Optimization of multicomponent photopolymer formulations using high‐throughput analysis and kinetic modeling

While high throughput and combinatorial techniques have played an instrumental role in materials development and implementation, numerous problems in materials science and engineering are too complex and necessitate a prohibitive number of experiments, even when considering high throughput and combinatorial approaches, for a comprehensive approach to materials design. Here, we propose a unique combination of high throughput experiments focused on binary formulations that, in combination with advanced modeling, has the potential to facilitate true materials design and optimization in ternary and more complex systems for which experiments are never required. Extensive research on the development of photopolymerizable monomer formulations has produced a vast array of potential monomer/comonomer, initiator and additive combinations. This array dramatically expands the range of material properties that are achievable; however, the vast number of potential formulations has eliminated any possibility of comprehensive materials design or optimization. This limitation is addressed by maximizing the benefits and unique capabilities of high throughput experimentation coupled with predictive models for material behavior and properties. The high throughput experimentation‐model combination is useful to collect a limited amount of data from as few as 11 experiments on binary combinations of 10 analyzed monomers, and then use this limited data set to predict and optimize formulation properties in ternary resins that would have necessitated at least 1000 high throughput experiments and several orders of magnitude greater numbers of traditional experiments. A data analysis approach is demonstrated, and the model development and implementation for one model application in which a range of material properties are prescribed, and an optimal formulation that meets those properties is predicted and evaluated. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Combinatorial-designed multifunctional polymeric nanosystems for tumor-targeted therapeutic delivery

By definition, multifunctional nanosystems include several features within a single construct so that these devices can target tumors or other disease tissue, facilitate in vivo imaging, and deliver a therapeutic agent. Investigations of these nanosystems are rapidly progressing and provide new opportunities in the management of cancer. Tumor-targeted nanosystems are currently designed based primarily on the intrinsic physico-chemical properties of off-the-shelf polymers. Following fabrication, the surfaces of these nanoscale structures are functionalized for passive or active targeted delivery to the tumors. In this Account, we describe a novel approach for the construction of multifunctional polymeric nanosystems based on combinatorial design principles. Combinatorial approaches offer several advantages over conventional methods because they allow for the integration of multiple components with varied properties into a nanosystem via self-assembly or chemical conjugation. High-throughput synthesis and screening is required in polymer design because polymer composition directly affects properties including drug loading, retention in circulation, and targeting of the nanosystems. The first approach relies on the self-assembly of macromolecular building blocks with specific functionalities in aqueous media to yield a large variety of nanoparticle systems. These self-assembled nanosystems with diverse functionalities can then be rapidly screened in a high-throughput fashion for selection of ideal formulations, or hits, which are further evaluated for safety and efficacy. In another approach, a library of a large number of polymeric materials is synthesized using different monomers. Each of the formed polymers is screened for the selection of the best candidates for nanoparticle fabrication. The combinatorial design principles allow for the selection of those nanosystems with the most favorable properties based on the type of payload, route of administration, and the desired target for imaging and delivery.     

Studies on corrosion resistant properties of sacrificial primed IPN coating systems in comparison with epoxy–PU systems

The continuous development in the field of protective coatings and the search for newer materials with improved properties have led to the emergence of interpenetrating polymer networks (IPNs) as binders for high performance organic coatings for corrosion protection. In this study, one such ambient curing IPN polymer alloy poly(epoxy–urethane–acrylate) developed specially for use in protective coatings has been studied. Undercoat and a topcoat based on the alloy have been formulated and coated over zinc ethyl silicate primed steel surfaces. Similar formulations based on an epoxy polyamide undercoat and a PU topcoat has been formulated and coated over zinc ethyl silicate primed steel surfaces. Both the systems were evaluated for their physical and corrosion resistant properties by subjecting them to accelerated laboratory tests and field test at a corrosive location. The results are reported and conclusions drawn in this paper.     

Design of polymeric materials: Experiences and prescriptions

As process engineering has matured, research interest has shifted towards polymer product quality. In the past 20 years or so, the shift has progressed even further, as interest in polymer product quality has morphed into polymer product design. Product design is intended to be a targeted pursuit of optimal conditions that will yield polymers with desirable properties for a specific application. This can be achieved by following a systematic design framework that employs sequential, iterative steps informed by prior knowledge and experience. This overview provides some background information regarding the need for design (including some examples from previous experience), especially in terms of structure‐property relationships. When links between kinetics (synthesis conditions), polymer structure, and application properties are well‐understood, it becomes possible to essentially reverse‐engineer the polymeric material; the researcher can start with known application requirements and synthesize polymers with tailor‐made properties using an optimized recipe (according to the polymerization kinetics). A suggested design approach is presented herein, followed by the application of the design approach to two large case studies. The number of applications for polymeric materials is essentially limitless; the current work provides typical examples of a systematic polymeric material design framework (and related case studies).     

