Automation and Computerization of (Bio)sensing Systems

Sensing systems necessitate automation to reduce human effort, increase reproducibility, and enable remote sensing. In this perspective, we highlight different types of sensing systems with elements of automation, which are based on flow injection and sequential injection analysis, microfluidics, robotics, and other prototypes addressing specific real-world problems. Finally, we discuss the role of computer technology in sensing systems. Automated flow injection and sequential injection techniques offer precise and efficient sample handling and dependable outcomes. They enable continuous analysis of numerous samples, boosting throughput, and saving time and resources. They enhance safety by minimizing contact with hazardous chemicals. Microfluidic systems are enhanced by automation to enable precise control of parameters and increase of analysis speed. Robotic sampling and sample preparation platforms excel in precise execution of intricate, repetitive tasks such as sample handling, dilution, and transfer. These platforms enhance efficiency by multitasking, use minimal sample volumes, and they seamlessly integrate with analytical instruments. Other sensor prototypes utilize mechanical devices and computer technology to address real-world issues, offering efficient, accurate, and economical real-time solutions for analyte identification and quantification in remote areas. Computer technology is crucial in modern sensing systems, enabling data acquisition, signal processing, real-time analysis, and data storage. Machine learning and artificial intelligence enhance predictions from the sensor data, supporting the Internet of Things with efficient data management.

Machine learning for yield prediction for chemical reactions using in situ sensors

Machine learning models were developed to predict product formation from time-series reaction data for ten Buchwald-Hartwig coupling reactions. The data was provided by DeepMatter and was collected in their DigitalGlassware cloud platform. The reaction probe has 12 sensors to measure properties of interest, including temperature, pressure, and colour. Colour was a good predictor of product formation for this reaction and machine learning models were able to learn which of the properties were important. Predictions for the current product formation (in terms of % yield) had a mean absolute error of 1.2%. For predicting 30, 60 and 120 min ahead the error rose to 3.4, 4.1 and 4.6%, respectively. The work here presents an example into the insight that can be obtained from applying machine learning methods to sensor data in synthetic chemistry.

Chemputation and the Standardization of Chemical Informatics

The explosion in the use of machine learning for automated chemical reaction optimization is gathering pace. However, the lack of a standard architecture that connects the concept of chemical transformations universally to software and hardware provides a barrier to using the results of these optimizations and could cause the loss of relevant data and prevent reactions from being reproducible or unexpected findings verifiable or explainable. In this Perspective, we describe how the development of the field of digital chemistry or chemputation, that is the universal code-enabled control of chemical reactions using a standard language and ontology, will remove these barriers allowing users to focus on the chemistry and plug in algorithms according to the problem space to be explored or unit function to be optimized. We describe a standard hardware (the chemical processing programming architecture-the ChemPU) to encompass all chemical synthesis, an approach which unifies all chemistry automation strategies, from solid-phase peptide synthesis, to HTE flow chemistry platforms, while at the same time establishing a publication standard so that researchers can exchange chemical code (χDL) to ensure reproducibility and interoperability. Not only can a vast range of different chemistries be plugged into the hardware, but the ever-expanding developments in software and algorithms can also be accommodated. These technologies, when combined will allow chemistry, or chemputation, to follow computation-that is the running of code across many different types of capable hardware to get the same result every time with a low error rate.

BioChemPen for a Rapid Analysis of Compounds Supported on Solid Surfaces

We present BioChemPen, a portable wireless biosensor device for rapid analysis of substances adsorbed on solid surfaces. The device takes advantage of (bio)luminescent reactions taking place in a hydrogel matrix. In a typical embodiment, the active element of this device is a hydrogel disk (chemotransducer) containing enzyme(s), electrolyte solution, and all of the necessary substrates. When the hydrogel is exposed to a solid sample surface containing the target analyte, light is produced. A photoresistor (phototransducer), placed in close proximity to the hydrogel disk, detects the light. The operation of the BioChemPen is enabled by a MicroPython PyBoard microcontroller board and other low-cost electronic modules. The obtained results are immediately uploaded to the Internet cloud. In one application, we demonstrate an analysis of hypochlorite-containing cleaning agents present on the surfaces of daily use objects by an assay based on hydrogel embedded with luminol and hydrogen peroxide. In another application, we use hydrogel embedded with luciferin, luciferase, and pyruvate kinase to detect adenosine triphosphate (ATP), and adenosine diphosphate (ADP), and link the ATP content with meat freshness. Lastly, we demonstrate the detection of organophosphate pesticides present on vegetables with the hydrogel containing acetylcholinesterase, choline oxidase, and horseradish peroxidase. The limits of detection for sodium hypochlorite, ATP, ADP, and chlorpyrifos-methyl (a pesticide) were 7.95 × 10^-11, 2.73 × 10^-13, 2.35 × 10^-12, and 2.59 × 10^-10 mol mm^-2, respectively.

Telechemistry 2.0: Remote monitoring of fluorescent chemical reactions

Implementation of the Internet-of-Things in chemistry research has the potential to improve research methodologies. Here, we describe a cloud-integrated real-time laboratory monitoring system for: (i) monitoring reactions involving fluorescent chemical species, and (ii) monitoring laboratory environment for safety purpose. A probe-type fluorescence detection system has been constructed to monitor reactions that involve fluorescent molecules. This device incorporates an in-house-built 3D-printed probe, two optical fibers, a light-emitting diode, a photoresistor, and a microcontroller board (MCB). The MCB relays experimental data to a single-board computer (SBC), which then uploads the data to a cloud-based platform (ThingSpeak) for data storage and visualization. The SBC is also connected to auxiliary sensors to measure relative alcohol vapor concentration, temperature, and humidity at different locations in the laboratory. The device has been validated and tested for its performance by monitoring a fluorescent chemical reaction (synthesis of fluorescent gold nanoclusters) for a period of 12 h.

