传统基于张量分解的稀疏阵列波达方向(direction of arrival,DOA)估计,通常将协方差矩阵直接进行划分来构建满秩张量,但这种方法没有考虑数据间的结构信息,使得信息利用不充分。针对这一问题,提出了一种基于数据间耦合关系的张量分解算...传统基于张量分解的稀疏阵列波达方向(direction of arrival,DOA)估计,通常将协方差矩阵直接进行划分来构建满秩张量,但这种方法没有考虑数据间的结构信息,使得信息利用不充分。针对这一问题,提出了一种基于数据间耦合关系的张量分解算法。根据信息间的结构特点,构建在俯仰和方位维度能分别利用耦合特性的两个三阶张量。通过张量分解从中估计出两组角度值,将其中利用耦合特性估计出的角度值作为DOA值,伴随产生的估计值用作角度匹配。仿真结果验证了所提算法可进一步提升对数据间耦合信息的利用,有效提高二维DOA估计的精度。展开更多
Electrocatalytic urea synthesis provides a favorable strategy for conventional energy-consuming urea synthesis,but achieving large-scale catalyst synthesis with high catalytic efficiency remains challenging.Herein,we ...Electrocatalytic urea synthesis provides a favorable strategy for conventional energy-consuming urea synthesis,but achieving large-scale catalyst synthesis with high catalytic efficiency remains challenging.Herein,we developed a simple method for the preparation of a series of FeNi-alloy-based catalysts,named FeNi@nC-T(n represents the content of nanoporous carbon as 1,3,5,7 or 9 g and T=900,950,1000 or 1100°C),for highly performed urea synthesis via NO_(3)−and CO_(2)co-reduction.The FeNi@7C-1000 achieved a high urea yield of 1041.33 mmol h^(−1)gFeNi^(−1)with a Faradaic efficiency of 15.56%at–1.2 V vs.RHE.Moreover,the scale-up synthesized FeNi@7C-950-S(over 140 g per batch)was achieved with its high catalytic performance and high stability maintained.Mechanism investigation illuminated that the Ni and Fe sites catalyze and stabilize the key*CO and*N intermediates and minimize the C–N coupling reaction barriers for highly efficient urea synthesis.展开更多
文摘传统基于张量分解的稀疏阵列波达方向(direction of arrival,DOA)估计,通常将协方差矩阵直接进行划分来构建满秩张量,但这种方法没有考虑数据间的结构信息,使得信息利用不充分。针对这一问题,提出了一种基于数据间耦合关系的张量分解算法。根据信息间的结构特点,构建在俯仰和方位维度能分别利用耦合特性的两个三阶张量。通过张量分解从中估计出两组角度值,将其中利用耦合特性估计出的角度值作为DOA值,伴随产生的估计值用作角度匹配。仿真结果验证了所提算法可进一步提升对数据间耦合信息的利用,有效提高二维DOA估计的精度。
文摘Electrocatalytic urea synthesis provides a favorable strategy for conventional energy-consuming urea synthesis,but achieving large-scale catalyst synthesis with high catalytic efficiency remains challenging.Herein,we developed a simple method for the preparation of a series of FeNi-alloy-based catalysts,named FeNi@nC-T(n represents the content of nanoporous carbon as 1,3,5,7 or 9 g and T=900,950,1000 or 1100°C),for highly performed urea synthesis via NO_(3)−and CO_(2)co-reduction.The FeNi@7C-1000 achieved a high urea yield of 1041.33 mmol h^(−1)gFeNi^(−1)with a Faradaic efficiency of 15.56%at–1.2 V vs.RHE.Moreover,the scale-up synthesized FeNi@7C-950-S(over 140 g per batch)was achieved with its high catalytic performance and high stability maintained.Mechanism investigation illuminated that the Ni and Fe sites catalyze and stabilize the key*CO and*N intermediates and minimize the C–N coupling reaction barriers for highly efficient urea synthesis.
