Pub Date : 2021-06-07DOI: 10.3389/fctls.2021.704925
A. Macchioni
The interaction between a metal center (M) and a molecular moiety (substrate) is the basis of most catalytic processes. The chemical environment surrounding M can equally be a set of suitable ligands (Coordination Catalysis) (Crabtree, 2014), a set of properly engineered/functionalized ligands anchored onto a solid support (Single-Site Surface Coordination Catalysis) (Copéret et al., 2016), a small cluster of metal atoms as well as a lattice of a material (Heterogeneous Catalysis) (Friend and Xu, 2017), and an enzymatic framework (Biocatalysis) (Schwizer et al., 2018) (Figure 1). If at least one of the M-environment interactions involves an M–R bond (where R C and H), all types of catalysis listed above are by definition Organometallic Catalysis. Furthermore, even in the absence of a M–R bond in the starting molecule/material, the catalytic process may be still defined as of organometallic nature if a M–R fragment forms in any step of the catalytic cycle. These simple considerations clearly indicate the generality and importance of organometallic catalysis. Relevant examples of organometallic catalysis, for each of category illustrated above, are very well known and reported in the textbooks (Drauz et al., 2012; Bochmann, 2014). The success of organometallic catalysis may be ascribed to the capability of a metal to activate lowenergy reaction pathways along which the deformed substrate, stabilized through coordination at a properly designed LnM-fragment, is induced to react in a novel and original way. This explains why some reactions are exclusive of coordination/organometallic complexes. In this respect, a classical example is the reductive elimination, which is one of the fundamental steps of organometallic catalytic cycles (Hartwig, 1998; Chen et al., 2017; Chu and Nikonov, 2018; Wolczanski, 2018). It involves the release of R–X from a (LnMXR) complex, where oxidation state, coordination number and electron of the metal center are reduced by two units. As a result of this propensity to activate a substrate by opening low-energy reaction pathways, the activity of organometallic catalysts can be so high that a <10−6 M active metal concentration is sufficient for carrying out the reaction efficiently: in these cases, catalyst separation and recovery from the products might even be avoided, as it occurs in some industrial polymerization processes (Stürzel et al., 2016). This notwithstanding, catalyst recovery is still necessary is many cases, and typically more easily achievable with heterogenous rather than molecular systems. For this reason, industrially relevant molecular catalysts are often heterogenized onto suitable supports, as mentioned above, leading to heterogeneous catalysts with similar (ideally the same) activity and selectivity to the molecular counterpart, but with the additional advantage of being easy to separate from the reaction environment and recycle (Schwarz et al., 1995; McNamara et al., 2002; Witzke et al., 2020). Selectiv
金属中心（M）和分子部分（底物）之间的相互作用是大多数催化过程的基础。M周围的化学环境同样可以是一组合适的配体（配位催化）（Crabtree，2014）、一组锚定在固体载体上的适当工程/功能化的配体（单位点表面配位催化剂）（Copéret et al.，2016）、金属原子的小簇以及材料的晶格（多相催化）（Friend和Xu，2017），和酶框架（生物催化）（Schwizer等人，2018）（图1）。如果M-环境相互作用中至少有一种涉及M–R键（其中R C和H），则上述所有类型的催化都属于有机金属催化。此外，即使在起始分子/材料中没有M–R键的情况下，如果在催化循环的任何步骤中形成M–R片段，则催化过程仍然可以定义为具有有机金属性质。这些简单的考虑清楚地表明了有机金属催化的普遍性和重要性。对于上述每一类，有机金属催化的相关例子都是众所周知的，并在教科书中进行了报道（Drauz等人，2012；Bochmann，2014）。有机金属催化的成功可以归因于金属激活低能量反应途径的能力，沿着该反应途径，通过在适当设计的LnM片段上的配位稳定的变形底物被诱导以新颖和原始的方式反应。这就解释了为什么有些反应不包括配位/有机金属配合物。在这方面，一个经典的例子是还原消除，这是有机金属催化循环的基本步骤之一（Hartwig，1998；Chen等人，2017；Chu和Nikonov，2018；Wolczanski，2018）。它涉及从（LnMXR）络合物中释放R–X，其中金属中心的氧化态、配位数和电子减少两个单位。由于这种通过开启低能量反应途径活化底物的倾向，有机金属催化剂的活性可能非常高，以至于＜10−6 M的活性金属浓度足以有效地进行反应：在这些情况下，甚至可以避免催化剂从产物中分离和回收，因为它发生在一些工业聚合过程中（Stürzel等人，2016）。尽管如此，在许多情况下，催化剂回收仍然是必要的，并且通常用非均相系统而不是分子系统更容易实现。因此，如上所述，工业上相关的分子催化剂通常被多相化到合适的载体上，导致多相催化剂具有与分子对应物相似（理想地相同）的活性和选择性，但具有易于从反应环境中分离和回收的额外优点（Schwarz等人，1995；McNamara等人，2002；Witzke等人，2020）。选择性是另一种强大的有机金属催化，可以通过适当选择/组合配体来调整活性金属的化学环境来实现。事实上，即使在非酶系统中，许多工业相关反应的化学、区域和立体选择性也已接近100%。重要的是，有机金属催化剂的有效性也源于可能的M-环境协同性。后者可能涉及配体，其可能具有氧化还原活性或具有研磨功能（碱、酸等）、载体、其他金属中心（均由荷兰代尔夫特理工大学Frank Hollmann编辑和审查
