Integration of spectroscopic techniques and machine learning for optimizing Phaeodactylum tricornutum cell and fucoxanthin productivity.

The development of sustainable and controlled microalgae bioprocesses relies on robust and rapid monitoring tools that facilitate continuous process optimization, ensuring high productivity and minimizing response times. In this work, we analyse the influence of medium formulation on the growth and productivity of axenic Phaeodactylum tricornutumcultures and use the resulting data to develop machine learning (ML) models based on spectroscopy. Our culture assays produced a comprehensive dataset of 255 observations, enabling us to train 55 (24+31) robust models that predict cells or fucoxanthin directly from either absorbance or 2D-fluorescence spectroscopy.

Non-invasive and real-time monitoring of polyhydroxyalkanoates production using two-dimensional fluorescence spectroscopy.

Bioplastics are a sustainable and environmental-friendly alternative to the conventional petroleum-based plastics, namely due to their source (biobased) and due to their biodegradability or both. Polyhydroxyalkanoates (PHA) stand out among the bioplastics group by being intracellular biobased, biodegradable and biocompatible polymers. PHA production has been highly investigated during the last decades.

Development and Implementation of MBR Monitoring: Use of 2D Fluorescence Spectroscopy.

The monitoring of a membrane bioreactor (MBR) requires the assessment of both biological and membrane performance. Additionally, the development of membrane fouling and the requirements for frequent membrane cleaning are still major concerns during MBR operation, requiring tight monitoring and system characterization. Transmembrane pressure is usually monitored online and allows following the evolution of membrane performance.

Nitrate Removal by Donnan Dialysis and Anion-Exchange Membrane Bioreactor Using Upcycled End-of-Life Reverse Osmosis Membranes.

This work explores the application of Reverse Osmosis (RO) upcycled membranes, as Anion Exchange Membranes (AEMs) in Donnan Dialysis (DD) and related processes, such as the Ion Exchange Membrane Bioreactor (IEMB), for the removal of nitrate from contaminated water, to meet drinking water standards. Such upcycled membranes might be manufactured at a lower price than commercial AEMs, while their utilization reinforces the commitment to a circular economy transition. In an effort to gain a better understanding of such AEMs, confocal µ-Raman spectroscopy was employed, to assess the distribution of the ion-exchange sites through the thickness of the prepared membranes, and 2D fluorescence spectroscopy, to evaluate alterations in the membranes caused by fouling and chemical cleaning The best performing membrane reached a 56% average nitrate removal within 24 h in the DD and IEMB systems, with the latter furthermore allowing for simultaneous elimination of the pollutant by biological denitrification, thus avoiding its discharge into the environment.

Perspectives of fluorescence spectroscopy for online monitoring in microalgae industry.

Microalgae industrial production is viewed as a solution for alternative production of nutraceuticals, cosmetics, biofertilizers, and biopolymers. Throughout the years, several technological advances have been implemented, increasing the competitiveness of microalgae industry. However, online monitoring and real-time process control of a microalgae production factory still require further development.

From Black Box to Machine Learning: A Journey through Membrane Process Modelling.

Membrane processes are complex systems, often comprising several physicochemical phenomena, as well as biological reactions, depending on the systems studied. Therefore, process modelling is a requirement to simulate (and predict) process and membrane performance, to infer about optimal process conditions, to assess fouling development, and ultimately, for process monitoring and control. Despite the actual dissemination of terms such as Machine Learning, the use of such computational tools to model membrane processes was regarded by many in the past as not useful from a scientific point-of-view, not contributing to the understanding of the phenomena involved.

Predicting the concentration of hazardous phenolic compounds in refinery wastewater-a multivariate data analysis approach.

The present study focused on the methodology for identification of the wastewater stream that presents the highest phenolic impact at a large oil refinery. As a case-study, the oil refinery, Petrogal S.A.

Fluorescence spectroscopy and chemometrics for simultaneous monitoring of cell concentration, chlorophyll and fatty acids in Nannochloropsis oceanica.

Online monitoring of algal biotechnological processes still requires development to support economic sustainability. In this work, fluorescence spectroscopy coupled with chemometric modelling is studied to monitor simultaneously several compounds of interest, such as chlorophyll and fatty acids, but also the biomass as a whole (cell concentration). Fluorescence excitation-emission matrices (EEM) were acquired in experiments where different environmental growing parameters were tested, namely light regime, temperature and nitrogen (replete or deplete medium).

Valorization of raw brewers' spent grain through the production of volatile fatty acids.

This work is focused on production of volatile fatty acids (VFA) through anaerobic digestion (AD) using raw (without pre-treatment) brewers' spent grain (BSG) as feedstock. VFAs are by-products from AD of organic wastes with wide potential industrial application in bioplastic production. A long term fed batch stirred-tank reactor was operated and the impact of three hydraulic retention times (HRT) and two organic loading rates (OLR) on VFA production was assessed.

