Dynamic Ion Speciation during the Hydrolysis of Aryltrifluoroborates*.

Organotrifluoroborates serve as coupling partners during transmetalation in the Suzuki-Miyaura reaction but require hydrolysis prior to the coupling reaction. Their anionic nature allows study of their hydrolysis by electrospray ionization mass spectrometry (ESI-MS) through real-time monitoring, complemented by pH analysis. The induction period varied according to the borates employed, and a dynamic series of equilibria for numerous ions was observed during hydrolysis. We found that the induction periods and reaction rates were sensitive to the R group of the borates, the shape of the reaction vessel, and stir rate.

Competitive Ligand Exchange and Dissociation in Ru Indenyl Complexes.

Kinetic profiles obtained from monitoring the solution-phase substitution chemistry of [Ru(η5-indenyl)(NCPh)(PPh3)2]+ (1) by both electrospray ionization mass spectrometry and 31P{1H} NMR are essentially identical, despite an enormous difference in sample concentrations for these complementary techniques. These studies demonstrate dissociative substitution of the NCPh ligand in 1. Competition experiments using different secondary phosphine reagents provide a ranking of phosphine donor abilities at this relatively crowded half-sandwich complex: PEt2H > PPh2H ≫ PCy2H. The impact of steric congestion at Ru is evident also in reactions of 1 with tertiary phosphines; initial substitution products [Ru(η5-indenyl)(PR3)(PPh3)2]+ rapidly lose PPh3, enabling competitive re-coordination of NCPh. Further solution experiments, relevant to the use of 1 in catalytic hydrophosphination, show that PPh2H out-competes PPh2CH2CH2CO2Bu t (the product of hydrophosphination of tert-butyl acrylate by PPh2H) for coordination to Ru, even in the presence of a 10-fold excess of the tertiary phosphine. Additional information on relative phosphine binding strengths was obtained from gas-phase MS/MS experiments, including collision-induced dissociation experiments on the mixed phosphine complexes [Ru(η5-indenyl)PP'P″]+, which ultimately appear in solution during the secondary phosphine competition experiments. Unexpectedly, unsaturated complexes [Ru(η5-indenyl)(PR2H)(PPh3)]+, generated in the gas-phase, undergo preferential loss of PR2H. We propose that competing orthometallation of PPh3 is responsible for the surprising stability of the [Ru(η5-indenyl)(PPh3)]+ fragment under these conditions.

PythoMS: A Python Framework To Simplify and Assist in the Processing and Interpretation of Mass Spectrometric Data.

Mass spectrometric data are copious and generate a processing burden that is best dealt with programmatically. PythoMS is a collection of tools based on the Python programming language that assist researchers in creating figures and video output that is informative, clear, and visually compelling. The PythoMS framework introduces a library of classes and a variety of scripts that quickly perform time-consuming tasks: making proprietary output readable; binning intensity vs time data to simulate longer scan times (and hence reduce noise); calculating theoretical isotope patterns and overlaying them in histogram form on experimental data (an approach that works even for overlapping signals); rendering videos that enable zooming into the baseline of intensity vs time plots (useful to make sense of data collected over a large dynamic range) or that depict the evolution of different species in a time-lapse format; calculating aggregates; and providing a quick first-pass at identifying fragments in MS/MS spectra. PythoMS is a living project that will continue to evolve as additional scripts are developed and deployed.

Automation isn't automatic.

Automation has become an increasingly popular tool for synthetic chemists over the past decade. Recent advances in robotics and computer science have led to the emergence of automated systems that execute common laboratory procedures including parallel synthesis, reaction discovery, reaction optimization, time course studies, and crystallization development. While such systems offer many potential benefits, their implementation is rarely automatic due to the highly specialized nature of synthetic procedures. Each reaction category requires careful execution of a particular sequence of steps, the specifics of which change with different conditions and chemical systems. Careful assessment of these critical procedural requirements and identification of the tools suitable for effective experimental execution are key to developing effective automation workflows. Even then, it is often difficult to get all the components of an automated system integrated and operational. Data flows and specialized equipment present yet another level of challenge. Unfortunately, the pain points and process of implementing automated systems are often not shared or remain buried deep in the SI. This perspective provides an overview of the current state of automation of synthetic chemistry at the benchtop scale with a particular emphasis on core considerations and the ensuing challenges of deploying a system. Importantly, we aim to reframe automation as decidedly not automatic but rather an iterative process that involves a series of careful decisions (both human and computational) and constant adjustment.

Data-science driven autonomous process optimization.

