Combinatorial and High-Throughput Methods in Macromolecular Materials Research and Development

Generation and Characterization of a Library of Novel Biologically Active Functional Surfactants (Surfmers) Using Combined High-Throughput Methods

We report the first successful combination of three distinct high-throughput techniques to deliver the accelerated design, synthesis, and property screening of a library of novel, bio-instructive, polymeric, comb-graft surfactants. These three-dimensional, surface-active materials were successfully used to control the surface properties of particles by forming a unimolecular deep layer on the surface of the particles via microfluidic processing. This strategy deliberately utilizes the surfactant to both create the stable particles and deliver a desired cell-instructive behavior. Therefore, these specifically designed, highly functional surfactants are critical to promoting a desired cell response. This library contained surfactants constructed from 20 molecularly distinct (meth)acrylic monomers, which had been pre-identified by HT screening to exhibit specific, varied, and desirable bacterial biofilm inhibitory responses. The surfactant's self-assembly properties in water were assessed by developing a novel, fully automated, HT method to determine the critical aggregation concentration. These values were used as the input data to a computational-based evaluation of the key molecular descriptors that dictated aggregation behavior. Thus, this combination of HT techniques facilitated the rapid design, generation, and evaluation of further novel, highly functional, cell-instructive surfaces by application of designed surfactants possessing complex molecular architectures.

High-Throughput and Combinatorial Approaches for the Development of Multifunctional Polymers

High-throughput (HT) development of new multifunctional polymers is accomplished by the combination of different HT tools established in polymer sciences in the last decade. Important advances are robotic/HT synthesis of polymer libraries, the HT characterization of polymers, and the application of spatially resolved polymer library formats, explicitly microarray and gradient libraries. HT polymer synthesis enables the generation of material libraries with combinatorial design motifs. Polymer composition, molecular weight, macromolecular architecture, etc. may be varied in a systematic, fine-graded manner to obtain libraries with high chemical diversity and sufficient compositional resolution as model systems for the screening of these materials for the functions aimed. HT characterization allows a fast assessment of complementary properties, which are employed to decipher quantitative structure-properties relationships. Moreover, these methods facilitate the HT determination of important surface parameters by spatially resolved characterization methods, including time-of-flight secondary ion mass spectrometry and X-ray photoelectron spectroscopy. Here current methods for the high-throughput robotic synthesis of multifunctional polymers as well as their characterization are presented and advantages as well as present limitations are discussed.

Accelerating organic solar cell material's discovery: high-throughput screening and big data

The discovery of novel high-performing materials such as non-fullerene acceptors and low band gap donor polymers underlines the steady increase of record efficiencies in organic solar cells witnessed during the past years. Nowadays, the resulting catalogue of organic photovoltaic materials is becoming unaffordably vast to be evaluated following classical experimentation methodologies: their requirements in terms of human workforce time and resources are prohibitively high, which slows momentum to the evolution of the organic photovoltaic technology. As a result, high-throughput experimental and computational methodologies are fostered to leverage their inherently high exploratory paces and accelerate novel materials discovery. In this review, we present some of the computational (pre)screening approaches performed prior to experimentation to select the most promising molecular candidates from the available materials libraries or, alternatively, generate molecules beyond human intuition. Then, we outline the main high-throuhgput experimental screening and characterization approaches with application in organic solar cells, namely those based on lateral parametric gradients (measuring-intensive) and on automated device prototyping (fabrication-intensive). In both cases, experimental datasets are generated at unbeatable paces, which notably enhance big data readiness. Herein, machine-learning algorithms find a rewarding application niche to retrieve quantitative structure-activity relationships and extract molecular design rationale, which are expected to keep the material's discovery pace up in organic photovoltaics.

