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We describe a straightforward self-assembly route to nanoporous materials derived from a hexagonally-packed cylinder (HEX) morphology of a polyisoprene- block -polylactide (PI- b -PLA) diblock copolymer, by thermal cross-linking of the minority PI domains followed by selective chemical etching of the PLA matrix. The resulting mechanically stable and porous samples defy the expectation that the remaining cylinders cannot yield a robust, integrated material upon matrix removal. Scanning electron microscopy imaging reveals that this unexpected structural integrity stems from the interconnected nanofibrils therein, reflecting topological defects at the grain boundaries of the parent polydomain HEX nanostructure. Hydrodynamic radius-dependent poly(ethylene oxide) ( M n = 0.4-35 kg/mol) permeation behavior through these monoliths directly demonstrated the continuity and size selectivity of the nanoporous material. The ready accessibility of block copolymer HEX morphologies of varied chemistries suggests that this matrix etching strategy will enable the future design of functional, size-selective nanofiltration membrane materials.

Two renewable, structurally analogous monomers, isosorbide undecenoate (IU) and glucarodilactone undecenoate (GDLU) reacted with pentaerythritol tetrakis(3-mercaptopropionate) (PETT) via thiol-ene photopolymerization to form IU-PETT and GDLU-PETT thermosets. Despite their chemical similarity, uniaxial tensile testing showed that GDLU-PETT exhibited a strain-hardening behavior and is significantly tougher than IU-PETT. To understand this observation, in situ tensile testing and wide-angle X-ray scattering experiments (WAXS) were conducted. While the 2D WAXS patterns of IU-PETT displayed an isotropic halo during uniaxial deformation, they exhibited a change from an isotropic halo to a pair of scattering arcs for the GDLU-PETT samples. Density functional theory calculations further revealed that the GDLU alkyl chains are less angled than the IU alkyl chains. Based on these results, we postulate that the GDLU molecules can more easily order and align during uniaxial deformation, hence increasing intermolecular interactions between the GDLU molecules and contributing to the observed strain hardening behavior of their thermosets. This study exemplifies how molecules with subtle differences in their chemical structures can alter the structures and thermophysical properties of the resulting polymers in unpredictable ways.

Poly(ethylene terephthalate) (PET) is one of the most prevalent polymers in the world due to its combined thermal, mechanical, and gas barrier attributes. Blending PET with other polymers is an appealing strategy to further tailor properties to meet the needs of an even more diverse range of applications. Most blends with PET are macrophase-separated; only a few miscible systems have been reported. Here, the miscibility of the aromatic polyesters poly(salicylic glycolide) (PSG) and poly(salicylic methyl glycolide) (PSMG) with PET is described. Both PSG and PSMG have similar chemical structures to PET but are derived from sustainable resources and readily degradable. This study suggests that they are fully miscible with PET over the entire composition range, which is attributed to favorable interactions with PET. Negative polymer-polymer interaction parameters (χ) were determined using Flory-Huggins theory to describe melting temperature variations in the blends. In addition, the PET blends showed mechanical properties that are intermediate between the two homopolymers.

The compatibilization of polyethylene (PE) and isotactic polypropylene ( i PP) blends is of particular interest due to the challenges associated with recycling these plastics from mixed waste streams. Polyethylene- graft - i PP copolymers (PE- g - i PP) were prepared using a grafting-through strategy by copolymerization of ethylene with allyl-terminated i PP macromonomers in the presence of a hafnium pyridylamido catalyst. Graft copolymers with a variety of graft lengths ( M n = 6-28 kg/mol), graft numbers, and graft spacings were prepared. These graft copolymers were melt-blended with high-density polyethylene (HDPE) and i PP ( i PP/HDPE = 30/70 w/w), and the blend properties were evaluated by tensile testing. The blends showed enhanced tensile strength at 5 and 1 wt % loading, with higher tensile strength observed for larger block numbers and graft lengths. These results indicate that graft copolymers are efficient compatibilizers for blends of HDPE and i PP.

