Microbial chain elongation represents an attractive alternative to chemical synthesis for the production of medium-chain fatty acids (MCFAs), enabling the upgrading of short-chain organic acids and alcohols through reverse ß-oxidation. Clostridium kluyveri typically utilizes ethanol as an electron donor and acetate as a carbon acceptor; however, the potential of alternative substrates derived from industrial and biorefinery waste streams, such as succinic acid, remains poorly investigated. This study investigated the feasibility of using succinic acid as an alternative electron acceptor in C. kluyveri fermentation for MCFA production. Anaerobic batch fermentations were conducted in sealed serum bottles (40 mL working volume) at 37°C and initial pH 6.8, evaluating the co-utilization of succinate and ethanol. The effects of succinate on metabolic activity, product distribution, and product yields were assessed. The results demonstrated that succinate can sustain C. kluyveri metabolism under anaerobic conditions, resulting in hexanoic acid concentrations of approximately 4.3–4.7 g/L when ethanol was supplied as the reducing equivalent source. The co-utilization of succinate and ethanol promoted butyrate and hexanoate formation, confirming the activation of chain elongation pathways and highlighting the strong dependence of succinate conversion on ethanol availability. Overall, these findings demonstrate the metabolic flexibility of C. kluyveri and support the integration of succinate-rich waste streams into MCFA bioproduction processes, provided sufficient reducing equivalents are available.

This work investigates the influence of different active phases on the hydrothermal liquefaction (HTL) of a tannery sludge (TS) performed in a 500 mL batch autoclave reactor at 350 °C for 10 min. The quality and energy-related properties of the bio-crude were evaluated through elemental analysis and higher heating value (HHV) determination. Results show that even if the bio-crude mass yield of the products does not vary significantly with the use of Fe, Zn and MgCl2, a variation of both the HTL products distribution and bio-crude composition are observed. In particular, Fe promotes the aqueous phase formation, while Zn limits organic transfer and MgCl2 promotes ash dissolution. Only Zn and MgCl2 improve the bio-crude quality in terms of C, N and S content.

The present study addresses mixing/segregation phenomena relevant to several chemical processes in bubbling fluidized bed reactors. Mixing between two dissimilar solids belonging to group B and D of Geldart classification is investigated in a lab-scale fluidized bed at high temperature. Capacitance probes are selected and tested innovatively to assess the transient phase of the mixing process between the two solids and the measurement of steady local mixture composition thanks to dissimilar dielectric properties of gas and solids and of the two chosen solids. A new procedure to gather quantitative results has been used considering expansion of the emulsion phase voidage and validated based on experimental data measured at 500 degrees C in the bubbling fluidized bed regime. The tests in transient conditions comprise the determination of two axial dispersion coefficients, Das,macro, on average, 3.1 x 10-2m2/s, and Da s , ranging between 1.8 and 3.1 x 10-3m2/s, referred to the tracers batch crossing the bed vertically without mixing with the rest of the bed and to the tracer batch disaggregating and reaching local steady-state concentrations in the dense bed, respectively. New insights are mainly revealed with reference to the phenomenology at steady-state conditions. In particular, axial and radial segregation patterns could be determined. Critical issues and corresponding improvements of the technique are highlighted and are mainly related to the properties of the two dissimilar solids and the capacitance probes amplification system.

Hydrogen has attracted significant interest as a sustainable energy carrier due to its high calorific value, high octane number, and the production of water as the only combustion product. However, most hydrogen is produced via steam methane reforming, a process not enough environmentally sustainable. Dark fermentation (DF) is a promising and eco-friendly alternative to produce hydrogen via the microbial oxidation of organic substrates under anaerobic conditions. Among the microorganisms active in DF, Thermotoga neapolitana is particularly noteworthy as it achieves the highest hydrogen yields reported to date. This thermophilic bacterium can grow on a wide variety of sugar-based substrates - those derived from agro-industrial waste included – and produce hydrogen, acetic acid, and lactic acid. The present study aimed to identify the most suitable carrier for biofilm formation by T. neapolitana. A series of batch experiments was conducted to test various materials as solid supports, including polypropylene, polyurethane sponge, silicone (Tygon tubing), metal nets, and nylon nets. The nylon nets provided the best results and were used in further experiments in continuous stirred-tank reactors to assess their performance. Results provide valuable insights for the optimization of biofilm-based hydrogen production and the potential application of T. neapolitana in sustainable bioenergy processes.

