Advances in electrocatalytic CO2 reduction with copper-based catalysts
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摘要:
碳排放导致的全球气候问题引起全世界的关注。利用可再生能源产生的电力驱动催化剂电催化CO2还原为碳氢燃料或化学原料具有广阔前景。过渡金属相对低廉的成本和优良的催化性能成为催化工程的首选。本文综述了铜衍生催化剂包括金属Cu、Cu单原子、Cu氧化物、Cu合金、Cu金属有机框架、铜酞菁和Cu-非金属化合物在电催化CO2还原的应用现状,阐明了CO2还原为不同碳产物的可能路径与机理。此外,在分析目前研究的重点与不足的基础上提出了未来可能的发展方向,为碳排放控制和高效催化剂的设计与制备提供参考。
Abstract:The global climate issues caused by carbon emissions have attracted worldwide attention. The electrocatalytic CO2 reduction to hydrocarbon fuels or chemical feedstocks by catalysts driven by electricity generated from renewable energy sources has a promising future. Transition metals with a relatively low cost and excellent catalytic performance have become the preferred choice for catalytic engineering. This work reviewed the current status of copper-derived catalysts, including monolithic copper, Cu single atom, copper oxides, copper alloys, copper-metal organic frameworks, copper phthalocyanines, and copper-nonmetallic compounds for electrocatalytic CO2 reduction, and elucidated the possible pathways and mechanisms for the reduction of CO2 to different carbon products. In addition, possible future development directions were proposed, providing reference for carbon emission control and the design and preparation of efficient catalysts based on the analysis of the highlights and shortcomings of the current research.
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Keywords:
- CO2 /
- electrocatalytic reduction /
- copper catalyst /
- hydrocarbon fuel
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铜阳极泥富含大量的Au、Ag等贵金属和Se稀散非金属[1-3]，加压酸浸工艺作为处理铜阳极泥的重要湿法冶金工艺之一，常以硫酸为浸出剂、氧气为氧化剂，并在高压条件下强化浸出，富集阳极泥中各金属物质.而立式釜因其高效的搅拌混合效率成为目前加压酸浸铜阳极泥[4, 5]的主要设备.据文献[6]记载，20年前化工工业产量约为7 500亿美元，其中与搅拌相关的产量值占比近一半.在多相搅拌过程中，搅拌转速、硫酸浓度、液固比、温度等条件的变化均能使气液固三相间的相间作用发生变化，进而改变多相混合流场，因此准确获取工艺参数对立式釜内气-液-固搅拌混合效率的影响规律对于提升工业铜阳极泥搅拌混合效率具有重要意义.
在实际工业生产中，立式釜内多相流体的流动非常复杂，难以进行有效的实时监测，因此通过实验分析立式釜内多相流场具有周期长、成本高、监测难等局限性.计算流体力学（CFD）[7-9]因其高效率低成本的特性成为研究多相混合流场不可或缺的方法之一. Yang等[10]对比多相流模拟中常用的“两流体模型”和“三流体模型”，发现由于“两流体模型”将三相间的相互作用简化为两相间的作用，因此模拟结果与实验结果相差较大，而“三流体模型”考虑气-液-固三相间的相互影响，模拟结果更加准确.因此采用欧拉-欧拉“三流体模型”模拟气液固三相流场，建立三相反应器内功率与气液体积传质系数的经验关联式. Grevskott等[11]采用“两流体模型”模拟气-液-固三相浆状流动，由于未考虑固液两相间的相对滑移速度，模拟结果与实验结果具有较大偏差. B.N.Murthy等[12]采用Fluent软件对三相搅拌分散体系进行了模拟，研究搅拌筒直径、桨径、桨型、桨叶位置、转速、颗粒尺寸、固相浓度和氧气入口流速对三相混合的影响，并将三相模拟结果与Chapman、Rewatkar、Zhu和Wu的实验结果比对，具有良好的一致性. Padial等[13]对鼓泡塔三相反应器进行了研究，同时考虑各相间的曳力作用，发现在多相混合过程中，颗粒会受到流体的作用力呈现跟随流体运动的趋势，而这种趋势在围绕气泡的颗粒上体现的尤为明显，因此气固间的相间曳力模型与气液间相间曳力是一致的. Panneerselvam等[14]研究桨型、颗粒直径和通气量对临界转速的影响，结果表明相同的操作条件下，PBTD桨的搅拌功率仅为DT桨的一半；颗粒直径的增大导致临界悬浮转速也随之增大；通气量的增加使得临界转速持续增加，且通气量的增加速度相同时，临界转速增加的程度与桨型相关.