Replication of a Printed Volatile Mold: a novel microfabrication method for advanced microfluidic systems

A novel and simple method to fabricate microchannels is reported based on an inkjet printing of a volatile solid mold. A liquid ink -1,6 hexanediol- ejected from a piezoelectric nozzle is instantaneously frozen when touching a cooled substrate. The created mold is then poured with PDMS. Once the PDMS is crosslinked, the ink is sublimated and the device is ready. With this approach it is possible to make microchannels on different nature surfaces such as glass, paper, uncross-linked PDMS layer or non planar substrates. The versatility of this method is illustrated by printing channels directly on commercial electrodes and measuring the channel capacitance. Moreover, millimetric height microfluidic systems are easily produced (aspect ratio [Formula: see text] 25) as well as 3D structures such as bridges. To demonstrate, we have fabricated a combinatorial microfluidic system which makes 6 mixtures from 4 initial solutions without any stacking and tedious alignment procedure.

High throughput approaches for controlled stem cell differentiation

Stem cells have unique ability to undergo self-renewal indefinitely in culture and potential to differentiate into almost all cell types in the human body. However, the developing a method for efficiently differentiating or manipulating these stem cells for therapeutic purposes remains a challenging problem. Pluripotent stem cells, as well as adult stem cells, require biological cues for their proliferation and differentiation. These cues are largely controlled by cell-cell, cell-insoluble factors (such as extracellular matrix), and cell-soluble factors (such as cytokine or growth factors) interactions. In this review, we describe a state of research on various stem cell-based tissue engineering applications and high throughput strategies for developing synthetic or biosynthetic microenvironments to allow efficient commitments in stem cells.

STATEMENT OF SIGNIFICANCE

Nowadays, pluripotency of stem cells have received much attention to use therapeutic purpose. However, a major difficulty with stem cell therapy is to control its differentiation through desired cells or tissues. In other words, various microenvironment factors are involved during stem cell differentiation, including dimensionality, growth factors, cell junctions, nutritional status, matrix stiffness, matrix composition, mechanical stress, and cell-matrix adhesion. Therefore, researchers have engineered a variety of platforms to enable controlling and monitoring bioactive factors to induce stem cell commitment. In this review, we report on recent advancements in a novel technology based on high-throughput strategies for stem cell-based tissue engineering applications.

Parallel and combinatorial liquid-phase synthesis of alkylbiphenyls using pentaerythritol support

Unfunctionalized alkylbiphenyls were fabricated by a parallel and combinatorial synthesis using pentaerythritol as a tetrapodal soluble support for a sulfonate-based traceless multifunctional linker system. Nickel N-heterocyclic carbene-catalyzed reactions of pentaerythritol tetrakis(biphenylsulfonate)s with primary alkylmagnesium bromides generated the alkylbiphenyl derivatives by desulfitative cleavage/cross-coupling of the C-S bond without any "memory" of the attachment on the support. Though the reactions were completed with sufficient yields in 12 h at room temperature, even with only 1.5 equiv of nucleophiles, they still retained the benefits of facile isolation observed in polymer-supported reactions.

Materiomics: an -omics approach to biomaterials research

The past fifty years have seen a surge in the use of materials for clinical application, but in order to understand and exploit their full potential, the scientific complexity at both sides of the interface--the material on the one hand and the living organism on the other hand--needs to be considered. Technologies such as combinatorial chemistry, recombinant DNA as well as computational multi-scale methods can generate libraries with a very large number of material properties whereas on the other side, the body will respond to them depending on the biological context. Typically, biological systems are investigated using both holistic and reductionist approaches such as whole genome expression profiling, systems biology and high throughput genetic or compound screening, as already seen, for example, in pharmacology and genetics. The field of biomaterials research is only beginning to develop and adopt these approaches, an effort which we refer to as "materiomics". In this review, we describe the current status of the field, and its past and future impact on the biomedical sciences. We outline how materiomics sets the stage for a transformative change in the approach to biomaterials research to enable the design of tailored and functional materials for a variety of properties in fields as diverse as tissue engineering, disease diagnosis and de novo materials design, by combining powerful computational modelling and screening with advanced experimental techniques.

