Periodic Reporting for period 1 - GREENPIX (First miniaturized universal gas analyzer for all renewable gases in all their extensive and complex composition at all production and consumption phases including Hydrogen purity for fuel cells)
Berichtszeitraum: 2022-02-01 bis 2023-04-30
Quality control, pollutants identification and other tests are needed along the renewable gases value chain. Currently, there are two main problems associated with these types of tests:
High cost of gas analysing instrumentation. State of the art analysers are big and expensive and most of the time not suited to on-site analysis unless huge infrastructure investment. The main reason behind high costs is that several elements still have to be produced and integrated manually.
Performance and reliability. Specifications for the analysis of pollutant compounds in renewable gases are more and more demanding and require extremely sensitive and accurate analysers that currently can only be performed by laboratories. The cost of failures in production or distribution facilities can be much higher than the cost of equipment itself.
On-site, cheaper, and reliable gas analysers are required.
The GREENPIX project, led by Apix, is developing a new chromatograph instrument to measure gas quality for various applications, such as biomethane, fuel cells, hydrogen, and CO2. The goal is to offer a single, cost-effective instrument (typically 10 times less expensive than current solutions) that meets the constraints of different targeted applications. Additionally, the instrument will have minimal operational costs and low maintenance requirements. To achieve these objectives, the GREENPIX project is addressing several key topics. The first is to automate the instrument's assembly process as much as possible, reducing manual operations by using fluidic manifolds that hold the necessary building blocks (injector, column, and detectors) for a GC instrument. These building blocks are redesigned to be compatible with the fluidic manifold assembly.
The second topic focuses on improving the instrument's limit of detection. Two strategies are being studied: the development of specific chemical layers coating our proprietary detector, named the NGD, whose detection principle is based on an absorption/desorption process of the gas of interest on a resonating structure; and cooling the NGD at low temperatures to significantly improve the adsorption/desorption process.
The last topic explored in GREENPIX is the deployment of artificial intelligence algorithms to improve the instrument's self-diagnosis, predict potential failures, and enhance the chromatogram processing software for better peak detection of gases.
At the end of the project, the final instrument will be demonstrated on site with specific early adopters who are leaders in their markets.
High cost of gas analysing instrumentation. State of the art analysers are big and expensive and most of the time not suited to on-site analysis unless huge infrastructure investment. The main reason behind high costs is that several elements still have to be produced and integrated manually.
Performance and reliability. Specifications for the analysis of pollutant compounds in renewable gases are more and more demanding and require extremely sensitive and accurate analysers that currently can only be performed by laboratories. The cost of failures in production or distribution facilities can be much higher than the cost of equipment itself.
On-site, cheaper, and reliable gas analysers are required.
The GREENPIX project, led by Apix, is developing a new chromatograph instrument to measure gas quality for various applications, such as biomethane, fuel cells, hydrogen, and CO2. The goal is to offer a single, cost-effective instrument (typically 10 times less expensive than current solutions) that meets the constraints of different targeted applications. Additionally, the instrument will have minimal operational costs and low maintenance requirements. To achieve these objectives, the GREENPIX project is addressing several key topics. The first is to automate the instrument's assembly process as much as possible, reducing manual operations by using fluidic manifolds that hold the necessary building blocks (injector, column, and detectors) for a GC instrument. These building blocks are redesigned to be compatible with the fluidic manifold assembly.
The second topic focuses on improving the instrument's limit of detection. Two strategies are being studied: the development of specific chemical layers coating our proprietary detector, named the NGD, whose detection principle is based on an absorption/desorption process of the gas of interest on a resonating structure; and cooling the NGD at low temperatures to significantly improve the adsorption/desorption process.
The last topic explored in GREENPIX is the deployment of artificial intelligence algorithms to improve the instrument's self-diagnosis, predict potential failures, and enhance the chromatogram processing software for better peak detection of gases.
At the end of the project, the final instrument will be demonstrated on site with specific early adopters who are leaders in their markets.
In this period, we have been working extensively on the development of detectors packaging and on/off silicon valves that are compatible with integration on a microfluidic manifold. The aim is to create advanced microfluidic systems automatically assembled to fabricate compact and high-performance chromatographs. First multi-detector manifold component has been achieved and validated.
Additionally, we have been designing silicon and glass microcolumns that are also compatible with integration on a microfluidic manifold. We have also been selecting specific chemistries to coat the NGD (next-generation detector) to enhance its performance. First chemical treatments have been done on NGD devices. To further improve the performance of the NGD, we have also been working on the development of a cryogenic system to cool it down. Cryogenic system has been delivered and firsts tests are under progress. Lastly, we have been developing AI algorithms that can be used to analyse the data collected by our chromatograph. The goal is to improve the self-diagnosis of our instrument, to help its maintenance by predicting its risks of failure, and eventually to improve our chromatogram processing software to better detect the different peaks of gas.
Architectures of analytical module, analytical channel and systems have been done. Development of specific electronic boards is under progress.
Additionally, we have been designing silicon and glass microcolumns that are also compatible with integration on a microfluidic manifold. We have also been selecting specific chemistries to coat the NGD (next-generation detector) to enhance its performance. First chemical treatments have been done on NGD devices. To further improve the performance of the NGD, we have also been working on the development of a cryogenic system to cool it down. Cryogenic system has been delivered and firsts tests are under progress. Lastly, we have been developing AI algorithms that can be used to analyse the data collected by our chromatograph. The goal is to improve the self-diagnosis of our instrument, to help its maintenance by predicting its risks of failure, and eventually to improve our chromatogram processing software to better detect the different peaks of gas.
Architectures of analytical module, analytical channel and systems have been done. Development of specific electronic boards is under progress.
The main results over the state of the art obtained so far are:
- Double detection capability with the TCD and NGD detectors integrated on a single manifold.
- Demonstration of on/off silicon microvalves mounted on a silicon manifold.
- Double detection capability with the TCD and NGD detectors integrated on a single manifold.
- Demonstration of on/off silicon microvalves mounted on a silicon manifold.