Determining Initiator Efficiency in Radical Polymerization by Electrospray-Ionization Mass Spectrometry: Determining Initiator Efficiency in Radical Polymerization …

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.

Dose-response of Fricke- and PAGAT-dosimetry gels in kilovoltage and megavoltage photon beams: Impact of LET on sensitivity

PURPOSE

Dosimetry of ionizing radiation quantifies the energy deposited by an incident beam to the medium. This study presents the relative response of two types of gel dosimeters describing their differences by estimating radiation chemical yields produced in water radiolysis.

METHODS

Two types of gel dosimeter were used, namely an acid ferrous ion solution infused with xylenol orange known as Fricke gel and a polymer gel based on acrylamide and N,N'-methylenebis(acrylamide) known as PAGAT. Samples were irradiated using two photon beam energies, one from a conventional X-ray tube operated at 44 kV and the other one from a LINAC operated at 6 MV. The dosimeters were analyzed by optical absorbance and magnetic resonance imaging. Additionally, the linear energy transfer of each beam was calculated using Monte Carlo simulations for further estimation of the radiation chemical yields produced during water radiolysis.

RESULTS

Obtained results for both gel dosimeters indicate that their response at 44 kV and 6 MV are different, regardless of the read-out technique. On average, the sensitivity at 44 kV was found to be 65 % of the response at 6 MV. The calculated radiation chemical yields are in agreement with the observed experimental results.

CONCLUSIONS

The main reason for the difference in the response of the dosimeters may be related to the linear energy transfer of each photon beam, which varies the production of primary chemical species during water radiolysis.

Tandem mass spectrometry of poly(ethylene imine)s by electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI)

In this contribution, linear poly(ethylene imine) (PEI) polymers, which are of importance in gene delivery, are investigated in detail by using electrospray ionization-quadrupole-time of flight (ESI-Q-TOF) and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry (MS). The analyzed PEIs with different end groups were synthesized using the polymerization of substituted 2-oxazoline via a living cationic ring-opening polymerization (CROP) and a subsequent hydrolysis under acidic conditions. The main goal of this study was to identify linear PEI polymers in a detailed way to gain information about their fragmentation pathways. For this purpose, a detailed characterization of three different linear PEIs was performed by using ESI-Q-TOF and MALDI-TOF MS in combination with collision-induced dissociation (CID) experiments. In ESI-MS as well as MALDI-MS analysis, the obtained spectra of PEIs resulted in fitting mass distributions for the investigated PEIs. In the tandem MS analysis, a 1,2-hydride shift with a charge-remote rearrangement via a four-membered cyclic transition state, as well as charge-induced fragmentation reactions, was proposed as the main fragmentation mechanisms according to the obtained fragmentation products from the protonated parent peaks. In addition, heterolytic and homolytic cleavages were proposed as alternative fragmentation pathways. Moreover, a 1,4-hydrogen elimination was proposed to explain different fragmentation products obtained from the sodiated parent peaks.