多相搅拌模拟中常采用单因素变量法研究各因素对搅拌流场的影响，但各个因素对搅拌混合流场影响程度的主次顺序尚不明确.灰色关联分析是通过多个因素间关联性大小的量度以寻求系统中各因素之间的主次关系，找到影响混合效果的重要因素并建立灰色关联评价模型，最终得到各因素之间发展趋势的相似或相异程度，因此被初步应用于冶金及其它工业技术反应器结构优化和工艺参数分析中[15, 16].
通过采用CFD技术对立式釜内H2SO4-O2-铜阳极泥颗粒三相搅拌体系进行了模拟仿真，并结合正交设计实验和灰色关联分析方法，选取4种工艺参数（搅拌转速、H2SO4溶液浓度、液固比、温度）为研究对象，以立式釜混合性能（截面气含率、湍流动能、硫酸平均速度、铜阳极泥平均速度）为评价指标，进行多目标综合评价，研究各工艺参数对混合性能影响程度的主次顺序.
1 立式釜H2SO4-O2-铜阳极泥三相搅拌模拟
1.1 物理模型
将工业上立式釜模型做必要简化，忽略所有与流体运动无关的区域，简化后的模型及参数如图 1和表 1所示.由于气液固三相的密度、黏度等物理性质均受压力影响，大大增加了模拟过程中的计算成本，因此为简化三相混合过程，文中采用常压搅拌模拟.为研究搅拌转速、液固比、硫酸质量分数、温度对立式釜内三相搅拌混合性能的影响，选取4种搅拌转速（120 r/min、210 r/min、300 r/min、400 r/min），4种液固比（4:1、6:1、8:1、10:1），4种硫酸质量分数（10 %、20 %、30 %、40 %），4种温度（293.15 K、323.15 K、353.15 K、393.15 K）共13种工况条件进行三相搅拌模拟.
表 1 立式釜结构参数Table 1. Structural parameters of vertical kettle
1.2 模拟物系
模拟物系为H2SO4-O2-铜阳极泥颗粒三相，其中铜阳极泥颗粒密度为1 450 kg/m3、黏度为0.001 003 kg/（m·s），颗粒平均粒径为74 μm；不考虑气泡的破碎和聚并，因此O2取单一气泡直径，值为0.003 m；H2SO4溶液的物理性质会随温度和质量分数的改变而发生变化，文中取温度为273.15 K时，4种质量分数及硫酸质量分数为20 %时，4种温度所对应的硫酸密度和黏度，其值如表 2所列.
表 2 硫酸在不同条件下的密度和黏度Table 2. Density and viscosity of sulfuric acid under different conditions
1.3 数学模型
采用Euler-Euler多相流模型模拟三相搅拌体系，由于不考虑立式釜内多相间的能量传递，因此主相和次相共用相同的质量守恒方程（Mass Conservation Equation）和动量守恒方程（Momentum Conservation Equation）如下所示：
质量守恒方程（连续性方程）：
(1) 次相动量守恒方程：
(2) 主相动量守恒方程：
(3) 式（2）、式（3）中μeff，l和μeff，g为有效黏度，F1g为相间动量传递项.
多相间的曳力采用Schiller-Naumann[17-19]模型，表达式为：
(4) 式（4）中Re为雷诺数.
1.4 模拟方法
针对立式釜中H2SO4-O2-铜阳极泥三相搅拌模拟，采用Fluent软件进行求解计算，选择欧拉-欧拉“三流体模型”和标准k-ε湍流模型，近壁面流体运动选择标准壁面函数法处理，动静区域采用MRF模型，松弛因子保持默认，各方程控制收敛精度均小于10-4.基于上述模型和参数进行非稳态模拟，设置最大迭代步数为50，时间步长为0.002 s.
1.5 网格划分及边界条件
采用Gambit前处理软件对立式釜的流体计算域进行建模，并结合结构化网格和非结构化网格对立式釜模型进行网格划分，其中静区域进行分块后采用结构化网格划分模型，由于动区域的物理模型较为复杂，难以采用规则的六面体网格划分，因此双层搅拌动区域的网格均为非结构化网格.为了准确模拟立式釜内流体的运动，对进气口周围和2个动区域内的网格局部加密，最终总网格数为97万个.其中立式釜截面网格、直叶桨网格如图 2所示.
