The synthesis of poly(lactic acid), PLA, is facile in the presence of the cyclic, organic amidine catalyst 1,8-diazabicyclo[5.4.0]undec-7-ene, DBU. Since DBU’s catalytic capability was first reported by Lohmeijer and colleagues in 2006 for ring-opening polymerizations (ROP), there have been numerous studies conducted by a variety of groups on the catalytic functioning of DBU in the ROPs of cyclic esters resulting in a large body of un-unified material from a mechanistic standpoint. This lack of clarity will hamper engineering polymers with desired characteristics from cyclic ester and lactone monomers. The work outlined in this paper seeks to propose a unified picture of the mechanisms in the DBU catalyzed ROP of lactide. In providing this unified picture of the ROP our work encompassed: (i) proposing a detailed reaction network scheme, (ii) conducting syntheses of lactide and DBU over a range of initial concentrations, and (iii) kinetic modeling to further support the proposed reaction network. As a result, our work has produced: (i) kinetic data, (ii) a consistent, viable reaction scheme verified through kinetic modeling, (iii) deduced and quantified the interplay between polymerization routes facilitated by the presence of DBU, thus demonstrating the need for detailed kinetic studies to deconstruct complex reaction networks, (iv) the first experimental evidence in support of the combination of ketene aminal-ended chains with alcohol-ended chains, and (v) analyzed the robustness of the catalyst to acid contamination.

We introduce a powerful, widely applicable approach to characterizing polymer conformational distributions, specifically the end-to-end distance distributions, P(R ee ), accessed through double electron−electron resonance (DEER) spectroscopy in conjunction with molecular dynamics (MD) simulations. The technique is demonstrated on one of the most widely used synthetic, disordered, water-soluble polymers: poly(ethylene oxide) (PEO). Despite its widespread importance, no systematic experimental characterization of PEO's R ee conformational landscape exists. The evaluation of P(R ee ) is particularly important for short polymers or (bio)polymers with sequence complexities that deviate from simple polymer physics scaling laws valid for long chains. In this study, we characterize the R ee landscape by measuring P(R ee ) for low molecular weight (MW: 0.22−2.6 kDa) dilute PEO chains. We use DEER with end-conjugated spin probes to resolve R ee populations from ∼2−9 nm and compare them with full distributions from MD. The P( R ee )'s from DEER and MD show remarkably good agreement, particularly at longer chain lengths where populations in the DEER-unresolvable range (<1.5 nm) are low. Both the P(R ee ) and the root-mean-square R ̃ee indicate that aqueous PEO is a semiflexible polymer in a good solvent, with the latter scaling linearly with molecular weight up to its persistence length (l p ∼ 0.48 nm), and rapidly transitioning to excluded volume scaling above l p . The R ̃ee scaling is quantitatively consistent with that from experimental scattering data on high MW (>10 kDa) PEO and the P(R ee )'s crossover to the theoretical distribution for an excluded volume chain.

Achieving thermodynamic faithfulness and transferability across state points is an outstanding challenge in the bottom-up coarse graining of molecular models, with many efforts focusing on augmenting the form of coarse-grained interaction potentials to improve transferability. Here, we revisit the critical role of the simulation ensemble and the possibility that even simple models can be made more predictive through a smarter choice of ensemble. We highlight the efficacy of coarse graining from ensembles where variables conjugate to the thermodynamic quantities of interest are forced to respond to applied perturbations. For example, to learn activity coefficients, it is natural to coarse grain from ensembles with spatially varying external potentials applied to one species to force local composition variations and fluctuations. We apply this strategy to coarse grain both an atomistic model of water and methanol and a binary mixture of spheres interacting via Gaussian repulsions and demonstrate near-quantitative capture of activity coefficients across the whole composition range. Furthermore, the approach is able to do so without explicitly measuring and targeting activity coefficients during the coarse graining process; activity coefficients are only computed after-the-fact to assess accuracy. We hypothesize that ensembles with applied thermodynamic potentials are more “thermodynamically informative.” We quantify this notion of informativeness using the Fisher information metric, which enables the systematic design of optimal bias potentials that promote the learning of thermodynamically faithful models. The Fisher information is related to variances of structural variables, highlighting the physical basis underlying the Fisher information’s utility in improving coarse-grained models.

Currently, there is great interest in the development of ways to achieve the benefits of radiation treatments with reduced negative effects. The present study demonstrates the utilization of radio-luminescent particles (RLPs) as a means to achieve radio-sensitization and enhancement and their ability to affect head- and neck-cancer-cell cultures (in vitro) and xenografts (in vivo). Our approach utilizes a naturally abundant radio-luminescent mineral, calcium tungstate (CaWO4), in its micro or nanoparticulate form for generating secondary UV-A light by γ ray or X-ray photons. In vitro tests demonstrate that unoptimized RLP materials (uncoated CaWO4 (CWO) microparticles (MPs) and PEG–PLA-coated CWO nanoparticles (NPs)) induce a significant enhancement of the tumor-suppressive effect of X-rays and γ rays in both radio-sensitive- and radio-resistant-cancer models; uncoated CWO MPs and PEG–PLA-coated CWO NPs demonstrate comparable radio-sensitization efficacies in vitro. Mechanistic studies reveal that concomitant CaWO4 causes increased mitotic death in radio-resistant cells treated with radiation, whereas CaWO4 sensitizes radio-sensitive cells to X-ray-induced apoptosis and necrosis. The radio-sensitization efficacy of intratumorally injected CaWO4 particles (uncoated CWO MPs and PEG–PLA-coated CWO NPs) is also evaluated in vivo in mouse head- and neck-cancer xenografts. Uncoated CWO MPs suppress tumor growth more effectively than PEG–PLA-coated CWO NPs. On the basis of theoretical considerations, an argument is proposed that uncoated CWO MPs release subtoxic levels of tungstate ions, which cause increased photoelectric-electron-emission effects. The effect of folic acid functionalization on the in vitro radio-sensitization behavior produced by PEG–PLA-coated CWO NPs is studied. Surface folic acid results in a significant improvement in the radio-sensitization efficiency of CaWO4.

Polymer formulations possessing mesostructures or phase coexistence are challenging to simulate using atomistic particle-explicit approaches due to the disparate time and length scales, while the predictive capability of field-based simulations is hampered by the need to specify interactions at a coarser scale (e.g., χ-parameters). To overcome the weaknesses of both, we introduce a bottom-up coarse-graining methodology that leverages all-atom molecular dynamics to molecularly inform coarser field-theoretic models. Specifically, we use relative-entropy coarse-graining to parametrize particle models that are directly and analytically transformable into statistical field theories. We demonstrate the predictive capability of this approach by reproducing experimental aqueous poly­(ethylene oxide) (PEO) cloud-point curves with no parameters fit to experimental data. This synergistic approach to multiscale polymer simulations opens the door to de novo exploration of phase behavior across a wide variety of polymer solutions and melt formulations.