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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铷是重要的战略碱金属，具有优异的物理、化学和光电性能[1-3]。长期以来，铷及其化合物在原子钟、光电池、特种玻璃、生物化学及医药等传统领域中有着重要用途[4]。近年来，在钙钛矿电池、动力发电、离子推进发动机、激光能转换电能装置等新兴应用领域中[5-8]，铷也表现出越来越重要的作用，显示出强劲的生命力。因此，铷的提取和应用已引起世界各国的广泛关注。
自然界中的铷资源主要分布在盐湖卤水和矿石中，在地壳中的丰度排在第16位[9-12]。铷比同主族的碱金属锂和铯以及许多常见的金属锌、铅等的储量更丰富，但是这些金属每年的开采量却数倍于铷[13-14]。这是因为铷的分布分散且常以微量存在，开采难度较大。并且铷鲜有自己独立存在的矿物，主要以类质同象的形式取代钾的位置存在于花岗岩、光卤石和花岗伟晶岩类矿物中[15]。一直以来，铷主要是从铯榴石和锂云母提取铯、锂的副产物中回收，资源回收率低。近年来，一些文献报道的矿石提铷工艺主要可以分为：焙烧分解法、酸分解法以及酸碱联合法[16]。其中，焙烧分解法以氯化焙烧法为主，是目前研究最多的方法。氯化焙烧法的原理是氯化物与矿物中的碱金属会在高温下发生反应，产生氯化氢气体。氯化氢气体继续与含铷云母反应，破坏云母稳定的结构，使其中的铷释放出来，最后通过水浸使可溶性的氯化铷进入溶液[17-18]。氯化焙烧法虽然可以将铷高效浸出，但未考虑矿物中丰富硅、铝资源的资源化利用，并且采用氯化焙烧会产生大量的含盐酸废气和高盐废水，处理技术难度较大，成本较高。酸碱联合法[19]是目前得到广泛关注的矿石提铷方法，该法克服了酸法只能高效浸出云母而不能有效破坏长石结构的缺点。并且酸碱联合法不仅考虑到了铷的高效回收，还考虑到了宏量元素硅、铝的资源化利用，浸出液返回浸出，避免了大量高盐废水的产生。但是酸碱联合法流程较长，浸出压力和碱耗较高，仍然具有优化的可能[19-20]。
为了充分破坏含铷矿物中稳定的硅氧四面体结构，有效降低浸出压力和碱耗。课题组提出了对铷矿进行熔融水淬处理，在高温下强制破坏矿物结构，使铷彻底解离，实现其高效浸出[21-22]。为了进一步研究所得水淬渣的浸出活性，系统研究碱浸过程中氢氧化钠浓度、温度和水淬渣粒度对浸出速率的影响，分析水淬渣浸出动力学和浸出控制性环节，以期为复杂铷矿的高效处理提供参考。
1 试验
1.1 试验原料
铷矿熔融水淬渣是由铷矿与质量分数30%的氢氧化钠充分混合后，在1 250 ℃条件下焙烧2 h直接水淬所得。铷矿与熔融水淬渣的主要成分如表 1所列。氢氧化钠质量分数为96%，为分析纯。
表 1 钨酸铵原料液中各杂质元素的浓度Table 1. The concentration of each impurity element in ammonium tungstate feed liquid
1.2 试验仪器
试验所使用的仪器主要有SHJ-A6恒温磁力搅拌水浴锅、PL203电子天平、SHB-3循环水式真空泵、DZF-6090真空干燥箱、烧杯、容量瓶、量筒、玻璃杯、移液管等。
1.3 试验步骤与分析手段
首先配置500 mL一定浓度的氢氧化钠溶液于烧杯中，将烧杯放入恒温水浴锅中加热至设定温度后加入10 g细磨水淬渣，调节转速为400 r/min开始反应。每隔2 min取5 mL浆液，液固分离后，对滤液中的铷含量进行分析。实验中，水淬渣、浸出液和浸出渣中的铷离子浓度通过电感耦合等离子发射光谱(ICP)进行分析，水淬渣和浸出渣的物相、形貌通过X射线衍射仪(XRD)、扫描电镜(SEM)、能谱仪(EDS)等方法进行分析，水淬渣粒度通过激光粒度分析仪进行分析。
2 结果与讨论
2.1 铷矿熔融水淬渣分析
熔融一段时间后，铷矿中稳定的硅酸盐结构被强制破坏，直接水淬使矿物保持高温下高活性状态，得到的水淬渣以高活性的状态存在。水淬渣的XRD图谱如图 1所示，从图 1可以看出，水淬渣无晶型，以无定形的状态存在，与预期相符。
为了进一步分析经过熔融焙烧后各有价元素的赋存状态，对熔融水淬渣进行了SEM-EDS分析，所得结果如图 2所示。从水淬渣的能谱图中可以看出，铷以高度分散的状态存在，可以进一步推测在前期熔融阶段原矿的稳定物相已经被充分破坏。
2.2 碱浸实验
2.2.1 氢氧化钠浓度对铷浸出率的影响
取10 g细磨至38~48 μm之间的水淬渣，在碱浸温度100 ℃，液固比50:1 (mL/g)，转速400 r/min的条件下，研究氢氧化钠浓度(100，160，180，200 g/L)对铷浸出的影响，结果如图 3所示。从图 3中可以看出氢氧化钠浓度对水淬渣的浸出影响较为明显。随着氢氧化钠浓度的增加，铷的浸出率快速上升。在氢氧化钠浓度为200 g/L条件下，反应10 min，铷浸出率达到65%以上。熔融水淬-碱浸法相较于现阶段碱法对铷矿的处理工艺中碱耗较高(氢氧化钠浓度为600 g/L)的问题，具有明显的优势[22]。
