铜基电催化剂在CO_(2)还原反应(CO_(2)RR)中产高附加值产物的潜力巨大,是实现碳负排放的一种很有前景的途径。同时,安培级电流是实现多碳(C_(2+))产业化的关键。然而,由于复杂的电子传递过程和不可避免的副反应,工业电流密度下的C_(2+)...铜基电催化剂在CO_(2)还原反应(CO_(2)RR)中产高附加值产物的潜力巨大,是实现碳负排放的一种很有前景的途径。同时,安培级电流是实现多碳(C_(2+))产业化的关键。然而,由于复杂的电子传递过程和不可避免的副反应,工业电流密度下的C_(2+)选择性仍然不令人满意。在此,我们开发了一种碳修饰策略来优化局部环境并调节中间产物在Cu活性位点的吸附。结果表明,Cu-Cx催化剂(x为催化剂中C的原子百分数)能有效催化CO_(2)RR生成C_(2+)产物。特别是在流动池中,Cu-C6%在−0.72 V vs.RHE(相对可逆氢电极)条件下,电流密度可达1.25 A∙cm^(−2),C_(2)H_(4)和C_(2+)产物的法拉第效率(FE)分别可达54.4%和80.2%。原位光谱分析和密度泛函理论(DFT)计算表明,C的存在调节了*CO在Cu表面的吸附,降低了C―C耦合的能垒,从而促进了C_(2+)产物的生成。展开更多
A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequ...A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequency domains is given.The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel.The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate.The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm.The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.展开更多
文摘铜基电催化剂在CO_(2)还原反应(CO_(2)RR)中产高附加值产物的潜力巨大,是实现碳负排放的一种很有前景的途径。同时,安培级电流是实现多碳(C_(2+))产业化的关键。然而,由于复杂的电子传递过程和不可避免的副反应,工业电流密度下的C_(2+)选择性仍然不令人满意。在此,我们开发了一种碳修饰策略来优化局部环境并调节中间产物在Cu活性位点的吸附。结果表明,Cu-Cx催化剂(x为催化剂中C的原子百分数)能有效催化CO_(2)RR生成C_(2+)产物。特别是在流动池中,Cu-C6%在−0.72 V vs.RHE(相对可逆氢电极)条件下,电流密度可达1.25 A∙cm^(−2),C_(2)H_(4)和C_(2+)产物的法拉第效率(FE)分别可达54.4%和80.2%。原位光谱分析和密度泛函理论(DFT)计算表明,C的存在调节了*CO在Cu表面的吸附,降低了C―C耦合的能垒,从而促进了C_(2+)产物的生成。
基金supported by the National Natural Science Foundation of China(60972056)the Innovation Foundation of Shanghai Education Committee(09ZZ89)Shanghai Leading Academic Discipline Project and STCSM(S30108and08DZ2231100)
文摘A compressed sensing（CS） based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel.A compressive basis expansion channel model with sparsity in both time and frequency domains is given.The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel.The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate.The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm.The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.