Analysis and prediction of defects in UV photo-initiated polymer microarrays

Polymer microarrays are a key enabling technology for the discovery of novel materials. This technology can be further enhanced by expanding the combinatorial space represented on an array. However, not all materials are compatible with the microarray format and materials must be screened to assess their suitability with the microarray manufacturing methodology prior to their inclusion in a materials discovery investigation. In this study a library of materials expressed on the microarray format are assessed by light microscopy, atomic force microscopy and time-of-flight secondary ion mass spectrometry to identify compositions with defects that cause a polymer spot to exhibit surface properties significantly different from a smooth, round, chemically homogeneous 'normal' spot. It was demonstrated that the presence of these defects could be predicted in 85% of cases using a partial least square regression model based upon molecular descriptors of the monomer components of the polymeric materials. This may allow for potentially defective materials to be identified prior to their formation. Analysis of the PLS regression model highlighted some chemical properties that influenced the formation of defects, and in particular suggested that mixing a methacrylate and an acrylate monomer and/or mixing monomers with long and linear or short and bulky pendant groups will prevent the formation of defects. These results are of interest for the formation of polymer microarrays and may also inform the formulation of printed polymer materials generally.

Combinatorial synthesis of photo-crosslinked biodegradable networks

PURPOSE

Photo-crosslinking is a technique that can accelerate the development of novel polymeric biomaterials.

METHODS

Here we show the development of a combinatorial platform to synthesize numerous synthetic biodegradable and biocompatible networks by photo-crosslinking mixtures of macromers.

RESULTS

Combinations of dimethacrylate-terminated macromers based on hydrophobic D,L-lactide (DLLA), trimethylene carbonate (TMC), epsilon-caprolactone (CL), and hydrophilic polyethylene glycol (PEG) were crosslinked into polymer networks with widely differing properties. The interaction of cells with the network surfaces was assessed by an in vitro cell seeding experiment in which cell proliferation was assessed using a DNA proliferation assay.

CONCLUSIONS

In this way, a hydrophilic material was identified that unexpectedly supported the proliferation of cells very well.

Spatially resolved solid-state 1H NMR for evaluation of gradient-composition polymeric libraries

Polyurethane libraries consisting of films with composition gradients of aliphatic polyisocyanate and hydroxy-terminated polyacrylate resin were characterized using methods of (1)H NMR microimaging (i.e., magnetic resonance imaging, (MRI)) and solid-state NMR. Molecular mobilities and underlying structural information were extracted as a function of the relative content of each of the two components. Routine NMR microimaging using the spin-echo sequence only allows investigations of transverse relaxation of magnetization at echo times >2 ms. A single-exponential decay was found, which is likely due to free, noncross-linked polymer chains. The mobility of these chains decreases with increasing content of the aliphatic polyisocyanate. The concept of a 1D NMR profiler is introduced as a novel modality for library screening, which allows the convenient measurement of static solid-state NMR spectra as a function of spatial location along a library sample that is repositioned in the rf coil between experiments. With this setup the complete transverse relaxation function was measured using Bloch decays and spin echoes. For all positions within the gradient-composition film, relaxation data consisted of at least three components that were attributed to a rigid highly cross-linked resin, an intermediate cross-linked but mobile constituent, and the highly mobile free polymer chains (the latter is also detectable by MRI). Analysis of this overall relaxation function measured via Bloch decays and spin echoes revealed only minor changes in the mobilities of the individual fractions. Findings with respect to the most mobile components are consistent with the results obtained by NMR microimaging. The major effect is the significant increase in the rigid-component fraction with the addition of the hydroxy-terminated polyacrylate resin.

NANOBIOMATERIALS LIBRARY SYNTHESIS FOR HIGH-THROUGHPUT SCREENING USING A DRY POWDER PRINTING METHOD

High-throughput (HT) screening and combinatorial searches for the discovery, development and optimization of functional materials have been widely accepted in many new materials discovery. Dry powder HT library synthesis have advantages such as using same powder materials in lab as in production, and avoiding the use of additives and/or solvents which could be harmful for cells. The VaryDose dry powder dispensing technology was adapted in this work to dispense nanobioceramic powders in quantities as low as 0.1 mg per dispensing. Nanocalcium phosphate biomaterials, including hydroxyapatite (HA) and β-tricalcium phosphate (β-TCP), were selected to demonstrate the library fabrication. The dispensing unit design and the effect of the dispensing parameters on dosage control and uniformity are discussed.

