General route to design polymer molecular weight distributions through flow chemistry

Scalable and Precise Synthesis of Structurally Colored Bottlebrush Block Copolymers: Enabling Refined Color Calibration for Sustainable Photonic Pigments

Self-assembled bottlebrush block copolymers (BBCPs) offer a vibrant, eco-friendly alternative to traditional toxic pigments and dyes, providing vivid structural colors with significantly reduced environmental impact. Scaling up the synthesis of these polymers for practical applications has been challenging with conventional batch methods, which suffer from slow mass and heat transfer, inadequate mixing, and issues with reproducibility. Precise control over molecular weight and dispersity remains a significant challenge for achieving finely tuned color appearances. Here, we present an alternative strategy to overcome the challenges by integrating a rapid continuous flow technique with an in-line self-assembly procedure. This strategy enables the rapid, stable and large-scale synthesis of narrow-dispersed BBCPs, exceeding 2 kg/day, a significant improvement over conventional gram-scale methods. Furthermore, precise control over the degree of polymerization is achieved with an unprecedented interval accuracy of four repeat units. This level of precision enables refined color calibration in the resulting photonic pigments, effectively eliminating the need for labor-intensive and costly multiple batch syntheses.

Unlocking regioselectivity: steric effects and conformational constraints of Lewis bases in alkyllithium-initiated butadiene polymerization

In nonpolar solvents, alkyllithium-initiated 1,3-butadiene polymerization exhibits high 1,4-selectivity, which shifts towards 1,2-selectivity upon the addition of Lewis bases. For the past 50 years, the prevailing hypothesis has suggested that Lewis bases primarily influence regioselectivity through electronic effects. However, our study reveals that steric hindrance also plays a crucial role. Using X-ray single-crystal diffraction, we analyzed the structure of the active species and proposed a new model for the chain-growth transition state. Techniques such as in situ NMR spectroscopy, isotope labeling studies, and density functional theory (DFT) calculations were employed to compare the impact of electronic and steric effects of various Lewis bases on regioselectivity. Our findings demonstrate that during 1,4-addition, the butadiene monomer is forced into close proximity with the Lewis base ligand, leading to significant steric interference and thus favoring 1,2-addition. Furthermore, we applied the concepts of "conformational restriction" to explain the enhanced 1,2-selectivity observed with ring-containing Lewis bases such as 1,2-dipiperidylethane. Building on this understanding, we have designed several highly efficient and cost-effective Lewis bases which achieves close to 100% 1,2-selectivity under mild conditions and significantly outperforms the best previously reported Lewis base, 1,2-dipiperidylethane, across a broad temperature range.

Visible light photoflow synthesis of a Cu(ii) single-chain polymer nanoparticle catalyst

We herein pioneer the visible light (λ max = 410 nm) mediated flow synthesis of catalytically active single-chain nanoparticles (SCNPs). Our design approach is based on a copolymer of poly(ethylene glycol) methyl ether methacrylate and a photocleavable 2-((((2-nitrobenzyl)oxy)carbonyl)amino)ethyl methacrylate monomer which can liberate amine groups upon visible light irradiation, allowing for single-chain collapse via the complexation of Cu(ii) ions. We initially demonstrate the successful applicability of our design approach for the batch photochemical synthesis of Cu(ii) SCNPs and transfer the concept to photoflow conditions, enabling, for the first time, the continuous production of functional SCNPs. Critically, we explore their ability to function as a photocatalyst for the cleavage of carbon-carbon single and double bonds on the examples of xanthene-9-carboxylic acid and oleic acid, demonstrating the advantageous effect SCNPs can provide over analogous small molecule catalysts.

