On the Early Years of High Throughput Experimentation and

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On the Early Years of High Throughput Experimentation and Combinatorial Approaches in Catalysis and Materials Science Wilhelm Maier ACS Comb. Sci., Just Accepted Manuscript • DOI: 10.1021/acscombsci.8b00189 • Publication Date (Web): 02 Apr 2019 Downloaded from http://pubs.acs.org on April 7, 2019

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ACS Combinatorial Science

On the Early Years of High Throughput Experimentation and Combinatorial Approaches in Catalysis and Materials Science Wilhelm F. Maier*, i.R. Technische Chemie Saarland University, Campus 66123 Saarbruecken, Germany

ABSTRACT: A report on the early years of combinatorial materials science and technology. High throughput technologies (HTT) are found in life science and materials laboratories. While in life sciences HTT became long standard for academia as well as industry, HTT in materials became standard in industry, but not in academia. In life science successful drugs developed with HTT have been reported, while there is no information on successful materials, which made it to the market. Some initial development of HTT in materials sciences is summarized, especially early applications of artificial intelligence are mentioned. The outlook attempts to summarize the development of combinatorial materials sciences from the early years to today.

Research and development (R&D) in chemistry have long been and mostly still are based on single experiments, whose results are used to plan the next experimental steps. R&D acceleration through parallel experimentation has a long history. Schubert et al. describe early applications by Edison (1878), Mitasch (1909) and Ciamician (1912) [1]. Running experiments in parallel (on libraries) often reduces time and costs. Acceleration of R&D by combinatorial approaches is established and belongs to today’s portfolio of many companies. It is now well known, that such combinatorial research is more than running large numbers of experiments in parallel. Thorough planning of the experiments is essential (see below). First, some definitions are required: Combinatorial chemistry (CC) or combinatorial research point to the combination of parameters, such as chemical elements, solvents, additives, pre- and aftertreatments, and others. High Throughput Experimentation (HTE) points to the numeric variation of parameters, such as temperature, pressure, stirring speed, time, concentration and others. High throughput screening (HTS) is the parallel or rapid sequential testing of desired properties or functions, where especially optical methods (parallel testing) are typical for life science applications. Essential is the preparation of libraries (prepared either by parallel or sequential synthesis), which allow parallel (often optical methods) or rapid sequential testing of properties. For convenience, we

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address all of the above under the term high throughput technologies (HTT), which encompass CC libraries and their synthesis as well as screening technologies and data collection and mining. Historically HTT were formulated already in 1970, at that time called Multiple Sample Concept (MSC) [2]. Hanak, then a scientist at RCA, pointed out, that “the single experiments approach is expensive and inefficient, since it does not properly use the time and effort of the highly trained researcher” [2]. Hanak, who clearly was ahead of his time, prepared the first gradient libraries by physical vapor deposition (PVD) techniques in his searches for new superconducting alloys, photovoltaic materials and others. In his latest review he points to cermets, thin film photovoltaics and metallic superconductors, developed by MSC, as having benefited developments in his company [3]. Nevertheless, his approach was long ignored by industry as well as academia, in part owed to the lack of reliable technologies for wider applications and the early state of informatics and robotics. In life sciences the use of combinatorial approaches started already 14 years after Hanak in the mid 1980s. 1984 Geyson published the first spatially resolved 96 peptide library based on parallel peptide synthesis on microtiter plates [4], followed by Houghten in 1985 (tea-bag-method) [5]. The early stages of combinatorial synthesis of small molecules for the generation of compound libraries have been reviewed [6]. Much of biology is inherently combinatorial (DNA, proteins, polysaccharides, genes ...) and thus lends itself well to CC. HTT have entered many fields of molecular biology and pipetting- and other robots became rapidly standard equipment of life science laboratories. Reetz has early on applied combinatorial and evolution-based methods to create artificial enzymes for enantioselective catalysis [7]. Modern drug discovery relies increasingly on combinatorial chemistry [8]. Compound libraries and sophisticated screening technologies have approached sizes of millions. The impact of HTS on drug discovery has been nicely documented in an article, which also hints to the ever-growing importance of HTT in life science applications [9]. Common myths on HTS, such as poor quality, expensive and time consuming, anti-intellectual and irrational, fails to find leads for many targets, are commented and rebutted. Most impressive is a table of approved drugs developed with HTS and examples of HTS in drug discovery (see Fig 1).


