1. Buying Professionally Designed and Standardised Equipment:
In lesson 3 we reviewed how most labs are currently setup. In order to improve their performance, researchers need more standardisation, and dedicated equipment packages that can be used by all laboratories.
By using professional and standardised solutions for heating, mixing and feeding, it will become much easier to repeat or build on previously reported experiments. It will also be easier to educate skilled lab workers, because simple instructions videos and manuals can be used.
2. Welcoming Automation:
With the goals to reduce human error and free up lab workers’ time, more automatic functions could be introduced.
Automatic and continuous gas measurements can simplify the testing procedure and produce higher quality data, making it more reliable
Continuous measurements of temperature and pressure should be introduced – as well as automatic corrections of these parameters. Not only will this reduce the time and effort required from the lab worker, but it will also guarantee that the data is presented in a consistent and accurate manner.
With less time dedicated to manually managing tests, it becomes possible to perform more parallel tests and thereby drive the study much further.
3. Sharing Data and Engaging with Online Communities:
The development of online databases and practitioner communities greatly advances the field of AD research. These tools are already extremely helpful for data management and communicating latest research. They are particularly useful for continuous processes with large datasets.
By improving the accessibility of your test results, data from different experimental batches cannot only be used within your research team but also be shared easily with desired partners.
Today this is a highly achievable: With cloud-based solutions becoming increasingly popular, it is easier than ever to store, study and share complex datasets.
By implementing the recommendations mentioned hereabove it is expected that the advancements in the research related to AD will progress much faster. Researchers will have access to data of both higher quantity and quality and key findings can more easily spread via online communities, resulting in higher impact. This will lead to faster solving of the current technological challenges, namely slow and inefficient degradation processes, and nutrient limited and toxic substrates. It will also increase the understanding of the microbiology and process dynamics.