Equilibration of linear polyethylene melts with pre-defined molecular weight distributions employing united atom Monte Carlo simulations

Possessing control over the molecular size (molecular weight/chain length/degree of polymerization) distribution of a polymeric material is extremely important in applications. This is manifested de facto by the extensive contemporary scientific literature on processes for controlling this distribution experimentally. Yet, the literature on computational techniques for achieving prescribed molecular size distributions in simulations and exploring their impact on properties is much less abundant than its experimental/technical counterpart. Here, we develop-on the basis of united atom melt simulations employing connectivity-altering Monte Carlo moves-a new Metropolis selection criterion that drives the multichain system to a prescribed but otherwise arbitrary distribution of molecular sizes. The new formulation is a generalization of that originally proposed [P. V. K. Pant and D. N. Theodorou, Macromolecules 28, 7224 (1995)], but simpler and more computationally efficient. It requires knowledge solely of the target distribution, which need not be normalized. We have implemented the new formulation on long-chain linear polyethylene melts, obtaining excellent results. The target molecular size distribution can be provided in tabulated form, allowing absolute freedom as to the types of chain size profiles that can be simulated. Distributions for which equilibration has been achieved here for linear polyethylene include a truncated most probable, a truncated Schulz-Zimm, an arbitrary one defined in tabulated form, a broad truncated Gaussian, and a bimodal Gaussian. The last two are comparable to those encountered in industrial applications. The impact of the molecular size distribution on the properties of the simulated melts, such as density, chain dimensions, and mixing thermodynamics, is explored.

Accessing Cyclobutane Polymers: Overcoming Synthetic Challenges via Efficient Continuous Flow [2 + 2] Photopolymerization

We report an improved and efficient method to prepare well-defined, structurally complex truxinate cyclobutane polymers via a thioxanthone sensitized solution state [2 + 2] photopolymerization. Monomers with varying electron density and structure polymerize in good to excellent yields to afford a library of 42 polyesters. Monomers with internal olefin separation distances of greater than 5 Å undergo polymerization via intermolecular [2 + 2] photocycloaddition readily, as opposed to the intramolecular [2 + 2] photocycloaddition observed in monomers with olefins in closer proximity. Use of a continuous flow reactor decreases reaction time, increases polymer molecular weight, and decreases dispersity compared to batch reactions. Furthermore, under continuous flow, polymerization is readily scalable beyond what is possible with batch reactions. This advancement ushers truxinate cyclobutane-based polyesters, which have been historically limited to a few examples and only research scale quantities, to the forefront of development as new materials for potential use across industry sectors.

Continuous Flow Synthesis of Functional Isocyanate-Free Poly(oxazolidone)s by Step-Growth Polymerization

Flow chemistry presents many advantages over batch processes for the fast and continuous production of polymers under more robust, safer, and easily scalable conditions. Although largely exploited for chain-growth polymerizations, it has rarely been applied to step-growth polymerizations (SGP) due to their inherent limitations. Here, we report the facile and fast preparation of an emerging class of nonisocyanate polyurethanes, i.e., CO2-based poly(oxazolidone)s, by SGP in continuous flow reactors. Importantly, we also demonstrate that functional poly(oxazolidone)s are easily prepared by telescoping a flow module where SGP occurs with reagents able to simultaneously promote two polymer derivatizations in a second module, i.e., dehydration followed by cationic thiol-ene to yield poly(N,S-acetal oxazolidone)s. The functional polymer is produced at a high rate and functionalization degree, without requiring the isolation of any intermediates. This work demonstrates the enormous potential of flow technology for the facile and fast continuous production of functional polymers by SGP.

Simultaneous Spin Coating and Ring-Opening Metathesis Polymerization for the Rapid Synthesis of Polymer Films

We report a highly controlled technique for the synthesis of polymer films atop a substrate by combining spin coating with ring-opening metathesis polymerization (ROMP), herein termed spin coating ROMP (scROMP). The scROMP approach combines polymer synthesis and deposition into one process, fabricating films of up to 36 cm2 in under 3 min with orders-of-magnitude reduction in solvent usage. This method can convert numerous norbornene-type molecules into homopolymers and random copolymers as uniform films on both porous and nonporous substrates. Film thickness can be varied from a few hundred nanometers to a few tens of micrometers based on spin speed and monomer concentration. The resulting polymers possess high MW (>100 kDa) and low polydispersity (PDI) (<1.2) values that are similar to ROMP polymers made in solution. We also devise a model to investigate the balance between convective monomer spin-off and polymer growth from the surface, which allows the determination of critical kinetic parameters for scROMP. Finally, translation of scROMP to porous supports enables the synthesis of thin film composite membranes that demonstrate the ability to dehydrate ethanol by pervaporation.

