategy has been achieved,which is demonstrated with a multimodal object recognition task.By exploring the static nonlinearity of the dual-ferroelectric memristor,nonlinear in-memory computing is realized with gate-tunable nonlinear functions,which successfully accelerates the Euclidean distance computation in the K-means clustering task.This work achieves strong coupling between the intrinsic physical dynamics and computational functionalities,offering new opportunities for more efficient hardware-accelerated systems.
