Miau, a microbalance autosampler

Adapting an elemental analyser to perform high-temperature catalytic oxidation for dissolved organic carbon measurements in water

RATIONALE

Many laboratories employ elemental analyzers (EAs) coupled to isotope ratio mass spectrometers (IRMSs) to measure carbon stable isotope ratios (δ¹³ C) in solid samples. Dissolved organic carbon (DOC) in most natural water samples cannot be analyzed using this approach unless time-consuming preconcentration is employed.

METHODS

An EA-IRMS can be used to measure DOC δ¹³ C in natural waters without the need for sample preconcentration by employing high-temperature catalytic oxidation. An autosampler injects water into the EA reactor at 680°C filled with platinum catalyst beads, where all carbon is converted to CO₂ . Remaining water and halides are removed, while CO₂ is trapped in a cryotrap and later released to the IRMS.

RESULTS

Measurements were accurate (deviation <0.3‰ compared to solid sample measurements) and precise (error of 0.3‰ for concentrations ≥46 μM). Blanks were present and accounted for. Salinity up to seawater level did not affect accuracy or precision, but limited the number of samples that could be run before cleaning of the reactor was needed. DOC δ¹³ C in a river/estuary varied between -25.7 and -23.2‰, with higher values for waters with higher salinity, as expected. Deep-sea water reference material had a value of -22.9 ± 0.5‰, very similar to those found in recent reports employing similar techniques.

CONCLUSION

Adapting an EA is a feasible approach for the measurement of DOC δ¹³ C in natural waters. The low cost and simplicity of the system allow its use in any laboratory already equipped with EA-IRMS.

Automated weighing in the stable isotope lab: When less is more

Automated powder weighing is an elusive goal in scientific laboratories. The main problem is that powders are much more heterogeneous than liquids, making difficult the development of a unified automation solution for their handling. A compromise has been presented with miau, a low-cost, open-source autosampler for microbalance. Miau was demonstrably useful to perform the automated weighing of some powders, as long as the same powder is weighed repeatedly, which is useful for preparing standards to be measured along samples. However, in stable-isotope laboratories it is also necessary to weigh samples, which are often very heterogeneous, and thus not amenable for miau. Here it is demonstrated how miau can be adapted to handle not only standards, but also samples, using the "less is more" philosophy:•Miau is simplified to perform only the manipulation of weighing capsules, becoming "miau redux"•Miau redux can be used not only for standards, but for a variety of samples as well•Miau redux saves 64% of operator time when using a microbalance.

Mostly 3D printed chemical synthesis robot

Thanks to the current technology derived from the open-source world of 3D printers, it is conceivable to automate some laboratory activities remotely. In fact, simple operations, such as mixing liquids or solutions, stirring, heating and sampling to control the reaction course can be easily implemented. The idea of ​​automating the chemical laboratory would have immediate advantages, for example in terms of safety. The operators will be able to remotely control the machines and in case of handling dangerous material or accidents, there would only be damage to the hardware components. Many of the process parameters can also be read with low-cost probes and devices that can be easily interfaced with microprocessors. We include for example, but not limited to, temperature, pH, redox potential, electrochemical measurements in general or the use of probes for specific analytes. In this work we wish to present our liquid sampling station able to control up to 6 reagents and a temperature controlled chemical reactor. The workstation can be used graphically with an intuitive interface written in Python. The control program is structured to have modularity and contains a built-in programming language to control the interfaces.

Ender3 3D printer kit transformed into open, programmable syringe pump set

A cheap, open source 3D printer (Creality Ender 3) is transformed into an Open Hardware, programmable syringe pump set. Only 3 parts need to be purchased outside of the printer kit. All other parts are either in the Ender 3 kit, or can be 3D printed. No prior knowledge in electronics or programming languages is required. The pumps are controlled by the 3D printer firmware and motherboard and programmed in simple G-code text files. The total cost of a three pumps setup is ∼€170. The pumps are capable of reaching stable flows down to 5 µL/min using cheap, disposable 10 mL syringes. Higher flow speeds are also achievable, in the order of mL/min.

Computer Vision for Continuous Bedside Pharmacological Data Extraction: A Novel Application of Artificial Intelligence for Clinical Data Recording and Biomedical Research

Introduction: As real time data processing is integrated with medical care for traumatic brain injury (TBI) patients, there is a requirement for devices to have digital output. However, there are still many devices that fail to have the required hardware to export real time data into an acceptable digital format or in a continuously updating manner. This is particularly the case for many intravenous pumps and older technological systems. Such accurate and digital real time data integration within TBI care and other fields is critical as we move towards digitizing healthcare information and integrating clinical data streams to improve bedside care. We propose to address this gap in technology by building a system that employs Optical Character Recognition through computer vision, using real time images from a pump monitor to extract the desired real time information. Methods: Using freely available software and readily available technology, we built a script that extracts real time images from a medication pump and then processes them using Optical Character Recognition to create digital text from the image. This text was then transferred to an ICM + real-time monitoring software in parallel with other retrieved physiological data. Results: The prototype that was built works effectively for our device, with source code openly available to interested end-users. However, future work is required for a more universal application of such a system. Conclusion: Advances here can improve medical information collection in the clinical environment, eliminating human error with bedside charting, and aid in data integration for biomedical research where many complex data sets can be seamlessly integrated digitally. Our design demonstrates a simple adaptation of current technology to help with this integration.