High-Throughput Synthesis, Purification, and Application of Alkyne-Functionalized Discrete Oligomers

The development of synthetic oligomers as discrete single molecular entities with accurate control over the number and nature of functional groups along the backbone has enabled a variety of new research opportunities. From fundamental studies of self-assembly in materials science to understanding efficacy and safety profiles in biology and pharmaceuticals, future directions are significantly impacted by the availability of discrete, multifunctional oligomers. However, the preparation of diverse libraries of discrete and stereospecific oligomers remains a significant challenge. We report a novel strategy for accelerating the synthesis and isolation of discrete oligomers in a high-throughput manner based on click chemistry and simplified bead-based purification. The resulting synthetic platform allows libraries of discrete polyether oligomers to be prepared and the impact of variables such as chain length, number, and nature of side chain functionalities and molecular dispersity on antibacterial behavior examined. Significantly, discrete oligomers were shown to exhibit enhanced activity with lower toxicity compared with traditional disperse samples. This work provides a practical and scalable methodology for nonexperts to prepare libraries of multifunctional discrete oligomers and demonstrates the advantages of discrete materials in biological applications.

Real-time monitoring polymerization degree of organic photovoltaic materials toward no batch-to-batch variations in device performance

Polymerization degree plays a vital role in material properties. Previous methodologies of molecular weight control generally cannot suppress or alleviate batch-to-batch variations in device performance, especially in polymer solar cells. Herein, we develop an in-situ photoluminescence system in tandem with a set of analysis and processing procedures to track and estimate the polymerization degree of organic photovoltaic materials. To support the development of this protocol, we introduce polymer acceptor PYT constructed by near-infrared Y-series small molecule acceptors via Stille polymerization, and shed light on the correlations between molecular weight, spectral parameters, and device efficiencies that enable the design of the optical setup and confirm its feasibility. The universality is verified in PYT derivatives with stereoregularity and fluoro-substitution as well as benzo[1,2-b:4,5-b']dithiophene-based polymers. Overall, our result provides a tool to tailor suitable conjugated oligomers applied to polymer solar cells and other organic electronics for industrial scalability and desired cost reduction.

A co-carrier for plasmid DNA and curcumin delivery to treat pancreatic cancer via dendritic poly(l-lysine) modified amylose

Pancreatic cancer is one of the most lethal malignancies in the world and remains one of the leading causes of cancer related death. For its treatment, a lot of investigations have dealt not only with individual chemotherapy by using polymeric carriers to deliver anticancer drugs, but also with individual gene therapy by using polymeric carriers to deliver nucleic acids such as small interfering RNA (siRNA) and plasmid DNA. However, relatively few studies have been focused on the co-delivery of gene and anticancer drug by multifunctional polymeric carriers for its synergistic therapy. In this work, a DPLL-functionalized amylose (ADP) was prepared by the click reaction between azidized amylose and propargyl focal point poly(l-lysine) dendrons, and then used to co-deliver plasmid pIRES2-EGFP-TNFα and curcumin for pancreatic cancer treatment. Due to the internal hydrophobic cavity of amylose component, ADP could load efficiently curcumin with anticancer activity and showed a sustained release behavior. Moreover, the curcumin-loaded ADP could form colloidally stable nanocomplexes with plasmid DNA in aqueous system due to the existence of cationic poly(l-lysine) dendrons and exhibited high gene transfection efficiency. The in vitro and in vivo tests confirmed the effectiveness of using ADP to co-deliver plasmid pIRES2-EGFP-TNFα and curcumin for synergistic therapy of pancreatic cancer.