Cross-linked polyurethane (PU) is extensively used as thermoset foam; however, methods to directly reprocess PU foam waste derived from commercial sources into similar value materials have not been developed. We demonstrate that introducing dibutyltin dilaurate (DBTDL) into cross-linked PU foams and films enables their reprocessing at elevated temperatures via dynamic carbamate exchange reactions. Both model and commercial cross-linked PU foams were continuously reprocessed using twin-screw extrusion to remove gaseous filler and produce PU filaments or films with elastomeric or rigid thermoset mechanical properties. The properties of microcompounded model PU foam were in excellent agreement with PU film synthesized using the same monomers, indicating that this process occurs efficiently. These findings will enable the bulk reprocessing of commercial thermoset PU waste and inspire the further development of reprocessing methods for other thermosets and the compatibilization of chemically distinct cross-linked materials., Competing Interests: The authors declare the following competing financial interest(s): Northwestern University, the University of Minnesota, and Cornell University have filed a patent application related to the findings described in this manuscript., (Copyright © 2020 American Chemical Society.)

Polarity-switching photopatternable guidelines can be directly used to both orient and direct the self-assembly of block copolymers. We report the orientation and alignment of poly(styrene- block -4-trimethylsilylstyrene) (PS- b -PTMSS) with a domain periodicity, L 0 , of 44 nm on thin photopatternable grafting surface treatments (pGSTs) and cross-linkable surface treatments (pXSTs), containing acid-labile 4- tert -butoxystyrene monomer units. The surface treatment was exposed using electron beam lithography to create well-defined linear arrays of neutral and preferential regions. Directed self-assembly (DSA) of PS- b -PTMSS with much lower defectivity was observed on pXST than on pGST guidelines. The study of the effect of film thickness on photoacid diffusion by Fourier transform infrared spectroscopy and near-edge X-ray absorption fine structure spectroscopy suggested slower diffusion in thinner films, potentially enabling production of guidelines with sharper interfaces between the unexposed and exposed lines, and thus, the DSA of PS- b -PTMSS on thinner pXST guidelines resulted in better alignment control.

Plastic pollution is one of the most pressing global environmental issues we face today, in part due to the continued rise in production and use of disposable plastic products. Polyolefins and polyesters are two of the most prevalent polymers in the world accounting for ∼80% of total nonfiber plastic production. Recycling, despite being intrinsically environmentally friendly and sometimes economically viable, remains at a surprisingly low level (<9% in the U.S.) with most plastic waste ending up in landfills. One reason for this low rate of recycling stems from the challenge of recycling mixed waste streams and multicomponent plastics. In mixed waste streams, physical presorting of components prior to recycling requires significant effort, which translates to added cost. For multicomponent plastics (e.g., multilayer films such as food wrappers), the individual plastic components cannot be efficiently physically separated, and they are immiscible with poor interfacial adhesion when melt reprocessed. Thus, direct recycling of mixed plastics by melt reprocessing results in products that lack desired end-use properties. In this study, we describe the synthesis of novel poly(ethylene terephthalate)-polyethylene multiblock copolymers (PET-PE MBCPs) and evaluate their utility as adhesive tie layers in multilayer films and compatibilizer additives for melt reprocessed blends. PET and PE are targeted because they are two of the most prevalent commercial polymers in the world and are high volume waste streams. The work described here demonstrates two key findings. First, the PET-PE MBCPs serve as effective adhesive tie layers between neat PET/PE films with adhesive strength comparable to that of commercially available adhesives. Second, PET/PE (80/20 wt %) blends containing ∼0.5 wt % PET-PE MBCP were melt mixed to mimic recycling mixed plastic waste, and they were found to exhibit mechanical properties better than neat PET. Overall, this study demonstrates that PET-PE MBCPs could significantly enhance the ability to recycle PET/PE mixed waste streams by serving the role as both an adhesive promoting layer and a compatibilizer additive.

Polyesters constitute around 10% of the global plastic market with aromatic polyesters, such as poly(ethylene terephthalate) (PET), being the most prevalent because of their attractive properties. As for most commercial plastics, polyesters are primarily derived from fossil resources and are not readily degradable, which raises a number of sustainability concerns. Designing polymers with competitive properties from sustainable feedstocks that rapidly degrade under mild conditions is an attractive strategy for addressing the current plastic waste problem. Here, the detailed synthesis and characterization of degradable, high molar mass aromatic polyesters derived from salicylic acid, poly(salicylic glycolide) (PSG), and poly(salicylic methyl glycolide) (PSMG) are described. The synthesis of polymers was investigated through mechanistic experiments and complementary computational studies. The glass transition temperature ( T g ≈ 85 °C) and Young's modulus ( E ≈ 2.3 GPa) of these polyesters are comparable to those of PET. In contrast to the poor hydrolytic degradability of PET, both PSG and PSMG are readily degradable in neutral aqueous solutions (e.g., complete degradation in seawater at 50 °C in 60 days). These aromatic polyesters derived from salicylic acid have potential as future high-performance, sustainable, and degradable plastics.