This study deals with the design and construction of a lab-scale prototype plant integrating a fluidized bed pyrolytic converter of solid residual biomass with a fluidized bed steam reformer of pyrolytic bioliquids. The system consists of the following main components: a pyrolytic converter, a continuous biomass feeder with a feed rate of 5 kg/h, a three-stage condensation system and a steam reforming reactor equipped with a liquid feeding system. The pyrolytic converter was designed as an internally circulating fluidized bed with a gas residence time of 1 s and a reactor height of 0.6 m. The reforming reactor height is 0.8 m with a diameter of 0.078 m. The operation of the plant is flexible as it encompasses both in-line and off-line operation modes as well as different bio-oil feedstock types for the steam reforming stage. Furthermore, thermodynamics analysis indicated that the maximum hydrogen yields at 650oC for in-line and off-line steam reforming were 0.11 and 0.10 kg H2 per kg of biomass, respectively. Increasing the temperature above 650°C led to a decrease in H2 production.

This study deals with fast pyrolysis of giant reed Arundo Donax in a bench scale fluidized bed apparatus. The effect of organic carbon loading onto the pyrolysis process was investigated, as it affects products yield and composition. Steady state pyrolysis experiments have been carried out at 500°C, at fixed gas superficial velocity and solids residence time. The carbon inventory in the bed has been controlled by means of a system that allows partial discharge/charge of solids from the bed, during continuous biomass feeding. Products yield, oil and gas composition have been characterized for different carbon inventories. Semi-quantitative analysis of bio-oil composition has been obtained by GC-MS technique, while gases have been analyzed with micro-GC. Results highlight that organic carbon loading does affect secondary decomposition pathways. Increasing the carbon loading, phenols increase, while ketones and organic acids decrease, together with an increase of CO, H2 and CH4. Results confirm that a proper control of char loading during fast pyrolysis is crucial to maximize yield and selectivity in desired chemical compounds.

Biocatalytic fixation of CO2 into carboxylic acids offers a sustainable route to carbon capture and utilization. Microbial cofactor-free non-oxidative decarboxylases catalyze the reversible ortho-carboxylation of phenolic substrates under mild conditions in the presence of adequate concentrations of bicarbonate ions. The development of industrial biocatalysts based on immobilized DHDBs asks for a rapid method for the screening of immobilization techniques and optimization of carboxylation operating conditions. UV spectroscopy methods applied to DHDBs activity assay are scarce and not standardized, differing in solvent composition, wavelengths, and data analysis, while HPLC methods are more popular, as they are useful for substrate screening over a variety of phenols. The present contribution reports the development of a UV spectroscopic method for the analysis of both the carboxylation and decarboxylation reactions catalyzed by decarboxylases with 2,3-dihydroxybenzoic acid (2,3-DHBA) and catechol as substrates/products. Absorption spectra show which wavelengths provided the most significant differences among catechol and 2,3-DHBA, and the optimal ones were set to follow catechol and 2,3-DHBA concentration dynamics in the reaction mixture. The activity assay of 2,3-DHBD from Aspergillus oryzae was defined to the developed method with 0.05 g/L enzyme and 10 mM 2,3-DHBA. Further carboxylation tests of catechol proved the effectiveness of the method at relevant conditions for future optimization of 2,3-DHBD immobilization and continuous flow monitoring of phenols conversion by enzymatic carboxylation.

Calcium Looping (CaL) for thermochemical energy storage of Concentrated Solar Power (CSP) is widely investigated to increase the dispatchability of solar energy. High reaction heat, high operation temperatures and cheapness of natural sorbents are among the strengths of the CaL-CSP process. The decay of reactivity along CaL cycles, further aggravated in directly irradiated reactors by possible overheating phenomena, and the poor absorption of solar energy by Ca-based sorbents (e.g., limestone), negatively affect its efficiency. This study investigates the use of physical mixtures of natural limestone and SiC to improve solar energy absorption and possibly shield limestone particles from overheating phenomena. An experimental campaign was performed in a directly irradiated fluidized bed reactor using 420-590 mu m limestone particles. A series of tests was carried out to optimize the size range of SiC and the SiC/CaO ratio. Then, CaL tests with the optimal mixture were performed under different process conditions. Results demonstrate that the use of a small fraction of SiC can enhance solar energy absorption while preventing chemical/physical interaction with CaO. The observed performance in terms of carbonation degree over cycling suggests that SiC was also able to shield lime particles, alleviating the decrease in reactivity induced by bed surface overheating. Energy storage density was computed with reference to either discontinuous (long-term storage) or continuous (short-term storage) CaL operation. Estimated values are high (530-1950 MJ m-3 depending on the conditions) and confirm the potential of this technology for both daily and seasonal energy storage. Altogether, the results of this study encourage the use of SiC/limestone physical mixtures to improve solar energy absorption for CaL processes in directly irradiated fluidized beds.

