Hafnia-based ferroelectric materials, like Hf_(0.5)Zr_(0.5)O_(2)(HZO), have received tremendous attention owing to their potentials for building ultra-thin ferroelectric devices. The orthorhombic(O)-phase of HZO is fe...Hafnia-based ferroelectric materials, like Hf_(0.5)Zr_(0.5)O_(2)(HZO), have received tremendous attention owing to their potentials for building ultra-thin ferroelectric devices. The orthorhombic(O)-phase of HZO is ferroelectric but metastable in its bulk form under ambient conditions, which poses a considerable challenge to maintaining the operation performance of HZO-based ferroelectric devices. Here, we theoretically addressed this issue that provides parameter spaces for stabilizing the O-phase of HZO thin-films under various conditions. Three mechanisms were found to be capable of lowering the relative energy of the O-phase, namely, more significant surface-bulk portion of(111) surfaces, compressive c-axis strain,and positive electric fields. Considering these mechanisms, we plotted two ternary phase diagrams for HZO thin-films where the strain was applied along the in-plane uniaxial and biaxial, respectively. These diagrams indicate the O-phase could be stabilized by solely shrinking the film-thickness below 12.26 nm, ascribed to its lower surface energies. All these results shed considerable light on designing more robust and higher-performance ferroelectric devices.展开更多
VO_2 thin films were grown on silicon substrates using Al_2O_3 thin films as the buffer layers. Compared with direct deposition on silicon, VO_2 thin films deposited on Al_2O_3 buffer layers experience a significant i...VO_2 thin films were grown on silicon substrates using Al_2O_3 thin films as the buffer layers. Compared with direct deposition on silicon, VO_2 thin films deposited on Al_2O_3 buffer layers experience a significant improvement in their microstructures and physical properties. By optimizing the growth conditions, the resistance of VO_2 thin films can change by four orders of magnitude with a reduced thermal hysteresis of 4 °C at the phase transition temperature. The electrically driven phase transformation was measured in Pt/Si/Al_2O_3/VO_2/Au heterostructures. The introduction of a buffer layer reduces the leakage current and Joule heating during electrically driven phase transitions. The C–V measurement result indicates that the phase transformation of VO_2 thin films can be induced by an electrical field.展开更多
Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic computing.However,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMO...Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic computing.However,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive units.Here we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy costs.By further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological synapses.The low-temperature process also enables MCA integration on polyimide substrates for applications in flexible electronics.Moreover,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training algorithm.An impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the compensation.The demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.展开更多
The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,w...The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,which has significant applications in heat exchangers and engineering devices.To optimize heat transfer,a liquid film of Cu and TiO_(2)hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance.The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film.The solution of the problem is acquired using the homotopy analysis method HAM,and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis.HAM data is utilized to train the ANN in this study,which uses Cu and TiO_(2)hybrid nanofluids in a variable porous space for unsteady thin film flow,and it is used to train the ANN.The results indicate that Cu and TiO_(2)play a greater role in boosting the rate.展开更多
基金Project supported by the Fund from the Ministry of Science and Technology(MOST)of China(Grant No.2018YFE0202700)the National Natural Science Foundation of China(Grant Nos.11974422 and 12104504)+2 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB30000000)the Fundamental Research Funds for the Central Universitiesthe Research Funds of Renmin University of China(Grant No.22XNKJ30)。
文摘Hafnia-based ferroelectric materials, like Hf_(0.5)Zr_(0.5)O_(2)(HZO), have received tremendous attention owing to their potentials for building ultra-thin ferroelectric devices. The orthorhombic(O)-phase of HZO is ferroelectric but metastable in its bulk form under ambient conditions, which poses a considerable challenge to maintaining the operation performance of HZO-based ferroelectric devices. Here, we theoretically addressed this issue that provides parameter spaces for stabilizing the O-phase of HZO thin-films under various conditions. Three mechanisms were found to be capable of lowering the relative energy of the O-phase, namely, more significant surface-bulk portion of(111) surfaces, compressive c-axis strain,and positive electric fields. Considering these mechanisms, we plotted two ternary phase diagrams for HZO thin-films where the strain was applied along the in-plane uniaxial and biaxial, respectively. These diagrams indicate the O-phase could be stabilized by solely shrinking the film-thickness below 12.26 nm, ascribed to its lower surface energies. All these results shed considerable light on designing more robust and higher-performance ferroelectric devices.