Sample transformation in online separations: how chemical conversion advances analytical technology

While the advent of modern analytical technology has allowed scientists to determine the complexity of mixtures, it also spurred the demand to understand these sophisticated mixtures better. Chemical transformation can be used to provide insights into properties of complex samples such as degradation pathways or molecular heterogeneity that are otherwise unaccessible. In this article, we explore how sample transformation is exploited across different application fields to empower analytical methods. Transformation mechanisms include molecular-weight reduction, controlled degradation, and derivatization. Both offline and online transformation methods have been explored. The covered studies show that sample transformation facilitates faster reactions (e.g. several hours to minutes), reduces sample complexity, unlocks new sample dimensions (e.g. functional groups), provides correlations between multiple sample dimensions, and improves detectability. The article highlights the state-of-the-art and future prospects, focusing in particular on the characterization of protein and nucleic-acid therapeutics, nanoparticles, synthetic polymers, and small molecules.

Processability Considerations for Next-Generation Organic Photovoltaic Materials

The evolution of organic semiconductors for organic photovoltaics (OPVs) has resulted in unforeseen outcomes. This has provided substitute choices of photoactive layer materials, which effectively convert sunlight into electricity. Recently developed OPV materials have narrowed down the gaps in efficiency, stability, and cost in devices. Records now show power conversion efficiency in single-junction devices closing to 20%. Despite this, there is still a gap between the currently developed OPV materials and those that meet the requirements of practical applications, especially the solution processability issue widely concerned in the field of OPVs. Based on the general rule that structure determines properties, methodologies to enhance the processability of OPV materials are reviewed and explored from the perspective of material design and views on the further development of processable OPV materials are presented. Considering the current dilemma that the existing evaluation indicators cannot reflect the industrial processability of OPV materials, a more complete set of key performance indicators are proposed for their processability considerations. The purpose of this perspective is to raise awareness of the boundary conditions that exist in industrial OPV manufacturing and to provide guidance for academic research that aspires to contribute to technological advancements.

Controlling primary chain dispersity in network polymers: elucidating the effect of dispersity on degradation

Although dispersity has been demonstrated to be instrumental in determining many polymer properties, current synthetic strategies predominantly focus on tailoring the dispersity of linear polymers. In contrast, controlling the primary chain dispersity in network polymers is much more challenging, in part due to the complex nature of the reactions, which has limited the exploration of properties and applications. Here, a one-step method to prepare networks with precisely tuned primary chain dispersity is presented. By using an acid-switchable chain transfer agent and a degradable crosslinker in PET-RAFT polymerization, the in situ crosslinking of the propagating polymer chains was achieved in a quantitative manner. The incorporation of a degradable crosslinker, not only enables the accurate quantification of the various primary chain dispersities, post-synthesis, but also allows the investigation and comparison of their respective degradation profiles. Notably, the highest dispersity networks resulted in a 40% increase in degradation time when compared to their lower dispersity analogues, demonstrating that primary chain dispersity has a substantial impact on the network degradation rate. Our experimental findings were further supported by simulations, which emphasized the importance of higher molecular weight polymer chains, found within the high dispersity materials, in extending the lifetime of the network. This methodology presents a new and promising avenue to precisely tune primary chain dispersity within networks and demonstrates that polymer dispersity is an important parameter to consider when designing degradable materials.

Visible Light Photoiniferter Polymerization for Dispersity Control in High Molecular Weight Polymers

The synthesis of polymers with high molecular weights, controlled sequence, and tunable dispersities remains a challenge. A simple and effective visible-light controlled photoiniferter reversible addition-fragmentation chain transfer (RAFT) polymerization is reported here to realize this goal. Key to this strategy is the use of switchable RAFT agents (SRAs) to tune polymerization activities coupled with the inherent highly living nature of photoiniferter RAFT polymerization. The polymerization activities of SRAs were in situ adjusted by the addition of acid. In addition to a switchable chain-transfer coefficient, photolysis and polymerization kinetic studies revealed that neutral and protonated SRAs showed different photolysis and polymerization rates, which is unique to photoiniferter RAFT polymerization in terms of dispersity control. This strategy features no catalyst, no exogenous radical source, temporal regulation by visible light, and tunable dispersities in the unprecedented high molecular weight regime (up to 500 kg mol-1 ). Pentablock copolymers with three different dispersity combinations were also synthesized, highlighting that the highly living nature was maintained even for blocks with large dispersities. Tg was lowered for high-dispersity polymers of similar MWs due to the existence of more low-MW polymers. This strategy holds great potential for the synthesis of advanced materials with controlled molecular weight, dispersity and sequence.