将立式釜分为包括静区域和2个动区域在内的3部分，动静区域间通过interface交界面进行动量和质量的传递，且通过MRF模型赋予动区域一定转速，搅拌桨和搅拌轴与动区域间无相对运动，而静区域则设置为静止壁面.进气口采用速度入口作为边界条件，定义进气口中O2的体积分数为1，通气量为15.131 m3/h.釜顶的出口设置为压力出口，压力大小为一个标准大气压.初始状态通过Fluent软件中的Patch功能界定自由液面的高度，设置自由液面高度H=1.708 m，即H < 1.708 m的区域全部为H2SO4溶液和阳极泥颗粒；H > 1.708 m的区域全部为O2.
1.6 各工况条件对固相分布的影响
一定条件下不同搅拌转速对应的固相分布如图 3所示，由图 3可知，搅拌转速对釜内固相分布特性的影响极为显著，由图 3（a）可知，釜内流体湍流强度较弱，桨叶两侧的循环涡流受到抑制，此时阳极泥颗粒未能得到有效分散产生沉降现象.随着转速增大至400 r/min，如图 3（d），桨叶搅拌强度提升，铜阳极泥颗粒随剧烈的环流在釜内循环运动，此时顶部自由液面产生“漏斗”状下凹漩涡流，固相与气液两相之间得到均匀混合.
一定条件下不同硫酸质量分数和温度对应的固相分布如图 4、图 5所示，由图 4和图 5可知，硫酸质量分数和温度均能改变固液两相间的曳力作用，从而促进或抑制阳极泥在釜内的扩散，但Rushton桨对流体仅有径向分散作用，双层桨间区域湍流强度较弱，固-液两相由于速度差异产生的曳力作用不足以带动阳极泥颗粒随涡流充分流动，部分颗粒在双层桨间形成“滞留区”.
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图 4 硫酸质量分数对固相分布的影响Figure 4. Solid phase distribution under different sulfuric acid mass fraction一定条件下不同液固比对应的固相分布如图 6所示，从宏观上分析，增加液固比会使釜内湍流流动增强，但固-液两相间的曳力作用由于固相颗粒的减少和固-液速度差的减小而逐渐减弱，当液固比为4:1和6:1时，液相对固相产生足够的曳力，使得阳极泥颗粒克服重力做功上浮并与气液两相充分混合.随着液固比进一步增大至8:1和10:1，少部分颗粒受漩涡流作用在釜壁两侧区域循环流动，随后再次回到立式釜下半部分，此时近自由液面为阳极泥颗粒的低浓度区域.
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图 6 液固比对固相分布的影响Figure 6. Solid phase distribution under different liquid to solid ratio2 基于灰色关联度的工艺条件分析及多目标优化
2.1 灰色关联分析原理及步骤
灰色关联法是由邓聚龙教授于1982年提出[20]，其目的是通过比较数列与参考数列间的同步变化趋势来衡量因素间的关联程度，若两者间的同步变化趋势越相近，则其关联程度越高，该因素对于研究对象的影响程度也越大.灰色关联分析的具体步骤如下：
1）确定比较数列和参考数列.灰色理论提出了对各子系统进行灰色关联度分析的概念，因此首先应确定反应系统行为特征的参考数列和影响系统行为的比较数列，对于实验过程中的m组数据，每组数据含有n个混合性能评价指标，可表示为：
(5) 其中：Xi=（xi（1），xi（2），…，xi（m））T，i=1，2，…，n，xi（k）为第k组测量数据的第i个相关评价指标因素.
2）对参考数列和比较数列进行无量纲化处理.由于各指标的原始数据的量纲不同，且数值也相差较大，为使不同量纲的评价指标可以在同一度量尺度上进行比对分析，应该消除量纲，合并数量级.文中采用区间值化变换，计算公式如下：
若期望混合性能指标原始数据是越大越好，则采用公式：
(6) 其中：yi（k）为数据处理后的数据序列.
