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Vapor phase infiltration (VPI) is a post-polymerization modification technique that infuses inorganics into polymers to create organic–inorganic hybrid materials with new properties. Much is yet to be understood about the chemical kinetics underlying the VPI process. The aim of this study is to create a greater understanding of the process kinetics that govern the infiltration of trimethyl aluminum (TMA) and TiCl 4 into PMMA to form inorganic-PMMA hybrid materials. To gain insight, this paper initially examines the predicted results for the spatiotemporal concentrations of inorganics computed from a recently posited reaction–diffusion model for VPI. This model provides insight on how the Damköhler number (reaction versus diffusion rates) and non-Fickian diffusional processes (hindering) that result from the material transforming from a polymer to a hybrid can affect the evolution of inorganic concentration depth profiles with time. Subsequently, experimental XPS depth profiles are collected for TMA and TiCl 4 infiltrated PMMA films at 90 °C and 135 °C. The functional behavior of these depth profiles at varying infiltration times are qualitatively compared to various computed predictions and conclusions are drawn about the mechanisms of each of these processes. TMA infiltration into PMMA appears to transition from a diffusion-limited process at low temperatures (90 °C) to a reaction-limited process at high temperatures (135 °C) for the film thicknesses investigated here (200 nm). While TMA appears to fully infiltrate these 200 nm PMMA films within a few hours, TiCl 4 infiltration into PMMA is considerably slower, with full saturation not occurring even after 2 days of precursor exposure. Infiltration at 90 °C is so slow that no clear conclusions about mechanism can be drawn; however, at 135 °C, the TiCl 4 infiltration into PMMA is clearly a reaction-limited process, with TiCl 4 permeating the entire thickness (at low concentrations) within only a few minutes, but inorganic loading continuously increasing in a uniform manner over a course of 2 days. Near-surface deviations from the uniform-loading expected for a reaction-limited process also suggest that diffusional hindering is high for TiCl 4 infiltration into PMMA. These results demonstrate a new, ex situ analysis approach for investigating the rate-limiting process mechanisms for vapor phase infiltration. 

In this work, the vapor-phase infiltration (VPI) of polyethylene terephthalate (PET) fabrics with trimethylaluminum (TMA) and coreaction with water vapor is explored as a function of limiting TMA reagent conditions versus excess TMA reagent conditions at two infiltration temperatures. TMA is found to sorb rapidly into PET fibers, with a significant pressure drop occurring within seconds of TMA exposure. When large quantities of polymer are placed within the chamber, minimal residual precursor remains at the end of the pressure drop. This rapid and complete sorption facilitates the control of inorganic loading by purposely delivering a limited quantity of the TMA reagent. The inorganic loading for this system scales linearly with a Precursor:C=O molar ratio of up to 0.35 at 140 °C and 0.5 at 80 °C. After this point, inorganic loading is constant irrespective of the amount of additional TMA reagent supplied. The SEM analysis of pyrolyzed hybrids indicates that this is likely due to the formation of an impermeable layer to subsequent infiltration as the core of the fibers remains uninfiltrated. The Precursor:C=O molar ratio in the subsaturation regime is found to tune the hybrid fabric morphology and material properties such as the optical properties of the fabric. Overall, this work demonstrates how a reagent-limited processing route can control the inorganic loading in VPI synthesized hybrid materials in a simpler manner than trying to control kinetics-driven methods. 

Poly(3,4-ethylene dioxythiophene) (PEDOT) has a high theoretical charge storage capacity, making it of interest for electrochemical applications including energy storage and water desalination. Nanoscale thin films of PEDOT are particularly attractive for these applications to enable faster charging. Recent work has demonstrated that nanoscale thin films of PEDOT can be formed using sequential gas-phase exposures via oxidative molecular layer deposition, or oMLD, which provides advantages in conformality and uniformity on high aspect ratio substrates over other deposition techniques. But to date, the electrochemical properties of these oMLD PEDOT thin films have not been well-characterized. In this work, we examine the electrochemical properties of 5–100 nm thick PEDOT films formed using 20–175 oMLD deposition cycles. We find that film thickness of oMLD PEDOT films affects the orientation of ordered domains leading to a substantial change in charge storage capacity. Interestingly, we observe a minimum in charge storage capacity for an oMLD PEDOT film thickness of ∼30 nm (60 oMLD cycles at 150 °C), coinciding with the highest degree of face-on oriented PEDOT domains as measured using grazing incidence wide angle X-ray scattering (GIWAXS). Thinner and thicker oMLD PEDOT films exhibit higher fractions of oblique (off-angle) orientations and corresponding increases in charge capacity of up to 120 mA h g −1 . Electrochemical measurements suggest that higher charge capacity in films with mixed domain orientation arise from the facile transport of ions from the liquid electrolyte into the PEDOT layer. Greater exposure of the electrolyte to PEDOT domain edges is posited to facilitate faster ion transport in these mixed domain films. These insights will inform future design of PEDOT coated high-aspect ratio structures for electrochemical energy storage and water treatment. 

Motivated by the parameter identification problem of a reaction-diffusion transport model in a vapor phase infiltration processes, we propose a Bayesian optimization procedure for solving the inverse problem that aims to find an input setting that achieves a desired functional output. The proposed algorithm improves over the standard single-objective Bayesian optimization by (i) utilizing the generalized chi-square distribution as a more appropriate predictive distribution for the squared distance objective function in the inverse problems, and (ii) applying functional principal component analysis to reduce the dimensionality of the functional response data, which allows for efficient approximation of the predictive distribution and the subsequent computation of the expected improvement acquisition function.