Transfer Learning of Full Molecular Weight Distributions via High-Throughput Computer-Controlled Polymerization

The skew and shape of the molecular weight distribution (MWD) of polymers have a significant impact on polymer physical properties. Standard summary metrics statistically derived from the MWD only provide an incomplete picture of the polymer MWD. Machine learning (ML) methods coupled with high-throughput experimentation (HTE) could potentially allow for the prediction of the entire polymer MWD without information loss. In our work, we demonstrate a computer-controlled HTE platform that is able to run up to 8 unique variable conditions in parallel for the free radical polymerization of styrene. The segmented-flow HTE system was equipped with an inline Raman spectrometer and offline size exclusion chromatography (SEC) to obtain time-dependent conversion and MWD, respectively. Using ML forward models, we first predict monomer conversion, intrinsically learning varying polymerization kinetics that change for each experimental condition. In addition, we predict entire MWDs including the skew and shape as well as SHAP analysis to interpret the dependence on reagent concentrations and reaction time. We then used a transfer learning approach to use the data from our high-throughput flow reactor to predict batch polymerization MWDs with only three additional data points. Overall, we demonstrate that the combination of HTE and ML provides a high level of predictive accuracy in determining polymerization outcomes. Transfer learning can allow exploration outside existing parameter spaces efficiently, providing polymer chemists with the ability to target the synthesis of polymers with desired properties.

Shaping the Structure and Response of Surface-Grafted Polymer Brushes via the Molecular Weight Distribution

Breadth in the molecular weight distribution is an inherent feature of synthetic polymer systems. While in the past this was typically considered as an unavoidable consequence of polymer synthesis, multiple recent studies have shown that tailoring the molecular weight distribution can alter the properties of polymer brushes grafted to surfaces. In this Perspective, we describe recent advances in synthetic methods to control the molecular weight distribution of surface-grafted polymers and highlight studies that reveal how shaping this distribution can generate novel or enhanced functionality in these materials.

A Novel Method for Dynamic Molecular Weight Distribution Determination in Organometallic Catalyzed Olefin Polymerizations

In this study, a mathematical model for the time evolution of molecular weight distribution (MWD) was developed. This temporal model is based on the well-known Ziegler–Natta polymerization mechanism and reaction kinetics by the parametric solving of related differential equations. However, due to the generality of the reactions involved, the model can be extended to the other type of catalysts, such as metallocenes, Phillips, etc. The superiority of this model lies in providing the possibility of a more precise prediction over the active sites and kinetic parameters using a simple mathematical equation, which leads to improved reactor design in large-scale production. The model uses a function to develop a methodology for MWD calculations. In this way, the transient response is limited to the first few minutes of the reaction; however, it is important as it demonstrates the establishment of the final MWD. According to the results, almost for practical conditions with negligible transfer resistances, the time dependency of the MWD has a transient interval, depending on the kinetic constants of polymerization reactions. Increasing the time to infinity results in an increase in MW and a widening in MWD, which confirms the experimental plots well. In short, the main advantage of our proposed model over the previous ones is its ability to predict the MWD even before the completion of the polymerization reaction. The results of the present model match well with those of the well-known Schulz–Flory distribution, which only predicts the final molecular weight distribution, thus confirming that the model is reliable and generalizable.