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Figure 1: List of drugs developed/discovered by high throughput screening (from ref 9). Discovery of new molecular structures is the target of HTT in life science applications [9]. Even so opinions on the importance of HTT in life sciences remain controversial, especially in academia, HTT have become successful and well established in most industrial and academic pharmaceutical and life science laboratories. HTS in the search for new drugs encompasses combinatorial development of molecule libraries and screening of existing libraries with ever new assays as well as applications. In contrast to life science applications, HTT in materials science encompasses multi-parameter variations for synthesis and property screening of new materials, which include complex parameters, such as composition, conductivity, magnetic resistance, catalytic activity and selectivity, scratch resistance, color, electrode properties and many others (see below). For another 25 years after Hanak there have been very few publications associated with parallel experimentation to accelerate R&D in the area of materials and catalysis. In 1995 Schultz, a biological chemist, published a library of potential superconductors and its screening, an article which initiated the start of high throughput- and combinatorial materials research [10]. Schultz, having been exposed in his bioorganic research to the ingenious combinatorial processes of the immune system to generate antibodies against new antigens by genetically generating molecular diversity and selecting high affinity antibodies, started in the early 90s to apply these principles also to materials. He assembled materials scientists and physicists at Lawrence Berkeley Laboratory (LBL) of UC Berkeley to prepare potential superconductor libraries by physical vapor deposition (PVD) and screened them for superconductivity by measuring temperature dependent resistance by tiny 4point probes (10). What started as a high-risk research project supported by unrestricted funds (prize money; Schultz was unable to get federal funding for these projects (personal communication)) rapidly developed into the ground breaking and highly noticed genesis of HTT in materials science and catalysis. Together with Zaffaroni, Schultz founded in 1994 SYMYX, the first company based on ACS Paragon Plus Environment


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combinatorial technologies for the discovery of new materials. After several additional projects on phosphors, ferroelectrics and others (see for example [11]) Schultz moved out of the materials field (with the exception of using DNA to template nanocrystal assemblies) to focus on his main interests, drug discovery and chemical biology, where he is still active.

1995: P.G. Schultz 1996: F.C. Moates 1998: H. Koinuma; W.F. Maier; D.E. Akporiaye; R. Wendelboo; R.B. van Dover; S.M. Senkan 1999: T. Bein; S. Kobayashi; M. Baerns; F. Schüth; P. Claus; I.E. Maxwell 2000: D. Wolf; Y. Matsumoto; E.J. Amis, J.C. Meredith; A. Karim 2001: M. Bradley; J.N. Cawse; M.J. Fasolka; K. Rajan; J. Holmgreen; J. Lauterbach; R.A. Potyrailo; Y. Matsumoto; T. Chikyow; A. Ludwig; M. Lippmaa; D.S. Ginley; E.S. Smotkin; I. Takeuchi; J.R. Hattrick-Simpers 2002: M. Watanabe; J.K. Norskov; K. Fujimoto; D. Ginley; A. Corma; S.I. Woo 2003: V.M. Mirsky; U.S. Schubert; B. Hayden; C. Mirodatos; D. Farruseng; W. Schrof; M. Lippma; P.A. Jacobs; J.A. Martens; U.Dingerdissen..............

Table 1: chronological order of selected authors according to first publications related to HTT or combinatorial materials research other than Schultz-coworkers or SYMYX.

From 1995 to 1998 only Schultz and SYMYX published HTT of materials (see ref. [12]). A lonely exception here is the publication by Moates in 1996, who applied infrared thermography to visualize the heat of combustion of H2 on a library of catalysts [13]. From 1995 it took 3 years until research groups beyond Schultz’ started to publish their new HT-research. Table 1 provides a listing of some scientists, which remained active in the field of combinatorial materials science, ordered according to appearance of first publications indicating activity in HTT or combinatorial materials research in the open literature or meetings/conferences. The listing not only shows how the global activity in combinatorial materials research evolved after the Schultz-publication, it also may document, that there has been no engagement of other laboratories in HT-materials research globally before 1995 besides the Schultz group and SYMYX. The table does not claim perfection and may miss some publication activities, especially those from conferences or workshops.

