Adaptive Optimization of Chemical Reactions with Minimal Experimental Information

Optimizing reaction conditions depends on expert chemistry knowledge and laborious exploration of reaction parameters. To automate this task and augment chemical intuition, we here report a computational tool to navigate search spaces. Our approach (LabMate.ML) integrates random sampling of 0.03%–0.04% of all search space as input data with an interpretable, adaptive machine-learning algorithm. LabMate.ML can optimize many real-valued and categorical reaction parameters simultaneously, with minimal computational resources and time. In nine prospective proof-of-concept studies pursuing distinctive objectives, we demonstrate how LabMate.ML can identify optimal goal-oriented conditions for several different chemistries and substrates. Double-blind competitions and the conducted expert surveys reveal that its performance is competitive with that of human experts. LabMate.ML does not require specialized hardware, affords quantitative and interpretable reactivity insights, and autonomously formalizes chemical intuition, thereby providing an innovative framework for informed, automated experiment selection toward the democratization of synthetic chemistry.D.R. is a Swiss National Science Foundation Fellow (grant nos. P2EZP3_168827 and P300P2_177833). E.A.H. is supported by the Herchel Smith Fellowship awarded by Williams College. G.J.L.B. is a Royal Society URF (URF\R\180019). T.R. is an Investigador Auxiliar supported by FCT Portugal (CEECIND/00887/2017). T.R. acknowledges the H2020 (TWINN-2017 ACORN, grant no. 807281), FCT/FEDER (02/SAICT/2017, grant no. 28333). D.R. acknowledges the MIT-IBM Watson AI Lab and the MIT SenseTime coalition for funding. The authors are extremely grateful to several colleagues for suggesting Ugi reaction conditions, and to Prof. R. Langer and Prof. G. Traverso, who provided invaluable comments on the research and manuscript. The authors are indebted to Prof. R. Moreira for access to the CEM microwave reactor; Dr. F. Corzana for technical assistance with HRMS; and the 13 graduate students, 17 postdoctoral researchers, and eight principal investigators across Austria, Denmark, Portugal, Spain, the United Kingdom, and the United States who took part in the survey. We thank R. Rodrigues for help in producing Figure 1. The survey was approved by the iMM and MIT (COUHES protocol 1809514426). The authors also thank the four anonymous reviewers for their most insightful comments.info:eu-repo/semantics/publishedVersio

On the verge of Umdeutung in Minnesota: Van Vleck and the correspondence principle (Part One)

In October 1924, the Physical Review, a relatively minor journal at the time, published a remarkable two-part paper by John H. Van Vleck, working in virtual isolation at the University of Minnesota. Van Vleck combined advanced techniques of classical mechanics with Bohr's correspondence principle and Einstein's quantum theory of radiation to find quantum analogues of classical expressions for the emission, absorption, and dispersion of radiation. For modern readers Van Vleck's paper is much easier to follow than the famous paper by Kramers and Heisenberg on dispersion theory, which covers similar terrain and is widely credited to have led directly to Heisenberg's "Umdeutung" paper. This makes Van Vleck's paper extremely valuable for the reconstruction of the genesis of matrix mechanics. It also makes it tempting to ask why Van Vleck did not take the next step and develop matrix mechanics himself.Comment: 82 page

Flow characteristics of Newtonian and non-Newtonian fluids in a vessel stirred by a 60° pitched blade impeller

Mean and rms velocity characteristics of two Newtonian flows at Reynolds numbers of 12,800 (glycerin solution) and 48,000 (water) and of a non-Newtonian flow (0.2% CMC solution, at a power number similar to the Newtonian glycerin flow) in a mixing vessel stirred by a 60° pitched blade impeller have been measured by laser Doppler velocimetry (LDV). The velocity measurements, resolved over 360° and 1.08° of impeller rotation, showed that the mean flow of the two power number matched glycerin and CMC flows were similar to within 3% of the impeller tip velocity and the turbulence intensities generally lower in the CMC flow by up to 5% of the tip velocity. The calculated mean flow quantities showed similar discharge coefficient and pumping efficiency in all three flows and similar strain rate between the two power number matched glycerin and CMC flows; the strain rate of the higher Reynolds number Newtonian flow was found to be slightly higher. The energy balance around the impeller indicated that the CMC flow dissipated up to 9% more of the total input power and converted 7% less into the turbulence compared to the glycerin flow with the same power input which could lead to less effective mixing processes where the micro-mixing is important

Pulmonary artery occlusion pressure

The bedside estimation of left ventricular (LV) performance of critically ill patients is an important aspect of the diagnosis and management of these patients. Ever since the introduction of the balloon flotation pulmonary catheterization, health care providers have used measurements of pulmonary artery occlusion pressure (Ppao) to estimate both pulmonary venous pressure and LV preload. However, the significance of any specific value for Ppao in the diagnosis and treatment of cardiovascular insufficiency in patients with diseases other than cardiogenic shock has never been validated. The reasons for this continued uncertainty reflect both intrinsic inaccuracies in the measurement of Ppao and misconceptions about their physiological significance. In this first Physiological Note we shall discuss problems in the accurate measurement of Ppao at the bedside, while in the second Physiological Note we shall discuss the physiological significance of Ppao measurements © 2006 Springer-Verlag Berlin Heidelberg