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- Mdluli, V. et al. High-throughput Synthesis and Screening of Iridium(III) Photocatalysts for the Fast and Chemoselective Dehalogenation of Aryl Bromides. ACS Catalysis 10, 6977–6987 (2020). doi: 10.1021/acscatal.0c02247
- Coley, C. W. et al. A graph-convolutional neural network model for the prediction of chemical reactivity. Chemical Science 10, 370–377 (2019). doi: 10.1039/C8SC04228D
- Kutchukian, P. S. et al. Chemistry informer libraries: a chemoinformatics enabled approach to evaluate and advance synthetic methods. Chem. Sci. 7, 2604–2613 (2016). doi: 10.1039/c5sc04751j
- Buitrago Santanilla, A. et al. Nanomole-scale high-throughput chemistry for the synthesis of complex molecules. Science 347, 49–53 (2014). doi: 10.1126/science.1259203
- Perera, D. et al. A platform for automated nanomole-scale reaction screening and micromole-scale synthesis in flow. Science 359, 429–434 (2018). doi: 10.1126/science.aap9112
- Ahneman, D. T., Estrada, J. G., Lin, S., Dreher, S. D. & Doyle, A. G. Predicting reaction performance in C–N cross-coupling using machine learning. Science 360, 186–190 (2018). doi: 10.1126/science.aar5169
- Lowe, D. Chemical reactions from US patents (1976-Sep2016). (2017). doi: 10.6084/m9.figshare.5104873.v1
- ord_dataset-026684a62f91469db49c7767d16c39fb
- ord_dataset-02a54e4276634c4bb041190cd571231e
- ord_dataset-037d306d1fab4baeb9d6cd2bc74036fe
- ord_dataset-04c32a8cbc1b4538808c959d06ad0f18
- ord_dataset-0b603eaa855e4333bd323b102c67d74d
- ord_dataset-0e0d2e7177c54e0784a9b3be8e5826df
- ord_dataset-0ffab74143c1448e82514a9aa7add211
- ord_dataset-1b3d2b114de1429e9b70c3b1c16c9263
- ord_dataset-1d488c5b08dc4e89af99b354a7cccfd6
- ord_dataset-1e9e313f53dc41cb87a997202eb11f5e
- ord_dataset-26b48b4500264ea8b727223648e1cd02
- ord_dataset-353666fa8d90431b8c5bf5bee48c651e
- ord_dataset-3895ae1a26c54070863df57dbb433ebf
- ord_dataset-44b055ac982744f6baf98a65f2345902
- ord_dataset-4e466977eb464bb291fb276e42f2a78a
- ord_dataset-5136b2f7201841af83eb6757b7ec2009
- ord_dataset-5ba1da11397e4b30bfe8a36fb8096251
- ord_dataset-5d7549b92eb94e1287c455cf3a228d5b
- ord_dataset-6742d05ed8dd456ea92b7dfb8f63b91b
- ord_dataset-682d4c94ea604ce0b055eb55f6477904
- ord_dataset-683505b5a9bd4dc593f77c85687acf51
- ord_dataset-702e59c58c5f42f2836972fe5bb69669
- ord_dataset-7132516c8cb6483283df56a78b8743c0
- ord_dataset-7740e8852f744ac3baabb50556fc163d
- ord_dataset-83bfd1dac1b94c9eaa65b314baeb37d0
- ord_dataset-84a3818d08e94ba2bd2fa91be2954cd1
- ord_dataset-8bd80d2f3a754d4fa983fca1f895c39c
- ord_dataset-99677e107dad409997a2f362e07ec5ac
- ord_dataset-a3fa129955b045068520f7d018f37cc5
- ord_dataset-b2fba5174a374ce0a1d3598617974df1
- ord_dataset-b820e2b6e1474168ae2bfff5914f96ef
- ord_dataset-c19808d436894009b2929b3bf2a972df
- ord_dataset-ca5a32b5d663435e98c50c68d5ddf73f
- ord_dataset-cda008a678f14e8591cc845a37e85fed
- ord_dataset-d19aedb0dfd947f1933c0262803960d6
- ord_dataset-d9b6cc4de43c4597b14030ffd44791bc
- ord_dataset-df21fa35f2d54662b00b89e12450c75e
- ord_dataset-e2103f90b283456b82024392b65719f5
- ord_dataset-f400f3024cb541b6884630bbe6e9dace
- ord_dataset-f6e510ee6abe48bb9f9ddd9a7153160c
- ord_dataset-fa5a7d9322b445ab8e1efb1dfda208f2