Kinetic Monte Carlo (KMC) has become
a well-established technique
for simulating the kinetics of free radical polymerization, both to
generate polymer molecular weight distributions and, more recently,
to track the explicit monomer sequence in every chain. However, KMC
simulations require a minimal number of molecules in order to accurately
describe monomer conversion and macromolecular quantities, which can
render them computationally prohibitive. In this work, we propose
a novel approach for accelerating KMC simulations through scaling
relationships that allow the number of molecules simulated to be reduced.
Using the concept of the minimal number of molecules and an explicit
expression we derived for copolymerization, we propose a factor that
is used to scale the reaction rate constants which results in an acceleration
of KMC simulations by a factor of ∼100. Furthermore, we demonstrate
the limits of this scaling approach, revealing the absolute lower
bound for the number of molecules used in KMC simulations of free
radical polymerization and the associated population size of dead
chains formed. We illustrate this approach using examples of acrylate
copolymerization, but this approach is sufficiently general that it
can be applied to a wide variety of free radical polymerization systems
and even other free radical chemistries.
A novel spectroscopic approach, correlated surface-enhanced Raman scattering (SERS) and fluorescence microscopy, is used to identify organic materials in two 18th century oil paintings. The vibrational fingerprint of analyte molecules is revealed using SERS, and corresponding fluorescence measurements provide a probe of local environment as well as an inherent capability to verify material identification. Correlated SERS and fluorescence measurements are performed directly on single pigment particles obtained from historic oil paintings with Ag colloids as the enhancing substrate. We demonstrate the first extractionless nonhydrolysis SERS study of oil paint as well as the potential of correlated SERS and fluorescence microscopy studies for the simultaneous identification of organic colorants and binding media in historic oil paintings.
Surface-enhanced Raman scattering (SERS) spectroscopy is increasingly applied to the identification of organic colorants in cultural heritage objects because vibrational fingerprints can be measured from microscopic samples. However, the development of SERS into a reliable, broad-spectrum method for art analysis requires the study of a wide variety of organic and inorganic colorants as well as colorant mixtures in paint. Here, we demonstrate reliable protocols for SERS-based identification of insoluble indigo, Prussian blue (PB), and mixtures thereof in aged painted surfaces. The use of simple salts and acids for sample pretreatment is evaluated. High-quality SERS spectra of PB and indigo are elucidated upon sample pretreatment with H(2)SO(4). In several cases, SERS spectra of the colorants could not be obtained without sample pretreatment. We demonstrate the use of H(2)SO(4) to solubilize PB as well as perform an in situ conversion of insoluble indigo to soluble indigo carmine (IC) on indigo, indigo oil paint, and actual samples from historic painted surfaces. A microscopic H(2)SO(4)-treated sample from the Portrait of Evelyn Byrd produced a SERS spectrum that is consistent with a mixture of PB and IC. To our knowledge, this work represents the first SERS spectrum of indigo in oil paint and the first simultaneous detection of a mixture of blue organic and inorganic colorants in a single art sample using SERS.
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