Design of pressure-driven microfluidic networks using electric circuit analogy

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Automated ARGET ATRP Accelerates Catalyst Optimization for the Synthesis of Thiol-Functionalized Polymers

Conventional synthesis of polymers by ATRP is relatively low throughput, involving iterative optimization of conditions in an inert atmosphere. Automated, high-throughput controlled radical polymerization was developed to accelerate catalyst optimization and production of disulfide-functionalized polymers without the need of an inert gas. Using ARGET ATRP, polymerization conditions were rapidly identified for eight different monomers, including the first ARGET ATRP of 2-(diethylamino)ethyl methacrylate and di(ethylene glycol) methyl ether methacrylate. In addition, butyl acrylate, oligo(ethylene glycol) methacrylate 300 and 475, 2-(dimethylamino)ethyl methacrylate, styrene, and methyl methacrylate were polymerized using bis(2-hydroxyethyl) disulfide bis(2-bromo-2-methylpropionate) as the initiator, tris(2-pyridylmethyl)amine as the ligand, and tin(II) 2-ethylhexanoate as the reducing agent. The catalyst and reducing agent concentration was optimized specifically for each monomer, and then a library of polymers was synthesized systematically using the optimized conditions. The disulfide-functionalized chains could be cleaved to two thiol-terminated chains upon exposure to dithiothreitol, which may have utility for the synthesis of polymer bioconjugates. Finally, we demonstrated that these new conditions translated perfectly to conventional batch polymerization. We believe the methods developed here may prove generally useful to accelerate the systematic optimization of a variety of chemical reactions and polymerizations.

Synthesis of soybean oil-based thiol oligomers

Industrial grade soybean oil (SBO) and thiols were reacted to generate thiol-functionalized oligomers via a thermal, free radical initiated thiol-ene reaction between the SBO double bond moieties and the thiol functional groups. The effect of the reaction conditions, including thiol concentration, catalyst loading level, reaction time, and atmosphere, on the molecular weight and the conversion to the resultant soy-thiols were examined in a combinatorial high-throughput fashion using parallel synthesis, combinatorial FTIR, and rapid gel permeation chromatography (GPC). High thiol functionality and concentration, high thermal free radical catalyst concentration, long reaction time, and the use of a nitrogen reaction atmosphere were found to favor fast consumption of the SBO, and produced high molecular weight products. The thiol conversion during the reaction was inversely affected by a high thiol concentration, but was favored by a long reaction time and an air reaction atmosphere. These experimental observations were explained by the initial low affinity of the SBO and thiol, and the improved affinity between the generated soy-thiol oligomers and unreacted SBO during the reaction. The synthesized soy-thiol oligomers can be used for renewable thiol-ene UV curable materials and high molecular solids and thiourethane thermal cure materials.

Combinatorial synthesis of chemically diverse core-shell nanoparticles for intracellular delivery

Analogous to an assembly line, we employed a modular design for the high-throughput study of 1,536 structurally distinct nanoparticles with cationic cores and variable shells. This enabled elucidation of complexation, internalization, and delivery trends that could only be learned through evaluation of a large library. Using robotic automation, epoxide-functionalized block polymers were combinatorially cross-linked with a diverse library of amines, followed by measurement of molecular weight, diameter, RNA complexation, cellular internalization, and in vitro siRNA and pDNA delivery. Analysis revealed structure-function relationships and beneficial design guidelines, including a higher reactive block weight fraction, stoichiometric equivalence between epoxides and amines, and thin hydrophilic shells. Cross-linkers optimally possessed tertiary dimethylamine or piperazine groups and potential buffering capacity. Covalent cholesterol attachment allowed for transfection in vivo to liver hepatocytes in mice. The ability to tune the chemical nature of the core and shell may afford utility of these materials in additional applications.