Macromolecular engineering: a synthetic perspective

Abstract

It has long been a desire for both the polymer academic and industrial (production and process) communities to gain a true understanding of the effects of molecular architecture variables upon polymer properties and the implications for polymer process engineering. It has also long been realised that the greatest chance of gaining this insight is not to work with industrial grade materials, which are usually polydisperse both in terms of molecular weight and architecture, but to study model polymers, synthesised in the laboratory, usually by technically challenging methods such as anionic polymerisation. It is only by using polymers in which the molecular variables such as molecular weight, polydispersity and long chain branching are controlled with a high degree of precision, that we can hope to correlate these variables with key physical properties such as melt rheology, crystallinity and solid state properties. As polymer theoreticians develop ever more sophisticated models to predict the relationships between molecular structure and physical properties the challenge to the synthetic polymer chemist is to design and build (engineer) ever more complex yet well defined molecular structures to allow experimental validation (or otherwise) of the models. Here the author discusses how the synthetic chemist has risen to meet that challenge over the years.     

Sequestration of electroactive materials in a high Tg, insulating polymer matrix for optoelectronic applications. Part 1. Light emitting diode devices

The use of a high T_g, insulating polymer to sequester low molecular weight electroactive materials at high addition levels for utility in LED devices has been demonstrated. The threshold for effective light emission appears to be in the range of 15 wt% electroactive compounds in agreement with the percolation theory of deGennes. The high T_g polymer allows for suppression or elimination of the undesired crystallization of the electroactive species and yields a significant increase in the T_g of the light emitting layer (also required). Additionally this approach offers the potential for easier (and lower cost) fabrication routes not generally employed for low molecular weight electroactive materials (e.g. spin coating, ink jet printing, roll-to-roll printing). The improved mechanical properties of the light emitting layer with high molecular weight polymer addition should allow for improved performance/durability in flexible displays. The simple blend approach should be an attractive alternative to other more common methods reported in the literature employing covalent bonding of electroactive species to polymeric backbones to achieve the same results. This approach also allows for multiple addition of dopants (e.g. laser dyes), hole transport materials and electron transport materials in a single light emitting layer. While these results demonstrate the concept, optimization was not conducted and significant improvements would be expected with proper adjustment of the many variables possible with this approach.     

Polymer reaction engineering: From reaction kinetics to polymer reactor control

Polymer reaction engineering is a relatively “young”, very broad, multidisciplinary, rapidly developing field. It is the combination of polymer science, chemistry and technology with process engineering principles. The outcome of this high degree of synergism has evolved over the last fifteen or so years towards an area that includes any or all of the following: polymerization and post-polymerization (chemical modification) reaction kinetics; mathematical modelling and process simulation; polymer reactor design and scale-up; sensor development and process monitoring; and polymer reactor optimization, state estimation and computer control. This article will attempt to give an overview of the results obtained in our laboratory over the last seven years from systematic studies of polymer reaction engineering and polymer production technology problems. These problems cover all aspects of polymer reaction engineering mentioned above. Going from fundamentals to practice, the basic premise of the article is that only by adopting a holistic approach can one devise effective strategies in order to achieve the final objective of more efficient polymer reactor design and control, and hence improved production systems of polymeric materials.     

Evaluating the performance of designed terpolymers for polymer flooding

In this work, polymeric materials designed for enhanced oil recovery (EOR) were evaluated for their intended application. Properties including viscosity, flow through porous media (resistance factor and residual resistance factor), and heavy oil displacement (incremental oil recovery) were assessed for designed terpolymers of 2-acrylamido-2-methylpropane sulphonic acid (AMPS), acrylamide (AAm), and acrylic acid (AAc). The same properties were evaluated for two commercially available reference materials (e.g., partially hydrolyzed polyacrylamides or HPAM) with similar characteristics, which allowed for direct comparison between the newly designed terpolymers and materials that are currently on the market for the polymer flooding application. The incremental oil recovery directly associated with polymer flooding, which includes both the polymer flooding and post-polymer waterflooding stages (excluding the initial waterflooding injection (or secondary) oil recovery), demonstrates that the designed terpolymers provided a higher incremental recovery (42% and 58%) than the reference materials (33% and 46%). Therefore, the terpolymers provided a higher contribution to incremental (or enhanced) oil recovery than the typical HPAM. Additionally, both designed terpolymers showed better injectivity in unconsolidated porous media and are less likely to cause plugging than the commercially available reference materials. Therefore, using a targeted design approach ultimately led to polymeric materials with excellent performance for EOR polymer flooding applications.     

From electrons to infrastructure: Engineering concrete from the bottom up

An approach rooted in fundamental, mechanistic models of concrete materials offers the only viable path for handling the enormous number of variables that are being introduced as new materials are added to the design space, and as new properties are mandated for a sustainable infrastructure. These models must begin at the smallest length scales relevant for concrete properties; in some cases this is the scale of electron interactions among atoms and ions. But concrete has complex chemical and structural properties that are manifested at greater length and time scales, so atomic scale models must ultimately be integrated with new models that capture behavior at mesoscopic and macroscopic scales. We refer to this methodology as the "bottom-up" approach because it proceeds from the smallest length scales. We describe this kind of modeling approach, include some recent results, and suggest some principles for collaboratively integrating multi-scale models.