Combinatorial methods represent an appealing experimental method for the discovery of heterogeneous catalysts. One can efficiently identify candidate materials or sample vast regions of composition space using a combination of dense catalyst libraries and high-throughput reactivity screening techniques. This is particularly appealing for the discovery of novel catalysts for low temperature fuel cells where multi-component systems have shown improved performance. For example, the poison tolerance of typical anode catalysts can be improved by the addition of oxophilic components such as ruthenium, molybdenum, tin or osmium. Consequently, a vast composition space must be sampled in order to identify catalyst compositions or regions of composition space with greater activity. Combinatorial methods represent a practical means to speed-up the catalyst discovery process. In this manuscript, we demonstrate a novel method for combinatorial catalyst discovery based upon the synthesis and reactivity mapping of catalyst composition gradients. Samples consisting of uniform variations in surface composition of metals catalysts (Pt-M1 and Pt-M1−M2, where M1, M2 = Ru, Mo, Sn or Os) are fabricated using a gel-transfer technique. A concentration gradient of source metal ions is produced in a swollen polymer gel and then transferred onto a surface by electrodeposition to create a continuous composition gradient. An in situ reactivity-mapping tool based on the scanning electrochemical microscope is used to interrogate these catalyst gradients for the hydrogen oxidation reaction in the presence of adsorbed carbon monoxide.

We have developed a multichannel materials characterization system based on thickness-shear mode (TSM) sensors, also known as quartz crystal microbalances (QCMs). The sensors are arranged as a 6 × 4 array that is compatible with available 24-well plates that can be manipulated with standard robotic equipment. Our sensor system can measure frequencies from 5 MHz to 20 MHz with a noise level of less than 0.1 Hz for a 1 sec acquisition interval. The sensors can be placed in a gas-flow-though cell for studies of vapor-sorption properties, or they can be immersed into a 24-well plate array for studies of materials solubility. The sensor array is connected to the measurement electronics through a multi-conductor cable, enabling the sensors to be operated in a temperature, pressure, or chemical environment, which would otherwise adversely affect the electronic stability. The 24-channel array has been applied to the screening of sensor materials for determination of chlorinated organic solvents at part per billion levels in groundwater wells. The primary screen is the discovery screen where materials are exposed to a single analyte concentration. The secondary screen is the focused evaluation where the best subset of these materials is exposed to analytes and interferences. The tertiary screen involves evaluation of material performance under conditions mimicking the long-term application. Six families of potential sensor materials were examined with rapid downselection by using this approach.

A sol-gel process was used to synthesize potential combustion catalysts based on mixed oxides on several libraries. As mixed oxides a variety of doped Zr-Al-oxides and Ce-oxides were prepared. The catalytic activity of the materials was tested with the combustion of i-octane, n-butane and methane in synthetic air. Several Pt- and Rh-containing sol-gel materials showed effective methane combustion already at 60 °C under rich conditions and at 200 °C under lean conditions. Several noble metal free doped CeO2 catalysts combusted methane already at 300 °C under lean conditions. Combustion of i-octane was catalysed already at 125 °C. The most active catalysts were synthesized conventionally, characterized and catalytic activity was confirmed in a regular gas phase flow reactor.

State of the art commercial cathodes for solid oxide fuel cells (SOFC) include LaMnO3 with a zirconia-based electrolyte. However, the vacancy concentration in A site doped LaMnO3 is low, thus ionic conductivity is also very low (10−7 – 10−8 S/cm at 800 °C). The surface path dominates the reaction rate of the LaMnO3 cathode; therefore the optimized electrode is a porous composite material of both the cathode material and electrolyte and relies on triple-point boundaries for performance. The electrical conductivity and thermal expansion properties of this cathode material and other A3+B3+O3 perovskites can be tuned by substitution at the A and/or B site. The numerous combinations of composition, processing and microstructure needed for improved cathode performance is well suited for a high throughput screening (HTS) approach towards optimization and discovery. We present here a high throughput discovery process that includes, synthesis, performance testing and characterization techniques directed towards new low temperature SOFC cathode materials.

The predictions of a general “hierarchical model” for the rheology of general mixtures of linear and branched polymers are compared to experimental data for well-defined long-chain branched polymers. For a wide range of branched polymer melts, which include star-linear blends, H-polymers, and comb polymers, the predictions of the model agree well with experimental data. We apply the hierarchical model to metallocene-catalyzed polyethylenes (mPEs), in which the branched structures are generated by a Monte Carlo method based on the known reaction kinetics. The hierarchical model captures the shape of the curves of viscoelastic moduli vs. frequency of mPEs well and predicts accurately the effect of long chain branching on the linear viscoelastic properties. The quantitative agreement of the hierarchical model prediction with experimental data of well-defined long-chain branched polymers and mPEs shows that information on branching structure could be inferred from rheological measurements on combinatorial sets of mixtures of an unknown branched with different combinations of linear polymers.

A combinatorial approach has been utilized for researching the luminescence of rare-earth ions complexes (RE(DBM)3·Phen, RE=Dy3+, La3+, Gd3+, Sm3+, Y3+) sensitized Eu3+ complex in PMMA matrix. The results show that the La3+ complex has the maximum sensitization efficiency among these sensitization ions. The luminescent intensities increase as the Eu content increase in PMMA matrix. The La3+ complex exhibits higher sensitization efficiency at lower Eu content in PMMA matrix. At a content of 5% Eu complex, the maximum sensitization efficiency of La3+ is more than 20 times.

Large scale materials databases have been traditionally used for search and retrieval of experimental and theoretical data. In this paper, three different cases are used to illustrate applications of statistical techniques in databases that extend beyond searching. A complete large scale database of molten salts is visualized for pattern seeking. In the second case, a large virtual combinatorial library of chalcopyrite semiconductors is developed from a small experimental and theoretical dataset. This involves selecting statistically appropriate parameters based on the physics of the materials. In the third case, ‘secondary’ descriptors are developed for a zeolites database to better understand the topology of mesoporous structures and as a materials design tool. These examples serve to demonstrate how databases can be used to identify important combinations of parameters relevant to combinatorial experimentation.

New algorithms to design the microstructures in a ternary system with the solubility gap in one binary system have elaborated. They permit to visualize, to sect and to project a sophisticated surface with a trough.

Combinatorial chemistry has revolutionized the drug discovery as well as the catalyst discovery and optimization process during the last years. Nowadays, triggered by these developments, combinatorial methods and parallel chemistry also emerge in the field of material and polymer chemistry. Especially the field of polymer research seems to be perfectly suited for these approaches since many parameters can be varied during synthesis, processing, blending, formulation and compounding. Moreover, the screening of interesting parameters, such as molecular weight, polydispersity, polymerization kinetics, viscosity, hardness or stiffness, became feasible only recently.

Within this contribution we will describe our strategy to construct a most efficient workflow in the field of combinatorial polymer research. New developments made by our group as well as some general aspects will be discussed.