AIMC Topic: Electrons

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Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations.

Journal of chemical information and modeling
Parametrization of small organic molecules for classical molecular dynamics simulations is not trivial. The vastness of the chemical space makes approaches using building blocks challenging. The most common approach is therefore an individual paramet...

Using convolutional neural networks to estimate time-of-flight from PET detector waveforms.

Physics in medicine and biology
Although there have been impressive strides in detector development for time-of-flight positron emission tomography, most detectors still make use of simple signal processing methods to extract the time-of-flight information from the detector signals...

Utilization of a 3D printer to fabricate boluses used for electron therapy of skin lesions of the eye canthi.

Journal of applied clinical medical physics
This work describes the use of 3D printing technology to create individualized boluses for patients treated with electron beam therapy for skin lesions of the eye canthi. It aimed to demonstrate the effectiveness of 3D-printed over manually fabricate...

Automated electrophilic radiosynthesis of [¹⁸F]FBPA using a modified nucleophilic GE TRACERlab FXFDG.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
We modified a commercially available synthesis module for nucleophilic [(18)F]fluorinations (TRACERlab(TM) FXFDG, GE Healthcare) to enable the reliable synthesis of 2-[(18)F]fluoro-4-borono-L-phenylalanine ([(18)F]FBPA) via direct electrophilic subst...

Enhancing spatial resolution of (18)F positron imaging with the Timepix detector by classification of primary fired pixels using support vector machine.

Physics in medicine and biology
Position-sensitive positron cameras using silicon pixel detectors have been applied for some preclinical and intraoperative clinical applications. However, the spatial resolution of a positron camera is limited by positron multiple scattering in the ...

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

Journal of chemical theory and computation
Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationa...

Evaluating Molecular Similarity Measures: Do Similarity Measures Reflect Electronic Structure Properties?

Journal of chemical information and modeling
The rapid adoption of big data, machine learning (ML), and generative artificial intelligence (AI) in chemical discovery has heightened the importance of quantifying molecular similarity. Molecular similarity, commonly assessed as the distance betwee...

Recurrent Neural Network/Machine Learning Predictions of Reactive Channels in H + CH at E = 30 eV: A Prototype of Ion Cancer Therapy Reactions.

Journal of computational chemistry
We present a simplest-level electron nuclear dynamics/machine learning (SLEND/ML) approach to predict chemical properties in ion cancer therapy (ICT) reactions. SLEND is a time-dependent, variational, on-the-fly, and nonadiabatic method. In SLEND, nu...

NucleoFind: a deep-learning network for interpreting nucleic acid electron density.

Nucleic acids research
Nucleic acid electron density interpretation after phasing by molecular replacement or other methods remains a difficult problem for computer programs to deal with. Programs tend to rely on time-consuming and computationally exhaustive searches to re...

Deep-Learning Electron Diffractive Imaging.

Physical review letters
We report the development of deep-learning coherent electron diffractive imaging at subangstrom resolution using convolutional neural networks (CNNs) trained with only simulated data. We experimentally demonstrate this method by applying the trained ...