使用公式和对立式釜混合性能参数进行无量纲化处理，则公式可转换为：
(7) 3）计算灰色关联系数.从本质上来说，曲线间几何形状的差别程度就是各因素之间的关联程度，因此关联程度的衡量标准可用曲线间的差值大小来表示.计算各组测量数据列与参考数据列灰色关联系数的公式表示为：
(8) 式（8）中：y0（k）为参考序列，令y0（k）=1.0；ξ0i（k）为y0与yi的关联系数；Ψ为灰色关联的分辨系数，其取值范围一般为0 < Ψ < 1，文中根据文献将灰色关联的分辨系数取值为0.5；在公式中作为分母的Ψ越小，灰色关联系数ξ0i（k）计算值越大，越能进行区分.
4）计算灰色关联度.灰色关联系数是比较数列和参考数列在不同工艺参数下的关联程度值，为便于系统比较，反应立式釜工艺参数与混合性能的关联程度，因此对各参考数列和比较数列的关联系数取平均值，这个平均值成为灰色关联度，其计算公式为：
(9) 2.2 灰色关联分析
采用正交设计实验方案进行了不同参数下的立式釜三相搅拌模拟实验，并基于灰色关联分析法，综合考察各工艺参数对釜内搅拌混合性能的影响, 选取搅拌转速（A）、硫酸质量分数（B）、铜阳极泥颗粒体积分数（C）、温度（D）4种影响立式釜内搅拌流场的因素指标，以X=0.03 m截面的气含率（GH）、截面湍流动能（k）、硫酸溶液的平均速度（Vl）和铜阳极泥颗粒的平均运动速度（Vs）为评价指标，对立式釜内三相搅拌体系进行灰色关联分析，其原始数据如表 3所列.
表 3 立式釜内流场的影响因素原始数据Table 3. Original data of influencing factors of flow field in vertical kettle
由于各数据单位及物理量含义均不相同，无法对不同因素进行直接比较，因此对原始数据进行无量纲化处理.立式釜内截面气含率越高，多相混合效果越好，因此希望截面气含率越大越好；湍流动能越大，说明立式釜内各相流速越快，湍流强度越剧烈，混合越均匀，因此希望湍流动能越大越好；立式釜内硫酸溶液的高速流动使得铜阳极泥颗粒在釜内的运动范围将大大增加，促进固相颗粒悬浮作用；铜阳极泥颗粒的速度越快代表着立式釜内多相混合越均匀.因此，对于4种因素按公式（6）进行无量纲化处理.无量纲化后的数据见表 4.
表 4 混合性能无量纲化数据Table 4. Normalization data for mixing performance
将无量纲化后的数据代入式（8）、式（9）计算各混合性能评价指标（截面的气含率、湍流动能、硫酸溶液平均速度和铜阳极泥颗粒平均速度）之间的灰色关联度. 表 5所求得的灰色关联度表示的是各个因素与混合性能的关联的程度，值越大表示两者之间影响程度越明显，各因素与参考序列的灰色关联度及排序结果如表 5所列.
表 5 灰色关联度及排序Table 5. Grey correlation degree and sorting
由表 5可知，工况9的灰色关联度值最大，而工况3所对应的工艺参数灰色关联度值最小.因此工况9所对应的工艺参数搅拌混合效果最好，工况3所对应的工艺参数搅拌混合效果最差.为进一步比较各因素对搅拌混合性能的影响强弱，现对表 5中的灰色关联度进行极差分析，各因素水平的平均灰色关联度值如表 6所列，其在不同水平下的变化曲线如图 7所示.
表 6 各因素平均灰色关联度Table 6. The average gray incidence of each factor
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图 7 各因素水平与平均灰色关联度的关系Figure 7. The relationship between the level of each factor and the average gray correlation灰色关联度的极差大小代表各工艺参数对立式釜内搅拌混合性能的影响程度，极差越大，则该因素对混合性能影响越大，反之亦然.由表 6和图 7可知，搅拌转速在不同水平下的关联度相差最大，其值为0.574，表示搅拌转速是影响立式釜搅拌混合性能的最大参数因素.液固比的灰色关联度极差为0.028，即表示液固比是影响立式釜搅拌性能的最小参数因素.综合4种因素对搅拌混合的影响，其主次顺序依次为：搅拌转速>温度>硫酸质量分数>液固比.