{"title":"Speciality Grand Challenges in Organometallic Catalysis","authors":"A. Macchioni","doi":"10.3389/fctls.2021.704925","DOIUrl":"https://doi.org/10.3389/fctls.2021.704925","url":null,"abstract":"The interaction between a metal center (M) and a molecular moiety (substrate) is the basis of most catalytic processes. The chemical environment surrounding M can equally be a set of suitable ligands (Coordination Catalysis) (Crabtree, 2014), a set of properly engineered/functionalized ligands anchored onto a solid support (Single-Site Surface Coordination Catalysis) (Copéret et al., 2016), a small cluster of metal atoms as well as a lattice of a material (Heterogeneous Catalysis) (Friend and Xu, 2017), and an enzymatic framework (Biocatalysis) (Schwizer et al., 2018) (Figure 1). If at least one of the M-environment interactions involves an M–R bond (where R C and H), all types of catalysis listed above are by definition Organometallic Catalysis. Furthermore, even in the absence of a M–R bond in the starting molecule/material, the catalytic process may be still defined as of organometallic nature if a M–R fragment forms in any step of the catalytic cycle. These simple considerations clearly indicate the generality and importance of organometallic catalysis. Relevant examples of organometallic catalysis, for each of category illustrated above, are very well known and reported in the textbooks (Drauz et al., 2012; Bochmann, 2014). The success of organometallic catalysis may be ascribed to the capability of a metal to activate lowenergy reaction pathways along which the deformed substrate, stabilized through coordination at a properly designed LnM-fragment, is induced to react in a novel and original way. This explains why some reactions are exclusive of coordination/organometallic complexes. In this respect, a classical example is the reductive elimination, which is one of the fundamental steps of organometallic catalytic cycles (Hartwig, 1998; Chen et al., 2017; Chu and Nikonov, 2018; Wolczanski, 2018). It involves the release of R–X from a (LnMXR) complex, where oxidation state, coordination number and electron of the metal center are reduced by two units. As a result of this propensity to activate a substrate by opening low-energy reaction pathways, the activity of organometallic catalysts can be so high that a <10−6 M active metal concentration is sufficient for carrying out the reaction efficiently: in these cases, catalyst separation and recovery from the products might even be avoided, as it occurs in some industrial polymerization processes (Stürzel et al., 2016). This notwithstanding, catalyst recovery is still necessary is many cases, and typically more easily achievable with heterogenous rather than molecular systems. For this reason, industrially relevant molecular catalysts are often heterogenized onto suitable supports, as mentioned above, leading to heterogeneous catalysts with similar (ideally the same) activity and selectivity to the molecular counterpart, but with the additional advantage of being easy to separate from the reaction environment and recycle (Schwarz et al., 1995; McNamara et al., 2002; Witzke et al., 2020). Selectiv","PeriodicalId":73071,"journal":{"name":"Frontiers in catalysis","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44529299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-28DOI: 10.3389/fctls.2021.708319