HIGH-THROUGHPUT KINETIC STUDY OF PEROXIDE CURING OF EPDM RUBBER

Mixing of EPDM and a peroxide curative via a solution route and subsequent curing were performed in a downscaled set-up. The resulting vulcanizates were characterized by a down-scaled hardness measurement and by Raman spectroscopy in a high-throughput experimentation compatible approach. The characterization results obtained on these vulcanizates agreed well with those obtained on corresponding vulcanizates prepared via conventional mill mixing. By indentation on vulcanizates cured for various curing times, a rheometer curve could be constructed. The conversion of the EPDM unsaturation and, thus, the extent of the addition reactions was quantified by Raman spectroscopy. Using both the indentation and the Raman data, the cross-link density resulting from combination reactions was estimated.

High throughput surface characterization: A review of a new tool for screening prospective biomedical material arrays

The application of high throughput surface characterization (HTSC) to the analysis of polymeric biomaterial libraries is an important advancement for the discovery and development of new biomedical materials and is the focus of this review. The potential for HTSC to identify structure/activity relationships for large libraries of materials can be utilized to accelerate materials discovery as well as providing insight into the underlying biological-material interactions. Furthermore, the correlations identified between surface chemical structure and cellular behavior could not have been predicted by a rational design approach based simply on review of bulk structure, which demonstrates the importance of HTSC in the assessment of cell-material and cell-biomolecular interactions that are dependent on surface properties.

High throughput methods applied in biomaterial development and discovery

The high throughput discovery of new bio materials can be achieved by rapidly screening many different materials synthesised by a combinatorial approach to identify the optimal composition that fulfils a particular biomedical application. Here we review the literature in this area and conclude that for polymers this process is best achieved in a microarray format, which enable thousands of cell-material interactions to be monitored on a single chip. Polymer microarrays can be formed by printing pre-synthesised polymers or by printing monomers onto the chip where on-slide polymerisation is initiated. The surface properties of the material can be analysed and correlated to the biological performance using high throughput surface analysis, including time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS) and water contact angle (WCA) measurements. This approach enables the surface properties responsible for the success of a material to be understood, which in turn provides the foundations of future material design. The high throughput discovery of materials using polymer microarrays has been explored for many cell-based applications including the isolation of specific cells from heterogeneous populations, the attachment and differentiation of stem cells and the controlled transfection of cells. Further development of polymerisation techniques and high throughput biological assays amenable to the polymer microarray format will broaden the combinatorial space and biological phenomenon that polymer microarrays can explore, and increase their efficacy. This will, in turn, facilitate the discovery of optimised polymeric materials for many biomaterial applications.

Partial least squares regression as a powerful tool for investigating large combinatorial polymer libraries

Partial Least Squares (PLS) regression is an established analytical tool in surface science, particularly for relating multivariate ToF-SIMS data to a univariate surface property. Herein we construct a PLS model using ToF-SIMS and surface energy data from a 496 copolymer micro-patterned library. Using this 496 copolymer library we investigate how changing the number of samples used to construct the PLS model affects the identity of the most influential ions identified in the regression vector. The regression coefficients vary in magnitude, but the general relationship between ion structure and surface energy is maintained. As expected, if copolymers containing monomers with unique chemistries are removed from the training set, secondary ions specific to these copolymers are not present in the regression vector. The use of PLS to obtain quantitative predictions has not been actively explored in the surface analytical field. We investigate whether the PLS model obtained can be used to predict the surface energies of polymers within and outside of the training set. The model systematically underestimated the surface energy of a group of acrylate copolymers synthesised using monomers common to the training set, but in different compositions. The predictions for a group of acrylate copolymers that were synthesised from monomers not used in the training set were very poor. When the model was used to obtain predictions for six commercially available polymers the values obtained were all close to the mean surface energy of the training set. This exercise suggests that PLS may be able to predict the surface energy of polymers synthesised from monomers common to the training set, confirming the importance that the training set reflects the chemistry of the samples to be predicted.