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图 3 不同氢氧化钠浓度下铷浸出率与时间的关系Figure 3. Relationship of rubidium leaching rate with time for different sodium hydroxide concentrations2.2.2 碱浸温度对铷浸出率的影响
取10 g细磨至38~48 μm之间的水淬渣，在氢氧化钠浓度为200 g/L，液固比50:1 (mL/g), 转速400 r/min的条件下，研究碱浸温度(45，70，90，100 ℃)对铷浸出的影响。不同碱浸温度下，铷的浸出率与时间的关系如图 4所示。从图 4中可以看出浸出温度对水淬渣的浸出影响较为显著。温度可以有效的影响分子的热运动，温度越高，分子的热运动越快，单位时间参与浸出反应的分子越多，浸出速度越快。碱浸反应在100 ℃下反应速率很快，反应10 min，铷浸出率就能达到65%左右。该法相比较现阶段碱法工艺中存在的碱浸温度较高(约250 ℃)的问题，也具有较大优势[22]。
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图 4 不同浸出温度下铷浸出率与时间的关系Figure 4. Relationship of rubidium leaching efficiency with time at different leaching temperatures2.2.3 水淬渣粒度对铷浸出率的影响
取10 g水淬渣，在碱浸温度为100 ℃，液固比为50:1 (mL/g)，转速400 r/min，氢氧化钠浓度为200 g/L的条件下，研究水淬渣粒度(25~38，38~48，48~75，75~150 μm)对铷浸出效果的影响，结果如图 5所示。
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图 5 不同粒度下铷浸出率和时间的关系Figure 5. Relationship of rubidium leaching efficiency with time for different water quenched slag particles sizes从图 5中可以看出，水淬渣粒度对铷浸出率影响较为明显，在一定范围内，水淬渣粒度越小，浸出速率更快，铷浸出率越高。但是当粒度小于38~48 μm时，继续减小，水淬渣的浸出速率变化不大。因此可以适当减小水淬渣粒度来获得更好的浸出效果。
2.3 浸出动力学分析
铷矿水淬渣的浸出本质上为非均相液固反应，假设水淬渣的碱浸反应动力学过程可以用未反应核模型来描述[23-25]。水淬渣的碱浸主要包括以下①~⑤共5个过程：①浸出剂从溶液中运动到固体产物层表面(外扩散)；②浸出剂离子通过固体产物层向反应界面的扩散(内扩散)；③浸出剂离子在反应界面与未反应水淬渣发生化学反应(化学反应)；④反应产物通过从反应界面通过固体产物层向边界层的扩散(内扩散)；⑤碱浸渣从固体颗粒表面扩散到浸出液中(外扩散)。
上述不同控制步骤的控速方程如下：
(1) 
(2) 
(3) 
(4) 其中k1，k2，k3，k4是不同控速环节的速率常数，分别对应外扩散控制、化学反应控制、内扩散控制和混合控制的速率常数；x是铷的浸出率，%；t为碱浸反应的时间，min。
2.3.1 温度对浸出过程影响的动力学分析
将不同温度下铷的浸出率分别带入上述未反应核模型的不同动力学控制方程，并进行线性拟合，拟合效果如图 6所示，各模型对应温度下的拟合优度如表 2所列。分析表 2拟合结果，外扩散控制模型、化学反应控制模型的拟合优度均小于0.90，内扩散控制和混合控制的模型在拟合优度均在0.95以上。为了进一步确定该浸出反应的控速方程，通过Arrhenius[23, 26]方程如式(5)对浸出过程进一步分析。
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图 6 不同浸出温度下各动力学方程的拟合效果Figure 6. Fitting results for each kinetic equation at different leaching temperatures表 2 杂质S初始浓度对其析出率及在APT中的含量的影响Table 2. Effect of initial concentration of impurity S on itself precipitation rate and content in APT crystal
通过图 6中各浸出温度下直线的斜率确定速率常数k (如表 2)，并带入Arrhenius方程计算浸出反应的表观活化能。