Yi‐Jun Xu
Photocatalysis is a Promising Technology for Energy and Environmental Protection The current rapid industrial development causes both a heavy reliance on non-renewable energy and a dramatic increase in atmospheric CO2 concentration, which in turn lead to severe energy and environmental crises (Zhang et al., 2015; Li et al., 2019; Li et al., 2020; Li et al., 2021). Therefore, it is urgent to consider how to develop new energy to meet the sustainable development of society. Nowadays, direct solar-to-fuel conversion through green photocatalysis technology has received increasing research interests due to its potential for solar energy utilization and storage to relieve the growing energy demands and greenhouse effect (Habisreutinger et al., 2013). With the expansion and deepening of the research, photocatalysis technology has been extended to many fields, such as energy, health, environment, pollution control and value-added chemicals synthesis (Lu et al., 2020). As a result, the relevance of photocatalysis and human life has been increasing steadily. The grand challenge of photocatalysis today is to further expand the practical application of photocatalytic technology in the industrial field, which requires future research to pay attention to the following aspects:
当前工业的快速发展导致对不可再生能源的严重依赖和大气CO2浓度的急剧增加，从而导致严重的能源和环境危机(Zhang et al.， 2015;Li et al.， 2019;Li et al.， 2020;Li等人，2021)。因此，如何开发新能源以满足社会的可持续发展是迫切需要考虑的问题。如今，通过绿色光催化技术直接将太阳能转化为燃料已经受到越来越多的研究兴趣，因为它具有利用和储存太阳能以缓解日益增长的能源需求和温室效应的潜力(Habisreutinger et al.， 2013)。随着研究的扩大和深入，光催化技术已扩展到能源、健康、环境、污染控制和增值化学品合成等多个领域(Lu et al.， 2020)。因此，光催化与人类生活的相关性一直在稳步增加。光催化今天面临的巨大挑战是进一步扩大光催化技术在工业领域的实际应用，这需要未来的研究关注以下几个方面:
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Pub Date : 2021-05-21DOI: 10.3389/fctls.2021.683248
L. Bretschneider, Ingeborg Heuschkel, Martin Wegner, M. Lindmeyer, Katja Bühler, R. Karande, B. Bühler
6-hydroxyhexanoic acid (6HA) represents a polymer building block for the biodegradable polymer polycaprolactone. Alternatively to energy- and emission-intensive multistep chemical synthesis, it can be synthesized directly from cyclohexane in one step by recombinant Pseudomonas taiwanensis harboring a 4-step enzymatic cascade without the accumulation of any intermediate. In the present work, we performed a physiological characterization of this strain in different growth media and evaluated the resulting whole-cell activities. RB and M9* media led to reduced gluconate accumulation from glucose compared to M9 medium and allowed specific activities up to 37.5 ± 0.4 U gCDW −1 for 6HA synthesis. However, 50% of the specific activity was lost within 1 h in metabolically active resting cells, specifying growing cells, or induced resting cells as favored options for long-term biotransformation. Furthermore, the whole-cell biocatalyst was evaluated in a stirred-tank bioreactor setup with a continuous cyclohexane supply via the gas phase. At cyclohexane feed rates of 0.276 and 1.626 mmol min−1 L−1, whole-cell biotransformation occurred at first-order and zero-order rates, respectively. A final 6HA concentration of 25 mM (3.3 g L−1) and a specific product yield of 0.4 g gCDW −1 were achieved with the higher feed rate. Product inhibition and substrate toxification were identified as critical factors limiting biocatalytic performance. Future research efforts on these factors and the precise adjustment of the cyclohexane feed combined with an in situ product removal strategy are discussed as promising strategies to enhance biocatalyst durability and product titer and thus to enable the development of a sustainable multistep whole-cell process.