3 结论
1）由三相搅拌模拟结果可知：搅拌转速会加大立式釜内多相间的混合强度；硫酸质量分数的增加使得液相对气相的曳力作用增强，从而增加釜内的气含率；液固比的增加使得铜阳极泥颗粒对其它相的拖曳能力减弱，釜内流体流动速度加快；温度增加对流场的影响不大，只能在小范围增加釜内的气含率.
2）对正交设计实验的H2SO4-O2-铜阳极泥颗粒三相搅拌模拟结果进行灰色关联分析，得到各因素影响混合性能的主次顺序为：搅拌转速>温度>硫酸质量分数>液固比.
朱冬梅 -
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图 1 不同Cu基催化剂SEM图[42-44,50]；（a）立方体c-Cu2O；（b）八面体o-Cu2O；（c）多面体t-Cu2O；（d）棱镜形单质Cu；（e）C纳米管负载无定形Cu单原子；（f）三维分层树枝状空心Cu金属有机框架
Fig 1. SEM images of different Cu-based catalysts[42-44,50]； （a） cubic c-Cu2O； （b） octahedral o-Cu2O； （c） polyhedral t-Cu2O； （d） prismatic monolithic Cu； （e） amorphous Cu single atoms loaded on carbon nanotubes； （f） 3D layered dendritic hollow Cu metal organic framework
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图 3 Cu电极上电催化CO2还原为C1,C2和C3产品的反应途径。重叠的圆圈之间的箭头表示每个产品的烯醇、酮醇和二醇形式之间的变化,非重叠圆圈之间的箭头表示电化学还原步骤[104]
Fig 3. Reaction pathways for electrocatalytic CO2 reduction to C1, C2 and C3 products at a copper electrode. Arrows between overlapping circles indicate changes between enol, ketol and diol forms of each product, and arrows between non-overlapping circles indicate electrochemical reduction steps[104]
表 1 标准条件下电催化CO2还原半反应的电极电位及产物（1.01×105Pa,25 ℃,pH=7）[27-28]
Table 1 Electrode potentials and products of electrocatalytic CO2 reduction half-reactions under standard conditions （1.01×105Pa, 25 °C, pH= 7）[27-28]
电催化的热力学半反应 标准条件下的电极电位/（V vs. SHE） 产物 CO2（g） + 4H+ + 4e- → C（s） + 2H2O （l） 0.210 C CO2（g） + 2H2O（l） + 4e- → C（s） + 4OH- -0.627 C CO2（g） + 2H+ + 2e- → HCOOH（l） -0.250 HCOOH CO2（g） + 2H2O（l） + 2e- → HCOO-（aq） + OH- -1.078 HCOO- CO2（g） + 2H+ + 2e- → CO（g） + H2O（l） -0.106 CO CO2（g） + 2H2O（l） + 2e- → CO（g） + 2OH- -0.934 CO CO2（g） + 4H+ + 4e- → HCHO （l） + 4OH- -0.898 HCHO CO2（g） + 6H+ + 6e- → CH3OH（l） + H2O（l） 0.016 CH3OH CO2（g） + 5H2O（l） + 6e- → CH3OH（l） + 6OH- -0.812 CH3OH CO2（g） + 8H+ + 8e- → CH4（g） + H2O（l） 0.169 CH4 CO2（g） + 6H2O（l） + 8e- → CH4（g） + 8OH- -0.659 CH4 2CO2（g） + 2H+ + 2e- → HOOCCOOH （aq） -0.500 HOOCCOOH 2CO2（g） + 2e- →C2O42-（aq） -0.590 C2O42- 2CO2（g） + 12H+ + 12e- → C2H4 （g） + 4H2O（l） 0.064 C2H4 2CO2（g） + 8H2O（l）+ 12e- → C2H4 （g） + 12OH- -0.764 C2H4 2CO2（g） + 12H+ + 12e- → C2H5OH （l） + 3H2O（l） 0.084 C2H5OH 2CO2（g） + 9H2O（l） + 12e- → C2H5OH （l） + 12OH- -0.744 C2H5OH 