Superparamagnetic nanoparticles with a high initial magnetic susceptibility χ o are of great interest in a wide variety of chemical, biomedical, electronic, and subsurface energy applications. In order to achieve the theoretically predicted increase in χ o with the cube of the magnetic diameter, new synthetic techniques are needed to control the crystal structure, particularly for magnetite nanoparticles larger than 10 nm. Aqueous magnetite dispersions (Fe 3 O 4 ) with a χ o of 3.3 (dimensionless SI units) at 1.9 vol %, over 3- to 5-fold greater than those reported previously, were produced in a one-pot synthesis at 210 °C and ambient pressure via thermal decomposition of Fe(II) acetate in triethylene glycol (TEG). The rapid nucleation and focused growth with an unusually high precursor-to-solvent molar ratio of 1:12 led to primary particles with a volume average diameter of 16 nm and low polydispersity according to TEM. The morphology was a mixture of stoichiometric and substoichiometric magnetite according to X-ray diffraction (XRD) and Mössbauer spectroscopy. The increase in χ o with the cube of magnetic diameter as well as a saturation magnetization approaching the theoretical limit may be attributed to the highly crystalline structure and very small nonmagnetic layer (∼1 nm) with disordered spin orientation on the surface.

The structure, stability, and reorganization of lamella-forming block copolymer thin film surface topography ("islands" and "holes") were studied under boundary conditions driving the formation of 0.5 L 0 thick structures at short thermal annealing times. Self-consistent field theory predicts that the presence of one perfectly neutral surface renders 0.5 L 0 topography thermodynamically stable relative to 1 L 0 thick features, in agreement with previous experimental observations. The calculated through-film structures match cross-sectional scanning electron micrographs, collectively demonstrating the pinning of edge dislocations at the neutral surface. Remarkably, near-neutral surface compositions exhibit 0.5 L 0 topography metastability upon extended thermal treatment, slowly transitioning to 1 L 0 islands or holes as evidenced by optical and atomic force microscopy. Surface restructuring is rationalized by invoking commensurability effects imposed by slightly preferential surfaces. The results described herein clarify the impact of interfacial interactions on block copolymer self-assembly and solidify an understanding of 0.5 L 0 topography, which is frequently used to determine neutral surface compositions of considerable importance to contemporary technological applications.

We study dynamical reversibility in stationary stochastic processes from an information-theoretic perspective. Extending earlier work on the reversibility of Markov chains, we focus on finitary processes with arbitrarily long conditional correlations. In particular, we examine stationary processes represented or generated by edge-emitting, finite-state hidden Markov models. Surprisingly, we find pervasive temporal asymmetries in the statistics of such stationary processes. As a consequence, the computational resources necessary to generate a process in the forward and reverse temporal directions are generally not the same. In fact, an exhaustive survey indicates that most stationary processes are irreversible. We study the ensuing relations between model topology in different representations, the process's statistical properties, and its reversibility in detail. A process's temporal asymmetry is efficiently captured using two canonical unifilar representations of the generating model, the forward-time and reverse-time ε-machines. We analyze example irreversible processes whose ε-machine representations change size under time reversal, including one which has a finite number of recurrent causal states in one direction, but an infinite number in the opposite. From the forward-time and reverse-time ε-machines, we are able to construct a symmetrized, but nonunifilar, generator of a process--the bidirectional machine. Using the bidirectional machine, we show how to directly calculate a process's fundamental information properties, many of which are otherwise only poorly approximated via process samples. The tools we introduce and the insights we offer provide a better understanding of the many facets of reversibility and irreversibility in stochastic processes.