A dual initiator approach for oxygen tolerant RAFT polymerization

Reversible-deactivation radical polymerizations are privileged approaches for the synthesis of functional and hybrid materials. A bottleneck for conducting these processes is the need to maintain oxygen free conditions. Herein we report a broadly applicable approach to "polymerize through" oxygen using the synergistic combination of two radical initiators having different rates of homolysis. The in situ monitoring of the concentrations of oxygen and monomer simultaneously provided insight into the function of the two initiators and enabled the identification of conditions to effectively remove dissolved oxygen and control polymerization under open-to-air conditions. By understanding how the surface area to volume ratio of reaction vessels influence open-to-air polymerizations, well-defined polymers were produced using acrylate, styrenic, and methacrylate monomers, which each represent an expansion of scope for the "polymerizing through" oxygen approach. Demonstration of this method in tubular reactors using continuous flow chemistry provided a more complete structure-reactivity understanding of how reaction headspace influences PTO RAFT polymerizations.

Microfluidic synthesis as a new route to produce novel functional materials

By geometrically constraining fluids into the sub-millimeter scale, microfluidics offers a physical environment largely different from the macroscopic world, as a result of the significantly enhanced surface effects. This environment is characterized by laminar flow and inertial particle behavior, short diffusion distance, and largely enhanced heat exchange. The recent two decades have witnessed the rapid advances of microfluidic technologies in various fields such as biotechnology; analytical science; and diagnostics; as well as physical, chemical, and biological research. On the other hand, one additional field is still emerging. With the advances in nanomaterial and soft matter research, there have been some reports of the advantages discovered during attempts to synthesize these materials on microfluidic chips. As the formation of nanomaterials and soft matters is sensitive to the environment where the building blocks are fed, the unique physical environment of microfluidics and the effectiveness in coupling with other force fields open up a lot of possibilities to form new products as compared to conventional bulk synthesis. This Perspective summarizes the recent progress in producing novel functional materials using microfluidics, such as generating particles with narrow and controlled size distribution, structured hybrid materials, and particles with new structures, completing reactions with a quicker rate and new reaction routes and enabling more effective and efficient control on reactions. Finally, the trend of future development in this field is also discussed.

Molecular Weight Distribution Control for Polymerization Processes Based on the Moment-Generating Function

The molecular weight distribution is an important factor that affects the properties of polymers. A control algorithm based on the moment-generating function was proposed to regulate the molecular weight distribution for polymerization processes in this work. The B-spline model was used to approximate the molecular weight distribution, and the weight state space equation of the system was identified by the subspace state space system identification method based on the paired date of B-spline weights and control inputs. Then, a new performance criterion mainly consisting of the moment-generating function was constructed to obtain the optimal control input. The effectiveness of the proposed control method was tested in a styrene polymerization process. The molecular weight distribution of the styrene polymers can be approximated by the B-spline model effectively, and it can also be regulated towards the desired one under the proposed control method.

Free-radical polymerization of 2-hydroxyethyl methacrylate (HEMA) supported by the high electric field

In macromolecular science, tunning basic polymer parameters, like molecular weight (Mn) or molecular weight distribution (dispersity, Đ), is an active research topic. Many prominent synthetic protocols concerning chemical modification of...

A general model for the ideal chain length distributions of polymers made with reversible deactivation

A general model is developed for the distribution of polymers made with reversible deactivation. The model is applied to a range of experimental systems including RAFT, cationic and ATRP.

Controlling dispersity in aqueous atom transfer radical polymerization: rapid and quantitative synthesis of one-pot block copolymers

The dispersity (Đ) of a polymer is a key parameter in material design, and variations in Đ can have a strong influence on fundamental polymer properties. Despite its importance, current polymerization strategies to control Đ operate exclusively in organic media and are limited by slow polymerization rates, moderate conversions, significant loss of initiator efficiency and lack of dispersity control in block copolymers. Here, we demonstrate a rapid and quantitative method to tailor Đ of both homo and block copolymers in aqueous atom transfer radical polymerization. By using excess ligand to regulate the dissociation of bromide ions from the copper deactivator complexes, a wide range of monomodal molecular weight distributions (1.08 < Đ < 1.60) can be obtained within 10 min while achieving very high monomer conversions (∼99%). Despite the high conversions and the broad molecular weight distributions, very high end-group fidelity is maintained as exemplified by the ability to synthesize in situ diblock copolymers with absolute control over the dispersity of either block (e.g. low Đ → high Đ, high Đ → high Đ, high Đ → low Đ). The potential of our approach is further highlighted by the synthesis of complex pentablock and decablock copolymers without any need for purification between the iterative block formation steps. Other benefits of our methodology include the possibility to control Đ without affecting the M n, the interesting mechanistic concept that sheds light onto aqueous polymerizations and the capability to operate in the presence of air.

Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis

Modern polymer science suffers from the curse of multidimensionality. The large chemical space imposed by including combinations of monomers into a statistical copolymer overwhelms polymer synthesis and characterization technology and limits the ability to systematically study structure-property relationships. To tackle this challenge in the context of 19F magnetic resonance imaging (MRI) agents, we pursued a computer-guided materials discovery approach that combines synergistic innovations in automated flow synthesis and machine learning (ML) method development. A software-controlled, continuous polymer synthesis platform was developed to enable iterative experimental-computational cycles that resulted in the synthesis of 397 unique copolymer compositions within a six-variable compositional space. The nonintuitive design criteria identified by ML, which were accomplished by exploring <0.9% of the overall compositional space, lead to the identification of >10 copolymer compositions that outperformed state-of-the-art materials.

Tuning Ligand Concentration in Cu(0)-RDRP: A Simple Approach to Control Polymer Dispersity

Cu(0)-reversible deactivation radical polymerization (RDRP) is a versatile polymerization tool, providing rapid access to well-defined polymers while utilizing mild reaction conditions and low catalyst loadings. However, thus far, this method has not been applied to tailor dispersity, a key parameter that determines the physical properties and applications of polymeric materials. Here, we report a simple to perform method, whereby Cu(0)-RDRP can systematically control polymer dispersity (Đ = 1.07-1.72), while maintaining monomodal molecular weight distributions. By varying the ligand concentration, we could effectively regulate the rates of initiation and deactivation, resulting in polymers of various dispersities. Importantly, both low and high dispersity PMA possess high end-group fidelity, as evidenced by MALDI-ToF-MS, allowing for a range of block copolymers to be prepared with different dispersity configurations. The scope of our method can also be extended to include inexpensive ligands (i.e., PMDETA), which also facilitated the polymerization of lower propagation rate constant monomers (i.e., styrene) and the in situ synthesis of block copolymers. This work significantly expands the toolbox of RDRP methods for tailoring dispersity in polymeric materials.

Precise Control of Both Dispersity and Molecular Weight Distribution Shape by Polymer Blending

The breadth and the shape of molecular weight distributions can significantly influence fundamental polymer properties that are critical for various applications. However, current approaches require the extensive synthesis of multiple polymers, are limited in dispersity precision and are typically incapable of simultaneously controlling both the dispersity and the shape of molecular weight distributions. Here we report a simplified approach, whereby on mixing two polymers (one of high Đ and one of low Đ), any intermediate dispersity value can be obtained (e.g. from 1.08 to 1.84). Unrivalled precision is achieved, with dispersity values obtained to even the nearest 0.01 (e.g. 1.37→1.38→1.39→1.40→1.41→1.42→1.43→1.44→1.45), while maintaining fairly monomodal molecular weight distributions. This approach was also employed to control the shape of molecular weight distributions and to obtain diblock copolymers with high dispersity accuracy. The straightforward nature of our methodology alongside its compatibility with a wide range of polymerisation protocols (e.g. ATRP, RAFT), significantly expands the toolbox of tailored polymeric materials and makes them accessible to all researchers.