After 1998 HTT developed rapidly in many laboratories around the globe. Spatially resolved mass spectrometry, gas chromatography, conductivity, and many other HT-characterization methods have been presented. A productive workflow requires HT-synthesis of libraries, automated performance measurements, data collection and data evaluation as well as thorough planning of libraries based on


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knowledge from the literature and data collections [14] (see also Fig. 2). These requirements were met by many research groups early in the field, who built their own workflow in academia or industry. Today the installation and maintenance of such a complete workflow is very expensive, only affordable for industry and thus almost prohibitive for academic laboratories.

Library

Measurement of performance/ properties

Fig. 2: required workflow for productive application of high throughput technologies in materials and catalysis research (modified Fig. 1 from ref. [14]). Skepticism towards combinatorial approaches in materials research has been common in industry and academia, not only in the late 1990th, some is still there today and not without reason. Very careful and ongoing control of reliability and reproducibility of the experimental setup are always required to avoid false positives or false negatives. Examples of early arguments contra (too many parameters, solids are too complicated) and pro (R&D-acceleration, more information in a shorter time) are found in critical letters [15, 16, 17]. Nevertheless, the concept spread and HTT entered many laboratories. The initial focus on development of new technologies and discovery of new materials and catalysts resulted in a flood of patenting and publishing. New catalysts for dream reactions, such as air oxidation of propene to propylene oxide, direct amination of benzene with ammonia and air, air oxidation of benzene to phenol and many others have been searched for by various newly developed HTT, but no new commercial process based on catalysts from these initial attempts has been reported. This early lack of success was regarded as a failure of the initial promises of combichem in materials. HTT were refined and improved over time, while the focus moved away from discoveries to improvement of known catalysts and materials. ACS Paragon Plus Environment


HTT was not only applied to problems in homogeneous and heterogeneous catalysis, luminescent and magnetic materials, but also to polymers, electrochemistry and electrodes, coatings, formulations and many other materials. The progress of these initial years has been reviewed [12, 18]. Already in 1997, Symyx published the PVD preparation and screening of a 2’ library of potential phosphors containing over 25.000 distinct compounds [19], see Fig. 3.

Figure 3: Solid state combinatorial library with over 25000 distinct compositions under UV-radiation, prepared in a search for new phosphors [19]. While this library shocked the community, it did not become a standard of HTT. In the following years, libraries typically contained tens to hundreds of distinct materials or continuous composition spreads. A review on the rapid development of HTT for materials synthesis has been presented in 2005 [20]. IR-thermography was used to identify catalytic activity on coded polymer beads [21]. After background correction IR-thermography allowed the direct visualization of small temperature effects indicative of chemical reactions on catalyst libraries [22]. Detection of catalytic activity on an 8x9 catalyst library for cyclohexane dehydrogenation to benzene by resonance enhanced multiphoton ionization was also reported in 1998 [23]. Parallel hydrothermal synthesis of zeolites in a 100-fold autoclave at 200 °C in 0.5 mL reaction volume led to solid phases, which had to be identified by single XRD-measurements [24]. The high spatial resolution of a GADDS-micro-diffractometer was used in the same year for automated phase analysis of zeolites from parallel hydrothermal synthesis on a 110 mg scale in 37 autoclave chambers on a Si-single crystal support [25]. ACS Paragon Plus Environment