An efficient method for anthocyanins lipophilization based on enzyme retention in membrane systems.

Anthocyanin lipophilization emerged as an efficient technique to improve their chemical stability, liposolubility and antioxidant properties for novel technological applications. This work describes an efficient method for the synthesis of cyanidin-3-glucoside-fatty acid conjugate using a Candida antarctica lipase B-rich extract, without further purification and retained in a porous membrane. Due to the enzyme retention within the membrane structure it was possible to improve the yield of the lipophilization reaction by 2.

Nitrous oxide emissions from a full-scale biological aerated filter (BAF) subject to seawater infiltration.

The increase of salt concentrations in influent wastewaters will be a consequence of the sea level rises in coastal areas due to climate change and the future use of seawater to flush toilets as a cost-attractive option for alternative water resources. Yet, little is known about the salinity effect on full-scale wastewater treatment plants (WWTPs) performance and on greenhouse gas (GHG) emissions, such as nitrous oxide (NO). This study aimed at quantifying the NO emissions of a full-scale biological aerated filter (BAF) and to correlate the dynamic behavior of the emissions with the process conditions and the periods of infiltration of seawater.

Bioremoval of priority polycyclic aromatic hydrocarbons by a microbial community with high sorption ability.

The treatment of large volumes of wastewater during oil refining is presently a challenge. Bioremediation has been considered an eco-friendly approach for the removal of polycyclic aromatic hydrocarbons (PAHs), which are one of the most hazardous groups of organic micropollutants. However, it is crucial to identify native PAH-removing microorganisms for the development of an effective bioremediation process.

Dynamic change of pH in acidogenic fermentation of cheese whey towards polyhydroxyalkanoates production: Impact on performance and microbial population.

Polyhydroxyalkanoates (PHA) are a sustainable alternative to conventional plastics that can be obtained from industrial wastes/by-products using mixed microbial cultures (MMC). MMC PHA production is commonly carried out in a 3-stage process of acidogenesis, PHA culture selection and accumulation. This research focused on the possibility of tailoring PHA by controlling the acidogenic reactor operating conditions, namely pH, using cheese whey as model feedstock.

Impact of sludge retention time on the fine composition of the microbial community and extracellular polymeric substances in a membrane bioreactor.

Membrane bioreactors (MBRs) are an advanced technology for wastewater treatment whose wide application has been hindered by rapid fouling of the membranes. MBRs can be operated with long sludge retention time (SRT), a crucial parameter impacting microbial selection in the reactor. This also affects filtration performance, since a major fouling agent are the extracellular polymeric substances (EPS).

2D fluorescence spectroscopy for monitoring ion-exchange membrane based technologies - Reverse electrodialysis (RED).

Reverse electrodialysis (RED) is one of the emerging, membrane-based technologies for harvesting salinity gradient energy. In RED process, fouling is an undesirable operation constraint since it leads to a decrease of the obtainable net power density due to increasing stack electric resistance and pressure drop. Therefore, early fouling detection is one of the main challenges for successful RED technology implementation.

Chitin-glucan complex production by Komagataella (Pichia) pastoris: impact of cultivation pH and temperature on polymer content and composition.

Chitin-glucan complex (CGC) is a valuable biomaterial that can be extracted from the cell wall of several yeast and fungi. In this work, the yeast Komagataella (Pichia) pastoris was grown on glycerol as the sole carbon source in batch cultivation experiments to evaluate the effect of pH (3.5-6.

Development of a hybrid model strategy for monitoring membrane bioreactors.

In the present study, the performance of a membrane bioreactor (MBR) was modelled using a hybrid approach based on the activated sludge model number 3 (ASM3) combined with projection to latent structures (PLS) to predict the residuals of the ASM. The application of ASM to MBRs requires frequent re-calibration to adjust the model to variations in influent characteristics, determined through time-consuming analysis and batch tests. Considering this problem, the objective of this study was to improve ASM prediction ability with minimal additional monitoring effort.

Multivariate statistically-based modelling of a membrane bioreactor for wastewater treatment using 2D fluorescence monitoring data.

This work presents the development of multivariate statistically-based models for monitoring several key performance parameters of membrane bioreactors (MBR) for wastewater treatment. This non-mechanistic approach enabled the deconvolution of 2D fluorescence spectroscopy data, a powerful technique that has previously been shown to capture important information regarding MBR performance. Projection to latent structure (PLS) modelling was used to integrate 2D fluorescence data, after compression through parallel factor analysis (PARAFAC), with operation and analytical data to describe an MBR fouling indicator (transmembrane pressure, TMP), five descriptors of the effluent quality (total COD, soluble COD, concentration of nitrite and nitrate, total nitrogen and total phosphorus in the permeate) and the biomass concentration in the bioreactor (MLSS).