6-羟基己酸（6HA）代表可生物降解聚合物聚己内酯的聚合物构建块。作为能量和排放密集型多步化学合成的替代方案，它可以由含有4步酶级联的重组黄山假单胞菌直接从环己烷一步合成，而无需任何中间体的积累。在目前的工作中，我们在不同的生长培养基中对该菌株进行了生理学表征，并评估了由此产生的全细胞活性。与M9培养基相比，RB和M9*培养基减少了葡萄糖中葡萄糖酸盐的积累，并允许6HA合成的比活性高达37.5±0.4 U gCDW−1。然而，在代谢活跃的静息细胞中，50%的比活性在1小时内丧失，将生长细胞或诱导的静息细胞指定为长期生物转化的有利选择。此外，在通过气相连续供应环己烷的搅拌槽生物反应器装置中对全细胞生物催化剂进行了评估。在0.276和1.626 mmol min−1 L−1的环己烷进料速率下，全细胞生物转化分别以一级和零级速率发生。在较高的进料速率下，6HA的最终浓度为25 mM（3.3 g L−1），比产物产率为0.4 g gCDW−1。产物抑制和底物毒性被确定为限制生物催化性能的关键因素。未来对这些因素的研究工作以及环己烷进料的精确调整与原位产物去除策略相结合，被讨论为提高生物催化剂耐久性和产物滴度的有前景的策略，从而能够开发可持续的多步骤全细胞工艺。
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Pub Date : 2021-04-15DOI: 10.3389/fctls.2021.658965
F. Studt
Catalysis is a cornerstone of modern societies as over 90% of processes in the chemical industry are facilitated by catalysts, with the majority requiring a homogeneous or heterogeneous catalyst (Hagen, 2015). Future renewable energy scenarios also rely heavily on the utilization of electro-catalysts, e.g., for the production of clean hydrogen. This shift towards new feedstocks and benign processes entails the development of new generations of catalysts. While the discovery of catalysts has often relied on trial and error in the first half of the last century, the establishment of (design) rules has significantly improved the speed with which new catalysts are being discovered. To this end, the knowledge-based improvement and design of new catalysts is increasingly supported by quantum chemical calculations of reaction mechanisms and kinetic modeling of corresponding reaction rates. In fact, first examples of catalyst design by means of computational screening have already emerged (Nørskov et al., 2009; Medford et al., 2015; Zhao et al., 2019). The extent to which computational modeling becomes a dominant factor in the catalysis community in the 21st century depends crucially on the accuracy with which predictions can be made, but also on the development of a reductionist approach, where the main contributing factors to the performance of a given class of catalysts are reduced to a few selected key parameters that can be used efficiently for computational screening. Perhaps the most challenging issue in computational catalysis is the fact that the rate constant of a reaction step changes drastically with minor changes of the reaction barrier (e.g., for a reaction occurring at 500 K by a factor of about 120 for typical errors of ±20 kJ/mol, or a factor of approximately 3 for an error ±5 kJ/mol, that is commonly referred to as chemical accuracy) and that only approximate methods are computationally feasible for the calculation of enthalpy and entropy contributions of a transition states free energy as the catalytic systems are often large and complex. In all fields discussed here (homogeneous, heterogeneous and electro-catalysis) density functional theory (DFT) has become the workhorse of computational studies as it exhibits the best compromise between accuracy and computational cost. In homogeneous catalysis for example, the enthalpy related to the active site of a transition-metal complex can be determined quite accurately with advanced hybrid functionals (Jiang et al., 2012). However, homogeneous catalysts often exhibit large ligands raising the issue of conformational complexity that is difficult to model. This is often getting even more problematic with solvation and leads to difficulties in determining the active conformational space and corresponding enthalpy and particularly entropy contributions to the free energy (Harvey et al., 2019). A balanced description of interand intramolecular interactions during solvation is similarly challenging