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表 2 不同铜基催化剂电催化CO2还原性能总结
Table 2 Summary of electrocatalytic CO2 reduction performance of different copper-based catalysts
催化剂 工作电极 电解液 还原产物 电位 电流密度/（mA/cm2） 参考文献 Cu（100） — 0.1 mol/L KHCO3 C2H4 40.7%；CH4 19.8% -1.39 V vs. SCE 5 [62] Cu（711） — 0.1 mol/L KHCO3 C2H4 58.5%；CH46.9% -1.37 V vs. SCE 5 [62] Cu（111） — 0.1 mol/L KHCO3 HCOOH 16.6%； CH4 50.5% -1.52 V vs. SCE 5 [62] Cu纳米颗粒 气体扩散电极 1 mol/L KHCO3 CO 26.0%； C2H4 40% -0.8 V vs. RHE 300 [63] Cu纳米颗粒 Cu 0.1 mol/L KClO3 C2H4 36% -1.1 V vs. RHE — [64] SACu/CNT 碳纸 0.5 mol/L KHCO3 CO 96.3% -0.7 V vs. RHE 43.5 [43] CuO 玻璃碳电极 1 mol/L KHCO3 C2H4 31%； CO 8.3% -0.8 V vs. RHE 300 [33] Cu2O — 0.1 mol/L KHCO3 C2H4 34%～39%； C2H5OH 9%～16% -0.99 V vs. RHE -20 [65] Cu2O 抛光Cu电极 0.1 mol/L KHCO3 C2H4 43%； C2H5OH 11.8% -0.98 V vs. RHE -31.2 [66] Cu2O — 0.1 mol/L KHCO3 C2H4 43.1%； C2H5OH 17.4% -1.0 V vs. RHE 13.00 [67] ZnO@4Cu2O 气体扩散电极 1 mol/L KOH C2H4 33.5%； C2H5OH 16.3% -1.0 V vs. RHE 140.10 [68] Cu4O3 气体扩散电极 2.5 mol/L KOH C2H4 40% -0.64 V vs. RHE 400.00 [69] Cu4O3/CuO/Cu2O 碳纸 1 mol/L KOH C2H4 26.0%； C2H5OH 4.2% -0.8 V vs. RHE 80.00 [32] CuxO/CN — 0.5 mol/L NaHCO3 C2H4 42.2%；CH4 37.8% -1.2 V vs. RHE 40.00 [70] Cu3Sn@Cu-SnO2 — 0.5 mol/L KHCO3 HCOOH 78% -0.9 V vs. RHE 30.00 [71] 聚苯胺/Cu2O 负载30%Pt的碳纸 0.1 mol/L 四丁基高氯酸铵/甲醇 HCOOH 30.4%； CH3COOH 63.0% -0.3 V vs. SCE 0.05 [72] CuPc 玻璃碳电极 3.0 mol/L KHCO3 C2H4 25% -1.6 V vs. Ag/AgCl 2.80 [73] CuPPc 碳纸 0.1 mol/L KHCO3 CH4 55% -1.25 V vs. SCE 18.00 [74] Cu-MOF 碳纸 0.5 mol/L KHCO3 CO 39.6% -0.56 V vs. RHE 32.90 [75] CuN3O/C 碳纸 0.1 mol/L KHCO3 CO 96% -0.8 V vs. RHE 8.82 [76] 注： “SACu/CNT ”表示负载于碳纳米管吡咯氮配位的Cu单原子催化剂；“CuxO/CN”表示氮化碳（CN）包覆的CuxO；“CuPPc”表示聚合铜酞菁；“SCE”表示饱和甘汞电极；“RHE”表示可逆H电极；“—”表示无或不详。
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表 3 铜基催化剂优缺点对比
Table 3 Comparison of advantages and disadvantages of copper-based catalysts
催化剂 催化活性 产物选择性 结构稳定性 金属Cu 差,FE低于50% 差,可同时产生C1,C2,C3产物 不稳定,反应过程易被氧化 Cu氧化物 差,FE低于50% 差,可同时产生C1,C2,C3产物 稳定,反应过程结构不易被破坏 Cu合金 中等,FE低于70% 中等,可同时产生C1,C2产物 稳定,反应过程结构不易被破坏 Cu金属有机框架 优秀,FE高于90% 良好,主要产生一种碳产物 不稳定,反应过程配位有机物易被破坏 铜酞菁 良好,FE低于80% 良好,主要产生一种碳产物 稳定,芳香大环与金属中心共轭,结构稳定 Cu单原子 优秀,FE高于90% 优秀,主要产生一种碳产物 不稳定,反应过程易被氧化 Cu化合物 中等,FE低于70% 优秀,主要产生一种碳产物 稳定,反应过程结构不易被破坏
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