Correction: Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor

Abstract

Correction for ‘Bayesian optimization with constraint on passed charge for multiparameter screening of electrochemical reductive carboxylation in a flow microreactor’ by Yuki Naito et al., Chem. Commun., 2022, 58, 3893–3896, https://doi.org/10.1039/D2CC00124A.

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The authors regret that some of the current efficiencies reported in Table 1 were miscalculated in the original article. These errors do not affect the results or conclusions of the article. The corrected Table 1 is as shown below.

Table 1 Bayesian optimization (BO)-assisted multiparameter screening for the electrochemical carboxylation of 1a.^a Training dataset (entries 1–5), BO with the constraints 2.0 < q < 3.0 (entries 6A–9A) and 2.0 < q < 2.1 (entries 6B–9B) are listed along with the corresponding experimental results (yields and current efficiencies). The complete dataset is shown in Table S2 in the ESI

Entry	[1a]/M	[Bu4NClO4]/M	Current density/mA cm^−2	Flow rate/mL h^−1	Electrode distance/μm	Charge passed (q)/F mol^−1	Yield of 2a^b/%	Current efficiency/%
a Reaction conditions: cathode, glassy carbon plate; anode, Pt plate; solvent, THF; concentration of CO2, saturation concentration at 1 atm (∼0.4 M, see ESI for details). b Determined by HPLC.
1	0.08	0.1	25	15	120	2.33	28	24
2	0.08	0.15	40	25	80	2.24	31	28
3	0.04	0.1	10	10	20	2.80	88	63
4	0.04	0.05	25	25	120	2.80	39	28
5	0.12	0.15	15	5	80	2.80	46	33
6A	0.049	0.1	11.1	8.9	30	2.85	90	63
7A	0.062	0.075	12.2	7.4	20	2.98	78	52
8A	0.045	0.12	10.1	9.2	30	2.73	78	57
9A	0.043	0.077	11.9	11.1	30	2.79	81	58
6B	0.04	0.084	10.6	14.6	30	2.03	85	84
7B	0.071	0.053	10.6	8.3	40	2.01	71	71
8B	0.06	0.15	11.7	10.8	20	2.02	77	76
9B	0.042	0.094	12.2	16	20	2.03	88	87

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The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers.

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