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Already in 1980 the first 6-channel parallel gas phase microflow reactor has been reported [26]. The applications of parallel flow reactors were extended to rapid screening of oxidation reactions [27]. This reactor principle was perfected with the development of 16-fold and later 49-fold parallel reactors [28]. Multi-reactor-arrays have been reviewed in a report on Deacon-catalyst development with special emphasis on high corrosion resistance [29]. No significant progress or practical application of such multi-reactors has been reported since. The early start and progress of HTT in catalysis has been reviewed already in 2001 [30]. The reliable parallel screening of polymerization catalysts or polymerization processes was initially regarded much too complex for HTT [16], just consider properties such as hardness, elasticity, scratch resistance, transmittance, reflectivity or the sensitivity of polymerization to impurities like moisture or oxygen, chain length, block and normal copolymers. Nevertheless, proper HTT have been developed and applied to many fields of polymer research. Already in 1998, SYMYX published HTT for the discovery of new polymerization catalysts using a parallel polymerization reactor [31]. Parallel synthesis and testing of ethylene polymerization catalysts was described by the hte-company [32]. A first overview on instrumentation for HT in polymer science was published in 2003 [33]. With the use of commercial robotics systems from Chemspeed new polymers and new materials have been developed [34]. Temperature, composition and thickness gradient libraries have been developed and used to search for optimal properties of polymers and polymer blends [35]. Gradient libraries of copolymers of ethylene with CO could be prepared by a cold plasma reactor [36]. Automated parallel determination of contact angles to predict adhesion properties have been reported [37] as well as the mapping of surface energies of di-block copolymer libraries [38] or parallel thermomechanical measurements [39]. With increasing automation and digitalization of our daily environment, there is an increasing demand for more selective and faster sensors (devices that recognize a change in gaseous or liquid composition of the selected environment and convert this information into a digital signal). Innovative HTT for sensor development have been presented early, the field has been reviewed in 2008 [40]. New superconductors, phosphors and ferroelectrics have been searched for with spatially resolved thin film libraries [12]. Composition spread or phase spread libraries remain popular in searches for electronic, magnetic, thermoelectric or other functional materials [41-43]. The search for lead free piezo electric materials led to many impressive publications as reviewed in [43]. Early approaches were based on submicron capacitor libraries and measurements with scanning force microscopy [44]. Composition spread techniques led to new discoveries of lead-free piezo materials [45,46]. HTT have been successfully developed for a broad range of materials, many are



summarized in table 2. To the best of my knowledge there is no published or public record of any such material developed with the help of HTT, that made it into practical application.

superconductor materials ferroelectric materials magnetoresistive materials luminescent materials structural materials hydrogen storage materials organic light-emitting materials ferromagnetic shape-memory alloys thermoelastic shape-memory alloys heterogeneous catalysts homogeneous catalysts polymerization catalysts electrochemical catalysts electrocatalysts for hydrogen evolution fuel cell anode catalysts enantioselective catalysts paints……….

zeolites polymers metal alloys materials for methanol fuel cells materials for SOFC materials for solar cells automotive coatings waterborne coatings vaporbarrier coatings marine coatings fouling-release coatings organic dyes polymeric sensing materials metal oxide sensing materials formulated sensing materials agricultural materials

Table 2: summary of materials, HTT have been developed and applied for [43] With increasing capacity and reliability of HTT, data collection and data analysis became a limiting factor. This was the time when informatics entering the field. Rather than optimizing one parameter at a time, multiparameter optimization was required and therefore the available tools from informatics and mathematics had to be adjusted. While rapidly library sizes became large, efficient assays and data handling were developed and applied early in HTT [47]. It was soon realized, that HTT only accelerate R&D, when reliable tools for data collection, data storage and data mining are applied. HTT start with the design of libraries, often utilizing design of experiment (DoE). HTT cannot be based on large numbers (garbage in, garbage out) [48], false positives and false negatives have to be avoided. In order to increase the chances for success, individual library components have to be selected carefully based on previous knowledge, such as the literature or previous libraries. Factorial design and quantitative structure-activity relationships have been used for library design, data mining and optimization (genetic algorithms and evolutionary strategies, artificial neural networks, factorial design) [49].


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For predictive modeling, which allows the prediction of the performance of unprepared materials, machine learning techniques (today integral part of artificial intelligence (AI)) have been applied already in 2003 [50]. Neural networks (NN) or artificial neural networks (ANN) require training on a selected data set. Although they often perfectly work within the training set, they may fail to predict points outside the training set due to overfitting [51]. Support vector machines (SVM), believed to overcome the problems of overfitting and parameter settings [51], have been applied successfully to many reactions, such as olefin epoxidation, gasoline isomerization and even for modeling of zeolite synthesis [52]. Visualization is often the most convincing way of data presentation due to the pattern recognition capabilities of human vision. This has long been recognized and practiced in life science HTapplications. HTT in materials research often provide complex data sets, which cannot be represented sufficiently in 2-dimensional plots, thus complex plots [46,53,54] with up to 5 dimensions have been realized [54]. Principal component analysis (PCA), aimed to reduce the dimensionality of complex data sets, can help to clarify data visualization [55]. Attempts in academia, institutes and industry to create a generalized data base for materials and catalysis suitable for data storage as well as for data mining date back to 2003 [56 – 58] and are still ongoing. While HTT have been developed for and applied to a wide variety of materials (see table 2) by scientists around the globe, new companies were founded. SYMYX had a strong head start resulting in a big patenting advantage and many early publications (see ref. [12]).