催化是现代社会的基石，因为化学工业中超过90%的过程都是由催化剂促进的，其中大多数需要均相或非均相催化剂(Hagen, 2015)。未来的可再生能源方案也严重依赖于电催化剂的利用，例如用于生产清洁氢。这种向新原料和良性工艺的转变需要开发新一代催化剂。虽然在上个世纪上半叶，催化剂的发现往往依赖于试验和错误，但(设计)规则的建立大大提高了发现新催化剂的速度。为此，基于知识的新型催化剂的改进和设计越来越多地得到反应机理的量子化学计算和相应反应速率的动力学建模的支持。事实上，通过计算筛选来设计催化剂的第一个例子已经出现(Nørskov et al.， 2009;Medford et al.， 2015;Zhao et al.， 2019)。计算建模在21世纪成为催化界的主导因素的程度主要取决于预测的准确性，但也取决于还原论方法的发展，在这种方法中，对特定类型催化剂性能的主要影响因素被简化为几个选定的关键参数，这些参数可以有效地用于计算筛选。也许计算催化中最具挑战性的问题是，反应阶跃的速率常数随着反应势垒的微小变化而急剧变化(例如，对于发生在500 K下的反应，典型误差为±20 kJ/mol时，速率常数约为120倍，误差为±5 kJ/mol时，速率常数约为3倍)。这通常被称为化学精度)，并且只有近似的方法在计算过渡态自由能的焓和熵贡献时是可行的，因为催化系统通常是大而复杂的。在这里讨论的所有领域(均相、多相和电催化)中，密度泛函理论(DFT)已经成为计算研究的主要方法，因为它展示了精度和计算成本之间的最佳折衷。例如，在均相催化中，使用先进的杂化官能团可以相当准确地确定与过渡金属配合物活性位点相关的焓(Jiang etal .， 2012)。然而，均相催化剂通常表现出大配体，引起难以建模的构象复杂性问题。这在溶剂化过程中往往会变得更加成问题，并导致难以确定活性构象空间和相应的焓，特别是熵对自由能的贡献(Harvey et al.， 2019)。在溶剂化过程中平衡描述分子间和分子内相互作用同样具有挑战性(Schmidt et al.， 2013)。在大部分非均相催化(例如，负载过渡金属)中，需要用简单的扩展周期表面模型来近似活性位点，该模型通常忽略了颗粒大小和形状以及颗粒-支撑相互作用的影响。此外，使用广义梯度近似(GGA)的泛函通常是唯一适用的选择，最佳泛函的吸附能误差为±20 kJ/mol (Wellendorff等人，2015)。编辑和审查:Frank Hollmann，代尔夫特理工大学，荷兰
{"title":"Grand Challenges in Computational Catalysis","authors":"F. Studt","doi":"10.3389/fctls.2021.658965","DOIUrl":"https://doi.org/10.3389/fctls.2021.658965","url":null,"abstract":"Catalysis is a cornerstone of modern societies as over 90% of processes in the chemical industry are facilitated by catalysts, with the majority requiring a homogeneous or heterogeneous catalyst (Hagen, 2015). Future renewable energy scenarios also rely heavily on the utilization of electro-catalysts, e.g., for the production of clean hydrogen. This shift towards new feedstocks and benign processes entails the development of new generations of catalysts. While the discovery of catalysts has often relied on trial and error in the first half of the last century, the establishment of (design) rules has significantly improved the speed with which new catalysts are being discovered. To this end, the knowledge-based improvement and design of new catalysts is increasingly supported by quantum chemical calculations of reaction mechanisms and kinetic modeling of corresponding reaction rates. In fact, first examples of catalyst design by means of computational screening have already emerged (Nørskov et al., 2009; Medford et al., 2015; Zhao et al., 2019). The extent to which computational modeling becomes a dominant factor in the catalysis community in the 21st century depends crucially on the accuracy with which predictions can be made, but also on the development of a reductionist approach, where the main contributing factors to the performance of a given class of catalysts are reduced to a few selected key parameters that can be used efficiently for computational screening. Perhaps the most challenging issue in computational catalysis is the fact that the rate constant of a reaction step changes drastically with minor changes of the reaction barrier (e.g., for a reaction occurring at 500 K by a factor of about 120 for typical errors of ±20 kJ/mol, or a factor of approximately 3 for an error ±5 kJ/mol, that is commonly referred to as chemical accuracy) and that only approximate methods are computationally feasible for the calculation of enthalpy and entropy contributions of a transition states free energy as the catalytic systems are often large and complex. In all fields discussed here (homogeneous, heterogeneous and electro-catalysis) density functional theory (DFT) has become the workhorse of computational studies as it exhibits the best compromise between accuracy and computational cost. In homogeneous catalysis for example, the enthalpy related to the active site of a transition-metal complex can be determined quite accurately with advanced hybrid functionals (Jiang et al., 2012). However, homogeneous catalysts often exhibit large ligands raising the issue of conformational complexity that is difficult to model. This is often getting even more problematic with solvation and leads to difficulties in determining the active conformational space and corresponding enthalpy and particularly entropy contributions to the free energy (Harvey et al., 2019). A balanced description of interand intramolecular interactions during solvation is similarly challenging","PeriodicalId":73071,"journal":{"name":"Frontiers in catalysis","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46623261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-04-13DOI: 10.3389/fctls.2021.669260