We investigate a stationary process's crypticity--a measure of the difference between its hidden state information and its observed information--using the causal states of computational mechanics. Here, we motivate crypticity and cryptic order as physically meaningful quantities that monitor how hidden a hidden process is. This is done by recasting previous results on the convergence of block entropy and block-state entropy in a geometric setting, one that is more intuitive and that leads to a number of new results. For example, we connect crypticity to how an observer synchronizes to a process. We show that the block-causal-state entropy is a convex function of block length. We give a complete analysis of spin chains. We present a classification scheme that surveys stationary processes in terms of their possible cryptic and Markov orders. We illustrate related entropy convergence behaviors using a new form of foliated information diagram. Finally, along the way, we provide a variety of interpretations of crypticity and cryptic order to establish their naturalness and pervasiveness. This is also a first step in developing applications in spatially extended and network dynamical systems.

Appealing to several multivariate information measures--some familiar, some new here--we analyze the information embedded in discrete-valued stochastic time series. We dissect the uncertainty of a single observation to demonstrate how the measures' asymptotic behavior sheds structural and semantic light on the generating process's internal information dynamics. The measures scale with the length of time window, which captures both intensive (rates of growth) and subextensive components. We provide interpretations for the components, developing explicit relationships between them. We also identify the informational component shared between the past and the future that is not contained in a single observation. The existence of this component directly motivates the notion of a process's effective (internal) states and indicates why one must build models.

We adapt tools from information theory to analyze how an observer comes to synchronize with the hidden states of a finitary, stationary stochastic process. We show that synchronization is determined by both the process's internal organization and by an observer's model of it. We analyze these components using the convergence of state-block and block-state entropies, comparing them to the previously known convergence properties of the Shannon block entropy. Along the way we introduce a hierarchy of information quantifiers as derivatives and integrals of these entropies, which parallels a similar hierarchy introduced for block entropy. We also draw out the duality between synchronization properties and a process's controllability. These tools lead to a new classification of a process's alternative representations in terms of minimality, synchronizability, and unifilarity.

We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.

Polymeric bicontinuous microemulsions are thermodynamically stable structures typically formed by ternary blends of immiscible A and B homopolymers and a macromolecular surfactant such as an AB diblock copolymer. Investigations of these bicontinuous morphologies have largely focused on model systems in which all components have narrow molecular weight distributions. Here we probe the effects of AB diblock polydispersity in ternary blends of polystyrene (PS), polyisoprene (PI), and poly(styrene-b-isoprene) (PS-PI). Three series of blends were prepared using the same PS and PI homopolymers; two of them contain nearly monodisperse components while the third includes a polydisperse PS-PI diblock. The PS and PI homopolymers and two of the PS-PI diblocks were prepared by anionic polymerization using sec-butyllithium and have narrow molecular weight distributions. The polydisperse PS-PI diblock was prepared by anionic polymerization using the functional organolithium 3-tert-butyldimethylsilyloxy-1-propyllithium; this diblock has a polydisperse PS block (Mw/Mn = 1.57) and a nearly monodisperse PI block (Mw/Mn < 1.1). The phase behavior of the three series of blends was probed using a combination of dynamic mechanical spectroscopy, small-angle X-ray scattering, and cloud point measurements, and a bicontinuous microemulsion channel was identified in each system. These results prove that monodisperse components are not required to form bicontinuous microemulsions and highlight the utility of polydispersity as a tool to tune polymer blend phase behavior. The random-phase approximation, originally advanced by de Gennes, and self-consistent field theory are used to provide a theoretical supplement to the experimental work. These theories are able to predict the directions of the polydispersity-driven shifts in domain spacing, order-disorder transition temperatures, and the location of the microemulsion channel. Self-consistent field theory is also used in conjunction with the experimental data from a series of nearly monodisperse blends to probe the variations of chi with temperature. A single linear relation of the form chi = alpha/T + beta does not describe chi at all blend compositions. Rather, two separate relations describe chi as a function of temperature; one is obtained from data on the diblock-rich side of the bicontinuous microemulsion channel while the other is obtained from data on the homopolymer-rich side of the channel. The blend morphology, rather than the composition (homopolymer fraction), apparently dictates whether the system is in the "diblock chi" or "homopolymer chi" regime. These results reinforce the notion that a true understanding of chi still eludes the polymer science community.