1994: SYMYX (P.G. Schultz; A. Zaffaroni / W.H. Weinberg, H.W.Turner, A.F. Volpe, E.W. McFarland; B. Jandeleit, A. Hagemeyer.... ) 1997: Chemspeed (R. Gueller) parallel synthesizer, parallel pressure reactions 1999: hte-company, Heidelberg (F. Schüth, D.Demuth, S. Schunk, W. Stichert, A. Brenner, W. Strehlau), 2000: AVANTIUM (I.E. Maxwell, spinoff Royal Dutch Shell), 2004: ILIKA (Southampton), B. Hayden, Materials, today Solid State Batteries 2006: Bosch Lab Systems (T. Brinz) Lab-automation systems for formulations Instrumentation companies: Gilson, Tekon, Parr, Mettler-Toledo, Sartorius, Thermo Fisher, Metz, …..... Table 3: Some of the earlier companies associated with HT-materials development Table 3 provides a brief overview over the start of initial companies associated to combinatorial materials development and some associated scientists. Table 3 merely shows that there is no indication of serious HTT activity before 1995 besides SYMYX and a surge of new companies afterwards. Only some instrumentation companies with prior activities in life science, such as pipetting robots, appeared before 1995. Already in 1997 Symyx had multimillion$-contracts with the Hoechst company and later with Exxon and various others. SYMYX published impressive



developments of HT equipment and libraries for polymers, catalysts and materials. Its strength was the use and development of new screening devices, such as autoclave reactors for parallel polymerization, catalysis reactors with spatially resolved mass spectrometry, rapid determination of polymer molar masses, particle size, viscosity, melt property, rheology, adhesion or modulus and others. Over the years SYMYX specialized in HT informatics and automation. In 2010 the software part became part of Accelrys, the laboratory robotics systems became Freeslate. hte-company, founded in 1999, focused on catalysis and early on put emphasis on the development of parallel testing conditions as close as possible to real process conditions. hte became a HT-service company, who must have successfully developed improved catalysts for a variety of process applications and for many different companies in the fields of energy & refinery, chemical production, polymerization, environmental catalysis and materials. The large number of customers (see www.hte-company.com) supports the conclusion, that many of hte developments made it into application. Aside from customer-oriented HT-research, hte sells equipment and software for catalyst testing under realistic conditions, for process development, scale-up and quality control. With about 300 employees, hte is probably the most successful high throughput company in the materials field. It has been acquired by BASF in 2008, but maintained its partial independence. Probably in 1999 a combinatorial research group was installed in the Polymer Division of the National Institute of Standards and Technologies (NIST), which helped to advance the HTT with very successful thin film and coating research [35]. Avantium, founded in 2000 as a Shell-spin-off, started with catalyst projects, developed parallel gas phase and trickle bed reactors and software, divestment started in 2003. 2005 Flamac (www.flamac.be), a research center for HT methodologies, was founded and is still going strong with emphasis on coating research. They offer their HT-platforms (synthesis, formulation, application, screening and thin film deposition) for projects with interested partners from industry and academia. At about 2001 UOP reported on conferences about the successful installation of a HT-department for in-house R&D. In the meantime, all larger chemical and oil companies, such as UOP, DowDuPont, BAYER, BASF, SHELL, EXXON and many others have their in-house HT-departments. This has the disadvantage, that progress in the fields is often not shared with the scientific community. Success stories of industrial laboratories with HTT remain hidden and thus do not contribute to the reputation of HTT. Conclusion: The general progress of HTT has been reviewed regularly through journals [12], [43], [18], and books [59], [60]. Specialized reviews document the rapid and diverse initial progress of these new technologies in many disciplines, such as sensors [40], homogeneous and heterogeneous catalysis [61], [62], [63], [64], polymers [65], [66], or materials [20]. An excellent impression on the high


