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Abstract Aryl fluorosulfates of varying complexities have been used in amination reactions in water using a new Pd oxidative addition complex (OAC‐1) developed specifically to match the needs of the fine chemicals industry, not only in terms of functional group tolerance, but also reflecting time considerations associated with these important C−N couplings. Also especially noteworthy is that they replace both PFAS‐related triflates and nonaflates, which are today out of favor due to recent government regulations. The new complex based on the BippyPhos ligand is used at low loadings and under aqueous micellar conditions. Moreover, it is easily prepared and stable to long term storage. DFT calculations on the OAC precatalyst compare well with the X‐ray structure of the crystals with π‐complexation to the aromatic system of the ligand and also confirm the NMR data showing a mixture of conformers in solution that differ from the X‐ray structure in rotation of the phenyl andt‐butyl ligand substituents. An extensive variety of coupling partners, including pharmaceutically relevant APIs, readily participate under mild and environmentally responsible reaction conditions.
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A database framework for rapid screening of structure-function relationships in PFAS chemistry
Abstract This paper describes a database framework that enables one to rapidly explore systematics in structure-function relationships associated with new and emerging PFAS chemistries. The data framework maps high dimensional information associated with the SMILES approach of encoding molecular structure with functionality data including bioactivity and physicochemical property. This ‘PFAS-Map’ is a 3-dimensional unsupervised visualization tool that can automatically classify new PFAS chemistries based on current PFAS classification criteria. We provide examples on how the PFAS-Map can be utilized, including the prediction and estimation of yet unmeasured fundamental physical properties of PFAS chemistries, uncovering hierarchical characteristics in existing classification schemes, and the fusion of data from diverse sources.
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- Award ID(s):
- 1640867
- PAR ID:
- 10360771
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 8
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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