基金financially supported by the National Natural Science Foundation of China (Nos. 51401046, 51572042, 61131005, 61021061, and 61271037)International Cooperation Projects (Nos. 2013HH0003 and 2015DFR50870)+3 种基金the 111 Project (No. B13042)the Sichuan Province S&T program (Nos. 2014GZ0003, 2015GZ0091, and 2015GZ0069)Fundamental Research Funds for the Central Universitiesthe start-up fund from the University of Electronic Science and Technology of China
文摘VO_2 thin films were grown on silicon substrates using Al_2O_3 thin films as the buffer layers. Compared with direct deposition on silicon, VO_2 thin films deposited on Al_2O_3 buffer layers experience a significant improvement in their microstructures and physical properties. By optimizing the growth conditions, the resistance of VO_2 thin films can change by four orders of magnitude with a reduced thermal hysteresis of 4 °C at the phase transition temperature. The electrically driven phase transformation was measured in Pt/Si/Al_2O_3/VO_2/Au heterostructures. The introduction of a buffer layer reduces the leakage current and Joule heating during electrically driven phase transitions. The C–V measurement result indicates that the phase transformation of VO_2 thin films can be induced by an electrical field.
基金supported by the Swedish Strategic Research Foundation(SSF FFL15-0174 to Zhen Zhang)the Swedish Research Council(VR 2018-06030 and 2019-04690 to Zhen Zhang)+1 种基金the Wallenberg Academy Fellow Extension Program(KAW 2020-0190 to Zhen Zhang)the Olle Engkvist Foundation(Postdoc grant 214-0322 to Zhen Zhang).
文摘Memristive crossbar arrays(MCAs)offer parallel data storage and processing for energy-efficient neuromorphic computing.However,most wafer-scale MCAs that are compatible with complementary metal-oxide-semiconductor(CMOS)technology still suffer from substantially larger energy consumption than biological synapses,due to the slow kinetics of forming conductive paths inside the memristive units.Here we report wafer-scale Ag_(2)S-based MCAs realized using CMOS-compatible processes at temperatures below 160℃.Ag_(2)S electrolytes supply highly mobile Ag+ions,and provide the Ag/Ag_(2)S interface with low silver nucleation barrier to form silver filaments at low energy costs.By further enhancing Ag+migration in Ag_(2)S electrolytes via microstructure modulation,the integrated memristors exhibit a record low threshold of approximately−0.1 V,and demonstrate ultra-low switching-energies reaching femtojoule values as observed in biological synapses.The low-temperature process also enables MCA integration on polyimide substrates for applications in flexible electronics.Moreover,the intrinsic nonidealities of the memristive units for deep learning can be compensated by employing an advanced training algorithm.An impressive accuracy of 92.6%in image recognition simulations is demonstrated with the MCAs after the compensation.The demonstrated MCAs provide a promising device option for neuromorphic computing with ultra-high energy-efficiency.
文摘The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,which has significant applications in heat exchangers and engineering devices.To optimize heat transfer,a liquid film of Cu and TiO_(2)hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance.The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film.The solution of the problem is acquired using the homotopy analysis method HAM,and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis.HAM data is utilized to train the ANN in this study,which uses Cu and TiO_(2)hybrid nanofluids in a variable porous space for unsteady thin film flow,and it is used to train the ANN.The results indicate that Cu and TiO_(2)play a greater role in boosting the rate.
