A QM-AI Approach for the Acceleration of Accurate Assessments of Halogen‑π Interactions by Training Neural Networks di Marc U. Engelhardt (16642483)

Soggetti:

Data Sheet 1_Robust control of electrohydraulic soft robots.pdf di Angella Volchko (19309105)

“...The methods presented herein exploit linear system control theory as it applies to a nonlinear soft robotic system. ...”

Family of Robust and Strongly Luminescent CuI-Based Hybrid Networks Made of Ionic and Dative Bonds di Alexander V. Artem’ev (9143312)

“...The CuI-derived inorganic–organic hybrid compounds are considered as promising phosphors for the lighting industry. Herein, exploiting N-monoalkylated hexaminium salts, [R-HMTA]­X (R = Me, Et, Pr, and propargyl; X = Cl and I), as multibridging ligands, we have designed and synthesized a unique class of one-dimensional and two-dimensional hybrid CuI-materials. ...”

Data_Sheet_3_Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.zip di Mohan S. Rao (6249497)

“...The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. ...”

Data_Sheet_1_Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.CSV di Mohan S. Rao (6249497)

“...The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. ...”

Table_1_Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.docx di Mohan S. Rao (6249497)

“...The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. ...”

Data_Sheet_2_Novel Computational Approach to Predict Off-Target Interactions for Small Molecules.zip di Mohan S. Rao (6249497)

“...The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. ...”