Temporal Control over Two- and Three-State Living Coordinative Chain Transfer Polymerization for Modulating the Molecular Weight Distribution Profile of Polyolefins

A highly versatile new strategy for manipulating the molecular weight profiles, including breadth, asymmetry (skewness) and modal nature (mono-, bi-, and multimodal), of a variety of different polyolefins is reported. It involves temporal control over two- and three-state living coordinative chain transfer polymerization (LCCTP) of olefins in a programmable way. By changing the identity of the R' groups of the chain transfer agent, ER'_n , with time, different populations of chains within a bi- or multimodal polyolefin product can be selectively tagged with different end-groups. By changing the nature of the main-group metal of the CTA, programmed manipulation of the relative magnitudes of the dispersities of the different maxima that make up the final MWD profile can be achieved. This strategy can be implemented with existing LCCTP materials and conventional reactor methods to provide access to scalable and practical quantities of an unlimited array of new polyolefin materials.

Controlling Polymer Molecular Weight Distribution through a Latent Mediator Strategy with Temporal Programming

Polymer molecular weight distribution (MWD) is a key parameter of polymers. Here we present a robust method for controlling polymer MWD in controlled cationic polymerizations. A latent mediator strategy was designed and combined with temporal programming to regenerate mediators at different times during polymerization. Both the breadths and shapes of MWD curves were tuned easily by adjusting an external light source. Bimodal, trimodal, and tetramodal distributions were obtained, and the breadths could be varied from 1.06 to 2.09. Polymers with different MWDs prepared by this method had good chain end fidelity, which was demonstrated with successful chain-extension experiments. In addition, the introduction of temporal programming with a computer-controlled single chip for the light source opened an avenue for the use of artificial intelligence in polymer synthesis.

High-Throughput Routes to Biomaterials Discovery

Many existing clinical treatments are limited in their ability to completely restore decreased or lost tissue and organ function, an unenviable situation only further exacerbated by a globally aging population. As a result, the demand for new medical interventions has increased substantially over the past 20 years, with the burgeoning fields of gene therapy, tissue engineering, and regenerative medicine showing promise to offer solutions for full repair or replacement of damaged or aging tissues. Success in these fields, however, inherently relies on biomaterials that are engendered with the ability to provide the necessary biological cues mimicking native extracellular matrixes that support cell fate. Accelerating the development of such "directive" biomaterials requires a shift in current design practices toward those that enable rapid synthesis and characterization of polymeric materials and the coupling of these processes with techniques that enable similarly rapid quantification and optimization of the interactions between these new material systems and target cells and tissues. This manuscript reviews recent advances in combinatorial and high-throughput (HT) technologies applied to polymeric biomaterial synthesis, fabrication, and chemical, physical, and biological screening with targeted end-point applications in the fields of gene therapy, tissue engineering, and regenerative medicine. Limitations of, and future opportunities for, the further application of these research tools and methodologies are also discussed.

CFD analysis of asymmetric mixing at different inlet configurations of a split-and-recombine micro mixer

In the scope of the ENPRO II initiative (Energy Efficiency and Process Intensification for the Chemical Industry), a major challenge of process intensification of polymer synthesis in continuous systems is fouling. Pre-mixing is a key aspect to prevent fouling and is achieved through milli and micro structured devices (Bayer et al. 1). While equal volume flow ratios are well investigated in milli and micro systems, asymmetric mixing tasks have received less attention. This paper investigates the dependency of mixing phenomena on different flow rate ratios and modified inlet geometries. A split-and-recombine (SAR) mixer is modified by means of an injection capillary to facilitate the asymmetric mixing task. Asymmetric volume flows of ratios between 1:15 and 1:60 are investigated; the velocity ratios range from 0.5 to 2. The setup is simulated with the Computational Fluid Dynamics (CFD) tool ANSYS®;Fluent. The species equation is solved directly without the use of micro mixing models. The simulation is validated by means of a concentration field in a mixing Tee using Laser-Induced Fluorescence (LIF) with a Confocal Laser Scanning Microscope (CLSM). The three dimensional flow structures and the mixing quality are analyzed as a measure for micro mixing. The calculated concentration fields show good agreement with the experimental results and reveal the secondary flow structures and chaotic advection within the channel. The injection of the small feed stream is found to be very efficient when drawn into the secondary structures, increasing the potential of diffusive mixing. CFD simulations help to understand and locate such structures and improve the mixing performance.