Exploring the Limits of Intramolecular London Dispersion Stabilization with Bulky Dispersion Energy Donors in Alkane Solution.

We present an experimental study of a cyclooctatetraene-based molecular balance disubstituted with increasingly bulky tert-butyl (tBu), adamantyl (Ad), and diamantyl (Dia) substituents in the 1,4-/1,6-positions for which we determined the valence-bond shift equilibrium in n-hexane (hex), n-octane (oct), and n-dodecane (dod). Computations including implicit and explicit solvation support our temperature-dependent NMR equilibrium measurements indicating that the more sterically crowded 1,6-isomer is always favored, irrespective of solvent, and that the free energy is quite insensitive to substituent size.

Gauging the Steric Effects of Silyl Groups with a Molecular Balance.

We present an experimental and computational study of a cyclooctatetraene (COT)-based molecular balance disubstituted with commonly used silyl groups. Such groups often serve as protecting groups and are typically considered innocent bystanders. Our motivation here is to determine the actual steric effects of such groups by employing a molecular balance. While in the unfolded 1,4-valence isomer the silyl groups are far apart (dσ-σ ≥ 5.15 Å), the folded 1,6-isomer is affected greatly by noncovalent interactions due to close σ-σ contacts (dσ-σ ≤ 2.58 Å). In order to investigate the thermodynamic equilibrium between the 1,6- and 1,4-valence isomers, we employed temperature-dependent nuclear magnetic resonance measurements. Additionally, we assessed the nature of attractive and repulsive interactions in 1,6-disilyl-COT derivatives via a combination of local energy decomposition analysis (LED) and symmetry-adapted perturbation theory (SAPT) at the DLPNO-CCSD(T)/def2-TZVP and sSAPT0/aug-cc-pVDZ levels of theory. We identified London dispersion interactions as the main contributor to the molecular stability of the folded states, whereas Pauli exchange repulsion and a resulting internal strain favor the unfolded diastereomer.

Hexaphenylditetrels - When Longer Bonds Provide Higher Stability.

We present a computational analysis of hexaphenylethane derivatives with heavier tetrels comprising the central bond. In stark contrast to parent hexaphenylethane, the heavier tetrel derivatives can readily be prepared. In order to determine the origin of their apparent thermodynamic stability against dissociation as compared to the carbon case, we employed local energy decomposition analysis (LED) and symmetry-adapted perturbation theory (SAPT) at the DLPNO-CCSD(T)/def2-TZVP and sSAPT0/def2-TZVP levels of theory. We identified London dispersion (LD) interactions as the decisive factor for the molecular stability of heavier tetrel derivatives. This stability is made possible owing to the longer (than C-C) central bonds that move the phenyl groups out of the heavily repulsive regime so they can optimally benefit from LD interactions.

Intramolecular London Dispersion Interactions Do Not Cancel in Solution.

We present a comprehensive experimental study of a di-t-butyl-substituted cyclooctatetraene-based molecular balance to measure the effect of 16 different solvents on the equilibrium of folded versus unfolded isomers. In the folded 1,6-isomer, the two t-butyl groups are in close proximity (H···H distance ≈ 2.5 Å), but they are far apart in the unfolded 1,4-isomer (H···H distance ≈ 7 Å). We determined the relative strengths of these noncovalent intramolecular σ-σ interactions via temperature-dependent nuclear magnetic resonance measurements. The origins of the interactions were elucidated with energy decomposition analysis at the density functional and ab initio levels of theory, pinpointing the predominance of London dispersion interactions enthalpically favoring the folded state in any solvent measured.

Alcohol cross-coupling for the kinetic resolution of diols via oxidative esterification.

We present an organocatalytic C-O-bond cross-coupling strategy to kinetically resolve racemic diols with aromatic and aliphatic alcohols, yielding enantioenriched esters. This one-pot protocol utilizes an oligopeptide multicatalyst, m-CPBA as the oxidant, and N,N'-diisopropylcarbodiimide as the activating agent. Racemic acyclic diols as well as trans-cycloalkane-1,2-diols were kinetically resolved, achieving high selectivities and good yields for the products and recovered diols.

Range verification of passively scattered proton beams based on prompt gamma time patterns.

We propose a proton range verification technique for passive scattering proton therapy systems where spread out Bragg peak (SOBP) fields are produced with rotating range modulator wheels. The technique is based on the correlation of time patterns of the prompt gamma ray emission with the range of protons delivering the SOBP. The main feature of the technique is the ability to verify the proton range with a single point of measurement and a simple detector configuration. We performed four-dimensional (time-dependent) Monte Carlo simulations using TOPAS to show the validity and accuracy of the technique. First, we validated the hadronic models used in TOPAS by comparing simulations and prompt gamma spectrometry measurements published in the literature. Second, prompt gamma simulations for proton range verification were performed for the case of a water phantom and a prostate cancer patient. In the water phantom, the proton range was determined with 2 mm accuracy with a full ring detector configuration for a dose of ~2.5 cGy. For the prostate cancer patient, 4 mm accuracy on range determination was achieved for a dose of ~15 cGy. The results presented in this paper are encouraging in view of a potential clinical application of the technique.

Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy.

PURPOSE: To present the implementation and validation of a geometrical based variance reduction technique for the calculation of phase space data for proton therapy dose calculation. METHODS: The treatment heads at the Francis H Burr Proton Therapy Center were modeled with a new Monte Carlo tool (TOPAS based on Geant4). For variance reduction purposes, two particle-splitting planes were implemented. First, the particles were split upstream of the second scatterer or at the second ionization chamber. Then, particles reaching another plane immediately upstream of the field specific aperture were split again. In each case, particles were split by a factor of 8. At the second ionization chamber and at the latter plane, the cylindrical symmetry of the proton beam was exploited to position the split particles at randomly spaced locations rotated around the beam axis. Phase space data in IAEA format were recorded at the treatment head exit and the computational efficiency was calculated. Depth-dose curves and beam profiles were analyzed. Dose distributions were compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. In addition, dose in two patients was simulated with and without particle splitting to compare the efficiency and accuracy of the technique. RESULTS: A normalized computational efficiency gain of a factor of 10-20.3 was reached for phase space calculations for the different treatment head options simulated. Depth-dose curves and beam profiles were in reasonable agreement with the simulation done without splitting: within 1% for depth-dose with an average difference of (0.2 ± 0.4)%, 1 standard deviation, and a 0.3% statistical uncertainty of the simulations in the high dose region; 1.6% for planar fluence with an average difference of (0.4 ± 0.5)% and a statistical uncertainty of 0.3% in the high fluence region. The percentage differences between dose distributions in water for simulations done with and without particle splitting were within the accepted clinical tolerance of 2%, with a 0.4% statistical uncertainty. For the two patient geometries considered, head and prostate, the efficiency gain was 20.9 and 14.7, respectively, with the percentages of voxels with gamma indices lower than unity 98.9% and 99.7%, respectively, using 2% and 2 mm criteria. CONCLUSIONS: The authors have implemented an efficient variance reduction technique with significant speed improvements for proton Monte Carlo simulations. The method can be transferred to other codes and other treatment heads.

GPU-based fast Monte Carlo dose calculation for proton therapy.

Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6-22 s to simulate 10 million source protons to achieve ∼1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.