Catalytic Oxygenation-Mediated Extraction as a Facile and Green Way to Analyze Volatile Solutes

Sparging-based methods have long been used to liberate volatile organic compounds (VOCs) from liquid sample matrices prior to analysis. In these methods, a carrier gas is delivered from an external source. Here, we demonstrate "catalytic oxygenation-mediated extraction" (COME), which relies on biocatalytic production of oxygen occurring directly in the sample matrix. The newly formed oxygen (micro)bubbles extract the dissolved VOCs. The gaseous extract is immediately transferred to a separation or detection system for analysis. To start COME, dilute hydrogen peroxide is injected into the sample supplemented with catalase enzyme. The entire procedure is performed automatically-after pressing a "start" button, making a clapping sound, or triggering from a smartphone. The pump, valves, and detection system are controlled by a microcontroller board. For quality control and safety purposes, the reaction chamber is monitored by a camera linked to a single-board computer, which follows the enzymatic reaction progress by analyzing images of foam in real time. The data are instantly uploaded to the internet cloud for retrieval. The COME apparatus has been coupled on-line with the gas chromatography electron ionization mass spectrometry (MS) system, atmospheric pressure chemical ionization (APCI) MS system, and APCI ion-mobility spectrometry system. The three hyphenated variants have been tested in analyses of complex matrices (e.g., fruit-based drinks, whiskey, urine, and stored wastewater). In addition to the use of catalase, COME variants using crude potato pulp or manganese(IV) dioxide have been demonstrated. The technique is inexpensive, fast, reliable, and green: it uses low-toxicity chemicals and emits oxygen.

Monitoring Chemistry In Situ with a Smart Stirrer: A Magnetic Stirrer Bar with an Integrated Process Monitoring System

Inspired by the miniaturization and efficiency of the sensors for telemetry, we have developed a device that provides the functionalities of laboratory magnetic stirring and integrated multisensor monitoring of various chemical reaction parameters. The device, called "Smart Stirrer", when immersed in a solution, can in situ monitor physical properties of the chemical reaction such as the temperature, conductivity, visible spectrum, opaqueness, stirring rate, and viscosity. This data is transmitted real-time over a wireless connection to an external system, such as a PC or smartphone. The flexible open-source software architecture allows effortless programming of the operation parameters of the Smart Stirrer in accordance with the end-user needs. The concept of the Smart Stirrer device with an integrated process monitoring system has been demonstrated in a series of experiments showing its capability for many hours of continuous telemetry with fine accuracy and a high data rate. Such a device can be used in conventional research laboratories, industrial production lines, flow reactors, and others where it can log the state of the process to ensure repeatability and operational consistency.

Elevating Chemistry Research with a Modern Electronics Toolkit

With the rapid development of high technology, chemical science is not as it used to be a century ago. Many chemists acquire and utilize skills that are well beyond the traditional definition of chemistry. The digital age has transformed chemistry laboratories. One aspect of this transformation is the progressing implementation of electronics and computer science in chemistry research. In the past decade, numerous chemistry-oriented studies have benefited from the implementation of electronic modules, including microcontroller boards (MCBs), single-board computers (SBCs), professional grade control and data acquisition systems, as well as field-programmable gate arrays (FPGAs). In particular, MCBs and SBCs provide good value for money. The application areas for electronic modules in chemistry research include construction of simple detection systems based on spectrophotometry and spectrofluorometry principles, customizing laboratory devices for automation of common laboratory practices, control of reaction systems (batch- and flow-based), extraction systems, chromatographic and electrophoretic systems, microfluidic systems (classical and nonclassical), custom-built polymerase chain reaction devices, gas-phase analyte detection systems, chemical robots and drones, construction of FPGA-based imaging systems, and the Internet-of-Chemical-Things. The technology is easy to handle, and many chemists have managed to train themselves in its implementation. The only major obstacle in its implementation is probably one's imagination.

Facilitating chemical and biochemical experiments with electronic microcontrollers and single-board computers

Since the advent of modern science, researchers have had to rely on their technical skills or the support of specialized workshops to construct analytical instruments. The notion of the 'fourth industrial revolution' promotes construction of customized systems by individuals using widely available, inexpensive electronic modules. This protocol shows how chemists and biochemists can utilize a broad range of microcontroller boards (MCBs) and single-board computers (SBCs) to improve experimental designs and address scientific questions. We provide seven example procedures for laboratory routines that can be expedited by implementing this technology: (i) injection of microliter-volume liquid plugs into microscale capillaries for low-volume assays; (ii) transfer of liquid extract to a mass spectrometer; (iii) liquid-gas extraction of volatile organic compounds (called 'fizzy extraction'), followed by mass spectrometric detection; (iv) monitoring of experimental conditions over the Internet cloud in real time; (v) transfer of analytes to a mass spectrometer via a liquid microjunction interface, data acquisition, and data deposition into the Internet cloud; (vi) feedback control of a biochemical reaction; and (vii) optimization of sample flow rate in direct-infusion mass spectrometry. The protocol constitutes a primer for chemists and biochemists who would like to take advantage of MCBs and SBCs in daily experimentation. It is assumed that the readers have not attended any courses related to electronics or programming. Using the instructions provided in this protocol and the cited material, readers should be able to assemble simple systems to facilitate various procedures performed in chemical and biochemical laboratories in 1-2 d.