(5) 式(5)中：k为速常数；A为指前因子；Ea为浸出反应的表观活化能，kJ/mol；R为摩尔气体常数，J/(mol·K)；T为热力学温度，K。对Arrhenius方程两边取对数，构建lnk与1 000/T的关系(图 7)。通过图 7中Arrhenius曲线可以求出内扩散控制下浸出反应的表观活化能为Ea=33.25 kJ/mol，而扩散控制模型的表观活化能小于20 kJ/mol。因此，铷的浸出不属于内扩散控制[23]。混合控制下计算出的浸出反应的表观活化能为Ea=37.41 kJ/mol，表观活化能属于混合控制下的活化能的数值区间(20~40 kJ/mol)，这也进一步证明了铷矿水淬渣的浸出过程符合混合控制的动力学模型。
2.3.2 水淬渣粒度对浸出过程影响的动力学分析
把不同粒度水淬渣对应铷的浸出率带入混合控制的动力学方程并进行线性拟合(如图 8)。分析不同水淬渣粒度条件下对混合控制模型的拟合优度(如表 3)，可以看出混合控制模型的拟合优度均在0.95以上，与上文中得出的符合混合控制模型的结论一致。
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图 8 不同水淬渣粒度下ln(1-x)/3+(1-x)-1/3-1与t的关系Figure 8. Dimensions of ln(1-x)/3+(1-x)-1/3-1 with t for different water quenched slag particle sizes表 3 不同水淬渣粒度条件下混合控制模型的拟合数据Table 3. Fitting data of the hybrid control model for different water quenched slag particle sizes
经查阅文献[23, 27]，符合收缩核模型的动力学过程，还满足克兰克-金斯特林-布劳希特因方程式(6)。其中D为浸出剂的有效扩散系数；M为氢氧化钠的相对分子质量；C为浸出液中氢氧化钠浓度；δ为化学反应式中反应物的计量系数；ρ为反应物密度；r0为水淬渣原始半径，且当只改变水淬渣粒径时D，M，δ，C，ρ均视为常数。对式(6)两边取自然对数，并作lnk与lnd0(d0为水淬渣粒径)的关系图，如图 9所示。
(6) ![]()
图 9 不同水淬渣粒径下lnd0与lnk的关系Figure 9. Relationship between lnd0 and lnk for different water quenched slag particle sizes从图 9中可以看出，lnk与lnd0成很好的线性关系，拟合优度为0.98，水淬渣的粒径对碱浸反应的反应级数为-0.86，碱浸过程满足克兰克-金斯特林-布劳希特因方程，这也证明铷矿水淬渣的碱浸过程符合混合控制模型，并且在一定范围内降低铷矿水淬渣粒径可以有效提高铷的浸出速率。
2.4 动力学方程的确立
从上述实验中可以看出，碱浸过程中的浸出温度和水淬渣粒度均会对浸出过程产生较大影响。因此，浸出过程在浸出温度和水淬渣粒度作用下未反应核模型的表观反应速率常数可以表示为式(7)[28]。
(7) 式(7)中：A为Arrhenius方程的指前因子a为水淬渣粒度的反应级数。从图 7和图 9中的拟合结果可以得出表观活化能为37.41 kJ/mol，A=321和a=-0.86，代入式(4)可得混合控制模型的反应动力学方程为：
(8) 2.5 碱浸过程物相分析
为了分析碱浸过程水淬渣的物相转变及形貌变化，对碱浸渣(氢氧化钠200 g/L，98 ℃，1 h)进行了XRD以及扫描电镜分析。通过对图 10和图 11进行分析可以得出，经过碱浸，无定形的水淬渣转变为晶型较好的方钠石。生成的方钠石是由许多个表面疏松、比表面积较大的小球团簇在一起组成。方钠石作为类沸石类矿物，具有典型的硅酸盐矿物骨架。并且方钠石与A型沸石和X型沸石具有相同的β特征笼，可以在合适的条件下通过简单的沸石转化法进行转化[29]，进而实现对矿物中硅、铝资源的高值化利用。
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图 10 水淬渣碱浸前后XRD衍射图谱Figure 10. XRD diffraction pattern of water quenched slag before and after alkali leaching3 结论
通过对铷矿水淬渣系统的实验研究，得出了以下结论：
1) 结构稳定的铷矿经过熔融水淬后，稳定的结构被破坏，水淬渣的浸出活性较高。熔融水淬碱浸工艺相较于现阶段铷矿的碱法提铷工艺，具有碱耗和浸出温度较低的优势，可以实现在低碱、低温条件下铷的高效浸出。
2) 铷矿水淬渣的浸出动力学过程符合混合控制模型，拟合优度达到0.95以上，浸出过程的表观活化能为37.41 kJ/mol，混合控制模型的动力学方程为：ln(1-x)/3+(1-x)-1/3-1=321·d0-0.86·exp[-33250/(RT)]·t。
3) 碱浸过程中氢氧化钠浓度、浸出温度和水淬渣粒度是影响水淬渣浸出速率的最主要因素。在适当减小水淬渣粒径条件下，提高温度和氢氧化钠浓度可以有效提高铷的浸出率。
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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