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scientific quality of HTT of today’s laboratories around the globe was obtained at the 10. International Workshop on Combinatorial Materials Science and Technology (COMBI2018) at Yokohama in October 2018. Aside from the traditional fields of HTT applications, there are important uses of HTT, which do not contribute to global science. Formulations is such a nonscientific field that strongly benefits from HTT. Typical examples are adhesives, composites, paints, coatings, detergents, but also confections in pharma, health care and food applications. Formulations are typical industrial product developments, dependent on a multitude of parameters. Due to its complexity, formulations do not lend themselves to scientific analysis, but rather belong to engineering of materials. The power of informatics methods and the robotics developed for HTT turned out to be perfect for the rapid and diverse parameter variations required in formulations. Here among others Bosch landed a clever concept with Bosch Lab Systems, a customer tailored robotic laboratory that benefits from Bosch packaging technologies. These complete robotic laboratories, comparable to productions lines, are expensive and tailored towards the desired products. Other such applications not open to global science are HTT for parameter optimization of pilot plants and process engineering. During the past 30 years new technologies for library preparation and property screening have been developed for a wide variety of materials and catalysts leading to intensive initial IP protection activity. The period of patenting basic new technologies in HTT is fading, it has moved to classic patenting of materials and catalysts. The information about the use of HTT for the development of new materials belong to the proprietary knowledge of commercial companies and does therefore not contribute to the reputation of HTT. In the early days of HTT in materials and catalysis, discovery rather than development and optimization of new catalysts and materials was regarded as the big promise, but no practical application has been reported. A true breakthrough discovery with HTT in materials science or catalysis has not been published. That there must be many such successful developments is obvious from the presence of HT-departments in most companies and institutes associated with materials and catalysts. With time HTT in materials research have focused increasingly on optimization and improvements of principally known materials or catalysts, a move from high to low risk projects. HTT have become reliable tools to accelerate R&D for many applications. Materials HTT have been so successful that HTT became standard in many companies and institutes, which either developed their own data base platforms or rely on commercial data bases, supplied by various companies, such as



hte, Accellrys, Avantium or others. A drawback of this development is certainly, that little is known about the true state of HTT in such proprietary environments. As shown in table 2, HTT have been successfully developed for a wide range of applications. What is not shown there is the great effort associated with the development of such HTT. Presumably many academic research laboratories could benefit greatly from applications of HTT and research could be accelerated significantly thus utilizing the public support money much more efficiently. However, academic HT-labs either still use standard programs, such as the limited MS EXCEL for data storage and visualization, or have long developed their data base tailored to the individual requirements of the laboratory. Prejudice and the additional effort and costs associated with tailoring more sophisticated HTT for the research of interest may be main reasons, which prevent the broad use of HTT in academic materials laboratories. State of the art academic applications of HTT increasingly focus in well equipped HT-laboratories on their established lab-specific applications or on collaborations with industry in high risk projects. Author information: *E-mail: [email protected]