Autonomous process optimization involves the human intervention-free exploration of a range process parameters to improve responses such as product yield and selectivity. Utilizing off-the-shelf components, we develop a closed-loop system for carrying out parallel autonomous process optimization experiments in batch. Upon implementation of our system in the optimization of a stereoselective Suzuki-Miyaura coupling, we find that the definition of a set of meaningful, broad, and unbiased process parameters is the most critical aspect of successful optimization. Importantly, we discern that phosphine ligand, a categorical parameter, is vital to determination of the reaction outcome. To date, categorical parameter selection has relied on chemical intuition, potentially introducing bias into the experimental design. In seeking a systematic method for selecting a diverse set of phosphine ligands, we develop a strategy that leverages computed molecular feature clustering. The resulting optimization uncovers conditions to selectively access the desired product isomer in high yield.

Automated solubility screening platform using computer vision.

Solubility screening is an essential, routine process that is often labor intensive. Robotic platforms have been developed to automate some aspects of the manual labor involved. However, many of the existing systems rely on traditional analytic techniques such as high-performance liquid chromatography, which require pre-calibration for each compound and can be resource consuming. In addition, automation is not typically end-to-end, requiring user intervention to move vials, establish analytical methods for each compound and interpret the raw data. We developed a closed-loop, flexible robotic system with integrated solid and liquid dosing capabilities that relies on computer vision and iterative feedback to successfully measure caffeine solubility in multiple solvents. After initial researcher input (<2 min), the system ran autonomously, screening five different solvent systems (20-80 min each). The resulting solubility values matched those obtained using traditional manual techniques.

ChemOS: An orchestration software to democratize autonomous discovery.

The current Edisonian approach to discovery requires up to two decades of fundamental and applied research for materials technologies to reach the market. Such a slow and capital-intensive turnaround calls for disruptive strategies to expedite innovation. Self-driving laboratories have the potential to provide the means to revolutionize experimentation by empowering automation with artificial intelligence to enable autonomous discovery. However, the lack of adequate software solutions significantly impedes the development of self-driving laboratories. In this paper, we make progress towards addressing this challenge, and we propose and develop an implementation of ChemOS; a portable, modular and versatile software package which supplies the structured layers necessary for the deployment and operation of self-driving laboratories. ChemOS facilitates the integration of automated equipment, and it enables remote control of automated laboratories. ChemOS can operate at various degrees of autonomy; from fully unsupervised experimentation to actively including inputs and feedbacks from researchers into the experimentation loop. The flexibility of ChemOS provides a broad range of functionality as demonstrated on five applications, which were executed on different automated equipment, highlighting various aspects of the software package.

ChemOS: Orchestrating autonomous experimentation.

ChemOS aims to catalyze the expansion of autonomous laboratories and to disrupt the conventional approach to experimentation.

Mechanistic features of the copper-free Sonogashira reaction from ESI-MS.

The mechanism of the Sonogashira reaction in methanol was studied in detail using pressurized sample infusion electrospray ionization mass spectrometry (PSI-ESI-MS). Several key intermediates were identified and their structures were assigned by MS/MS studies. Cationic and anionic charged-tagged substrates were employed to look into the mechanism of this reaction from variety of angles. A reverse kinetic isotope effect was observed in which the reaction rate is accelerated in deuterated solvents (kH/kD = 0.6). The reaction was found to be zero order with respect to the aryl iodide and first order with respect to the phenylacetylene. A Hammett parameter of ρ = 1.4 indicates that the reaction is more favorable for aryl iodides with para EWGs. No evidence of product inhibition, dimerization of palladium catalyst, or agglomeration were observed. However, catalyst decomposition was inferred from a non-zero intercept in the plot of catalyst loading versus reaction rate. Monitoring the reaction by PSI-ESI-(-)MS on neutral and negatively charged substrates at variety of concentrations and conditions did not reveal any detectable anionic palladium complexes. Likewise no evidence of carbopalladation and relevant intermediates in the absence of a base was observed.

Practical approaches to the ESI-MS analysis of catalytic reactions.

Electrospray ionization mass spectrometry (ESI-MS) is a soft ionization technique commonly coupled with liquid or gas chromatography for the identification of compounds in a one-time view of a mixture (for example, the resulting mixture generated by a synthesis). Over the past decade, Scott McIndoe and his research group at the University of Victoria have developed various methodologies to enhance the ability of ESI-MS to continuously monitor catalytic reactions as they proceed. The power, sensitivity and large dynamic range of ESI-MS have allowed for the refinement of several homogenous catalytic mechanisms and could potentially be applied to a wide range of reactions (catalytic or otherwise) for the determination of their mechanistic pathways. In this special feature article, some of the key challenges encountered and the adaptations employed to counter them are briefly reviewed.