Sara El Hakim, T. Chave, A. Nada, S. Roualdès, S. Nikitenko
In this work, we provide new insights into the design of Ti@TiO2 photocatalyst with enhanced photothermal activity in the process of glycerol reforming. Ti@TiO2 nanoparticles have been obtained by sonohydrothermal treatment of titanium metal nanoparticles in pure water. Variation of sonohydrothermal temperature allows controlling nanocrystalline TiO2 shell on Ti0 surface. At 100 < T < 150°C formation of TiO2 NPs occurs mostly by crystallization of Ti(IV) amorphous species and oxidation of titanium suboxide Ti3O presented at the surface of Ti0 nanoparticles. At T > 150°C, TiO2 is also formed by oxidation of Ti0 with overheated water. Kinetic study highlights the importance of TiO2 nanocrystalline shell for H2 generation. Electrochemical impedance spectroscopy points out more efficient electron transfer for Ti@TiO2 nanoparticles in correlation with photocatalytic data. The apparent activation energy, Ea = (25–31) ± 5 kJ·mol−1, assumes that photothermal effect arises from diffusion of glycerol oxidation intermediates or from water dynamics at the surface of catalyst. Under the heating, photocatalytic H2 emission is observed even in pure water.
本研究为甘油重整过程中光热活性增强的Ti@TiO2光催化剂的设计提供了新的见解。在纯水中对金属钛纳米粒子进行超声水热处理，得到了Ti@TiO2纳米粒子。通过改变水热温度，可以控制Ti0表面的纳米TiO2壳层。在100 < T < 150℃时，TiO2 NPs的形成主要是通过钛(IV)非晶态的结晶和Ti0纳米颗粒表面的亚氧化钛ti30氧化来实现的。在150℃时，TiO2也是由Ti0与过热水氧化而形成的。动力学研究强调了TiO2纳米晶壳对H2生成的重要性。电化学阻抗谱与光催化数据相关，指出Ti@TiO2纳米粒子更有效的电子转移。表观活化能Ea =(25-31)±5 kJ·mol−1，假设光热效应是由甘油氧化中间体扩散或催化剂表面的水动力学引起的。在加热条件下，即使在纯水中也能观察到光催化H2释放现象。
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Pub Date : 2021-03-18DOI: 10.3389/fctls.2021.667675
Xijun Hu, A. Yip
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Pub Date : 2021-02-22DOI: 10.3389/fctls.2021.633893
F. Hollmann, R. Fernández-Lafuente
Biocatalysis Is an Enabling Technology for Chemical Synthesis Biocatalysis comprises the use of nature’s catalytic repertoire to facilitate chemical reactions (Sheldon and Woodley 2018; Sheldon and Brady 2019). Enzymes catalyze a broad range of chemical transformations, generally under very mild reaction conditions and with high selectivity. These features make enzymes attractive catalysts for industrial chemical transformations, enabling less resource-consuming and waste-generating synthesis routes. Therefore, biocatalysis is already today an important pillar of chemistry and continues gaining relevance in academic research and in industrial application. The last two decades have seen an exponential expansion of biocatalytic tools ranging from new catalysts with tailored properties to new reaction engineering concepts. As a result, the relevance of biocatalysis in the chemical industry has been also increasing steadily. Today’s grand challenge in biocatalysis is to keep this impetus up and further consolidate and expand the toolbox of biocatalysis. A few aspects will be highlighted in the following:
生物催化是利用自然界的催化系统来促进化学反应(Sheldon and Woodley 2018;谢尔顿和布雷迪2019)。酶催化广泛的化学转化，通常在非常温和的反应条件下，具有很高的选择性。这些特点使酶成为工业化学转化的有吸引力的催化剂，实现了更少的资源消耗和产生废物的合成路线。因此，生物催化在今天已经成为化学的重要支柱，并在学术研究和工业应用中继续获得相关性。在过去的二十年里，生物催化工具呈指数级增长，从具有定制性能的新型催化剂到新的反应工程概念。因此，生物催化在化学工业中的重要性也在稳步增加。当今生物催化的重大挑战是保持这种动力，进一步巩固和扩大生物催化工具箱。以下将重点介绍几个方面:
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