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31 Boussie, T. R.; Coutard, C.; Turner,H.; Murphy, V.; Powers, T. S. Solid-Phase Synthesis and Encoding Strategies for Olefin Polymerization Catalyst Libraries. Angew. Chem. Int. Ed. 1998, 37, 3272-3275. 32 Kolb, P.; Demuth, D.; Newsam, J. M.; Smith, M. A.; Sundermann, A.; Schunk, S. A.; Bettonville, S.; Breulet, J., Francois, P., Parallel Synthesis and Testing of Catalysts for the Polymerization of Ethylene. Macromol. Rapid Commun. 2004, 25, 280-285. 33 Schmatloch, S.; Meier, M. A. R.; Schubert, U. S. Instrumentation for combinatorial and polymer research. Macromol. Rapid Commun. 2003, 24, 33-46. 34 Janoschka, T.; Hager, M.D.; Schubert U. S. Powering up for the future: radical polymers for battery applications. Adv. Mater. 2012, 24, 6397-6409. 35 Meredith, J.C.; Karim, A.; Amis, E.J. Combinatorial Methods for Investigations in Polymer Materials Science, MRS Bull. 2002, 27,330-335. 36 Terajima, T.; Koinuma, H.; A Cold Plasma Generator and its Applications to Combinatorial Copolymerization of Carbon Dioxide with Organic Molecules. Macromol. Rapid Commun. 2004, 25, 312-314. 37 Thaburet, J.-F.; Mizomoto, H.; Bradley, M. High-Throughput Evaluation of the Wettability of Polymer Libraries. Macromol. Rapid Commun. 2004, 25, 366-370. 38 Smith, A.P.; Sehgal, A.; Douglas, J.F.; Karim, A.; Amis, E.J. Combinatorial Mapping of Surface Energy Effects on Diblock Copolymer Thin Film Ordering. Macromol. Rapid Commun. 2003, 24, 131-135. 39 Kossuth, M. B.; Hajduk, D. A.; Freitag, C.; Varni, J. Parallel dynamic thermochemical measurements of polymer libraries. Macromol. Rapid Commun. 2004, 25, 243-248. 40 Potyrailo, R. A.; Mirsky, V. M. Combinatorial and High-Throughput Development of sensing materials: the first 10 years. Chem. Rev. 2008, 108, 770-813. 41 a) Xiang, X.-D., Takeuchi, I., Eds.; Combinatorial Materials Synthesis; Dekker: New York, 2003; b) Koinuma H.; Takeuchi, I. Combinatorial solid-state chemistry of inorganic materials. Nat. Mater. 2004, 3, 429-438;. 42 Meier, M. A. R.; Hoogenboom, R.; Schubert, U. S., Eds.; Combinatorial Materials Research and High-Throughput Experimentation in Polymer and Material Research, Macromol. Rapid, Commun. 2004, 21-33. 43 Potyrailo, R.; Rajan, K.; Stöwe, K.; Takeuchi, I.; Chisholm, B.; Lam, H. Combinatorial and high throughput screening of materials libraries: review of state of the art. ACS Comb. Sci. 2011, 13, 579–633. 44 Nagarajan, V.; Stanishevsky, A.; Chen, L.; Zhao, T.; Liu, B.-T.; Melngailis, J.; Roytburd, A. L.; Ramesh, R.; Finder, J.; Yu, Z.; Droopad, R.; K. Eisenbeiser, K. Realizing intrinsic piezoresponse in epitaxial submicron lead zirconate titanate capacitors on Si. Appl. Phys. Lett. 2002, 81, 4215-4217. 45 Fujino, S.; Murakami, M.; Anbusathaiah, V.; Lim, S.-H.; Nagarajan, V.; Fennie, C. J.;Wuttig, M.;Salamanca-Riba, L.; Takeuchi, I. Combinatorial discovery of a lead-free morphotropic phase boundary in a thin-film piezoelectric perovskite. Appl. Phys. Lett. 2008, 92, 202904 46 Kan, D.; Suchoski, R.; Fujino, S.; Takeuchi, I. Combinatorial investigation of structural and ferroelectric properties of A- and B-site co-doped BiFeO3 thin films. Integr. Ferroelectr. 2010, 111, 116-124. 47 Cawse, J. N., Ed. Experimental Design for combinatorial and High Throughput Materials Development. Wiley-Interscience: Hoboken NJ 2003. 48 Rothenberg, G. Data mining in catalysis: Separating knowledge from garbage. Catalysis Today 2008, 137, 2-10. 49 Schunk, S. A.; Böhmer, N.; Futter, C.; Kuschel, A.; Prasetyo, E.; Roussiére, T. High throughput technology: approaches of research in homogeneous and heterogeneous catalysis, Catalysis. 2013, 25, 172-215. 50 Holena, M.; Baerns, M. Feedforward neural networks in catalysis: A tool for the approximation of the dependency of yield on catalyst composition, and for knowledge extraction. Catal. Today 2003, 81, 485-494. ACS Paragon Plus Environment

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Reste: Despite its success, strong feelings against and for HTT in industry as well as in academia remain. While by now successful product developments with HTT have been reported for life science applications (f. e. new drugs), reports on successful new materials or catalysts obtained with HTT are still missing. That there must be many such successful developments is obvious from the presence of ACS Paragon Plus Environment


HT-departments in most companies and institutes associated with materials and catalysts (see also below).


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Graphics for table of contents:


On the Early Years of High Throughput Experimentation and

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