A method to find optimum synthetic conditions was devised by combining a data-driven empirical model with a traditional mechanistic model. In this method, an experimental parameter space was empirically obtained by Design-of-Experiments optimizations with machine-learning supplements and was strategically expanded by examination of the mechanistic model of the reaction paths. An extra tier grown on the original 3×3×3 parameter space succeeded in allocating an optimum reaction condition in the expanded 3×3×4 parameter space. The method was specifically devised for the synthesis of a macrocycle, [n]cyclo-meta-phenylenes ([n]CMP), and the largest congener with n=12 was synthesized and fully characterized for the first time. Crystallographic and photophysical analyses revealed favorable features of [12]CMP for the material applications.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/asia.202201141 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Tensor neural networks for high-dimensional Fokker-Planck equations.
Neural Netw
January 2025
Division of Applied Mathematics, Brown University, Providence, RI 02912, USA; Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, Richland, WA, United States. Electronic address:
We solve high-dimensional steady-state Fokker-Planck equations on the whole space by applying tensor neural networks. The tensor networks are a linear combination of tensor products of one-dimensional feedforward networks or a linear combination of several selected radial basis functions. The use of tensor feedforward networks allows us to efficiently exploit auto-differentiation (in physical variables) in major Python packages while using radial basis functions can fully avoid auto-differentiation, which is rather expensive in high dimensions.
View Article and Find Full Text PDFStructural transitions of ionic microgel solutions driven by circularly polarized electric fields.
Soft Matter
January 2025
Faculty of Physics, University of Vienna, Boltzmanngasse 5, 1090 Vienna, Austria.
In this work, a theoretical approach is developed to investigate the structural properties of ionic microgels induced by a circularly polarized (CP) electric field. Following a similar study on chain formation in the presence of linearly polarized fields [T. Colla , , 2018, , 4321-4337], we propose an effective potential between microgels which incorporates the field-induced interactions a static, time averaged polarizing charge at the particle surface.
View Article and Find Full Text PDFOrientation selectivity properties for the affine Gaussian derivative and the affine Gabor models for visual receptive fields.
J Comput Neurosci
January 2025
Computational Brain Science Lab, Division of Computational Science and Technology, KTH Royal Institute of Technology, SE-100 44, Stockholm, Sweden.
This paper presents an in-depth theoretical analysis of the orientation selectivity properties of simple cells and complex cells, that can be well modelled by the generalized Gaussian derivative model for visual receptive fields, with the purely spatial component of the receptive fields determined by oriented affine Gaussian derivatives for different orders of spatial differentiation. A detailed mathematical analysis is presented for the three different cases of either: (i) purely spatial receptive fields, (ii) space-time separable spatio-temporal receptive fields and (iii) velocity-adapted spatio-temporal receptive fields. Closed-form theoretical expressions for the orientation selectivity curves for idealized models of simple and complex cells are derived for all these main cases, and it is shown that the orientation selectivity of the receptive fields becomes more narrow, as a scale parameter ratio , defined as the ratio between the scale parameters in the directions perpendicular to vs.
View Article and Find Full Text PDFCrystallography of the litharge to massicot phase transformation from neutron powder diffraction data.
Acta Crystallogr B Struct Sci Cryst Eng Mater
February 2025
CSIRO Division of Mineral Products, Port Melbourne, Victoria, Australia.
The crystallographic phase change from tetragonal litharge (α-PbO; P4/nmm) to orthorhombic massicot (β-PbO; Pbcm) has been studied by full-matrix Rietveld analysis of high-temperature neutron powder diffraction data collected in equal steps from ambient temperature up to 925 K and back down to 350 K. The phase transformation takes place between 850 and 925 K, with the coexisting phases having equal abundance by weight at 885 K. The product massicot remains metastable on cooling to near ambient temperature.
View Article and Find Full Text PDFRadiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis.
Med Phys
January 2025
Deparment of Radiation Oncology, Duke University, Durham, North Carolina, USA.
Background: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but an adverse effect, radionecrosis, complicates post-SRS management. Differentiating radionecrosis from tumor recurrence non-invasively remains a major clinical challenge, as conventional imaging techniques often necessitate surgical biopsy for accurate diagnosis. Machine learning and deep learning models have shown potential in distinguishing radionecrosis from tumor recurrence.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!