Ni/TPC催化剂的制备、表征及在秸秆热解燃气重整中的应用

以废弃汽车外轮胎热解后的副产物轮胎热解焦（Tyre pyrolysis char，TPC）为原料，利用均匀沉淀法制备以轮胎焦为载体的负载型Ni/TPC催化剂，采用EDX、SEM、XRD、TG、BET手段对催化剂进行了表征与分析，同时使用管式炉测试了Ni/TPC催化剂在秸秆热解燃气重整中的催化性能，并考察了热解温度、保温时间、镍负载量及催化时间对秸秆热解燃气重整效果的影响。研究结果表明，TPC富含焦和金属，Ni/TPC催化剂分散均匀，热稳定性好，比表面积为62 m²/g。催化剂活性测试显示，Ni/TPC催化剂用于作物秸秆热解燃气重整具有很强的催化活性，可显著提高燃气中可燃气体含量；热解温度在750℃、保温时间10 min、30%的Ni负载量时Ni/TPC催化剂的催化效率最高，连续使用850 min后，燃气中的H₂含量仍相对提高到50%以上，长时间使用后活性结构由Ni₃ZnC_0.7转变成FeNi₃，催化活性依然较强且趋于稳定，TPC可以作为良好的新型镍基催化剂载体。     

基于双向循环神经网络的汉语语音识别*

当前基于深度神经网络模型中,虽然其隐含层可设置多层,对复杂问题适应能力强,但每层之间的节点连接是相互独立的,这种结构特性导致了在语音序列中无法利用上下文相关信息来提高识别效果,而传统的循环神经网络虽然做出了改进,但是只能对上文信息进行利用。针对以上问题,该文采用可以同时利用语音序列中上下文相关信息的双向循环神经网络模型与深度神经网络模型相结合,并应用于语音识别。构建具有5层隐含层的模型,其中第3层为双向循环神经网络结构,其他层采用深度神经网络结构。实验结果表明:加入了双向循环神经网络结构的模型与其他模型相比,较好地提高了识别正确率;噪声对双向循环神经网络汉语识别有重要影响,尤其是训练集和测试集附加噪声类型不同时,单一的含噪声语音的训练模型无法适应不同噪声类型的语音识别;调整神经网络模型中隐含层神经元数量后,识别正确率并不是一直随着隐含层中神经元数量的增加而增加,神经元数量数目增加到一定程度后正确率出现了降低的趋势。     

One step NaBH4 reduction of Pt-Ru-Ni catalysts on different types of carbon supports for direct ethanol fuel cells: Synthesis and characterization

The ternary catalyst Pt₇₅Ru₅Ni₂₀ was conducted on various types of carbon supports including functionalized Vulcan XC-72R (f-CB), functionalized multi-walled carbon nanotubes (f-MWCNT), and mesoporous carbon (PC-Zn-succinic) by sodium borohydride chemical reduction method to improve the ethanol electrooxidation reaction (EOR) for direct ethanol fuel cell (DEFC). It was found that the particle size of the metals on f-MWCNT was 5.20 nm with good particle dispersion. The alloy formation of ternary catalyst was confirmed by XRD and more clearly described by SEM element mapping, which was relevant to the efficiency of the catalysts. Moreover, the mechanism of ethanol electrooxidation reaction based on the surface reaction was more understanding. The activity and stability for ethanol electrooxidation reaction (EOR) were investigated using cyclic voltammetry and chronoamperometry, respectively. The highest activity and stability for EOR were observed from Pt₇₅Ru₅Ni₂₀/f-MWCNT due to a good metal-carbon interaction. Ru and Ni presented in Pt-Ru-Ni alloy improved the activity and stability of ternary catalysts for EOR. Moreover, the reduction of Pt content in ternary catalyst led to the catalyst cost deduction in DEFC.