Enzymatic hydrolysis (EH) of lignocellulosic biomass (LB) is a central step in biorefinery saccharification, yet its large-scale implementation remains limited by unproductive enzyme adsorption on lignin and mass transfer constraints within biomass particles, both of which reduce sugar yields. The dosage of cellulases is crucial to achieve high conversion of polysaccharides and the amount of enzymes to the biomass is strongly affected by adsorption of enzymes on the biomass particles. In this study, a lab-scale packed-bed reactor was developed to investigate cellulases adsorption under continuous-flow conditions, to support the selection of enzyme dosage and in EH processes. The system enables the evaluation of enzyme partitioning between solid and liquid phases avoiding the limitations posed by mixing in stirred reactors at high-solids content. First, bovine serum albumin (BSA) was employed as an inert protein to set-up the apparatus and calibrate the on-line UV absorbance measurements. Then, the commercial cellulase cocktail Cellic® CTec2 was used as an industrially relevant biocatalyst to perform continuous adsorption tests with Cynara cardunculus and Arundo donax as reference biomass substrates. Breakthrough profiles and final protein partitioning showed an increase in adsorption capacity compared to data from batch adsorption tests in high-solids mixed systems. The study provides quantitative data for the design of heterogeneous biocatalytic processes relevant in the field of sugar-based biorefinery and opens opportunities to the study of multicomponent enzyme solutions on complex solid substrates.

The microbial conversion of C1 gas produced by the gasification of C-based streams (e.g., biomass and plastic) is a promising strategy for the production of bioalcohols and biocommodities. Acetogenic bacteria can produce value-added metabolites, such as acetate and butyrate, but their recovery is costly and energy intensive. The success of exploiting these acids may be their conversion into medium-chain fatty acids (MCFAs), such as n-caproic and n-caprylic acids, in a second fermentation step. Interest in MCFAs is related to their high hydrophobicity, high values, and high energy densities. These MCAF features make them better suited for chemical manufacturing and as biofuel precursors. Clostridium kluyveri is known for its ability to produce MCFAs under anaerobic fermentation via the reverse ß-oxidation pathway.

CO2 absorption in aqueous alkaline solutions promoted by carbonic anhydrase (CA) has received increased attention as a solution for post-combustion CO2 capture. In particular, accelerated weathering has emerged as an alternative approach for CO2 capture, mimicking nature's way to sequestrate CO2. In this study, an evolved CA from Desulfovibrio vulgaris was immobilized on magnetic nanoparticles (MNPs) offering a promising solution for the effective enzyme separation and recovery from complex and heterogeneous reaction media. The immobilization yields were high (86-98 %) and MNPs-DvCA8.0 were characterized based on standardized CO2 release and CO2 absorption assays and compared to the free enzyme. As a following step, MNPs-DvCA8.0 were applied as promoter in the accelerated weathering of insoluble lime mud, originating as a residue from a paper and pulp industry. MNPs-DvCA8.0 could be efficiently separated, washed and reused for up to 10 consecutive reaction cycles, offering a biocatalyst productivity equal to 2.83 g captured CO2/g CA opposite to the free enzyme that offered only 1.01 g captured CO2/g CA. CA immobilization could offer a mitigation strategy for the non-selective adsorption of the free enzyme on lime mud particles during the CO2 capturing reaction. The highly reproducible and robust immobilization method, that provides material separation based on its magnetic properties, could be a viable solution for the recovery of enzyme and its separation from the lime mud slurry, aiding in obtaining a highly pure solution rich in bicarbonate, as product.

Biomass pyrolysis involves the thermal decomposition of biomass constituents to yield valuable compounds to be exploited as biofuels and/or platform chemicals. Modelling biomass pyrolysis is challenging, but modern AI methods may give a valuable contribution to prediction of process yields, provided high-quality datasets are available. The published literature on the subject mostly refers to limited datasets, usually only a few hundred records, which are inadequate for robust AI applications. This work presents a dataset of about 500 observations with no missing values, compiled from published data on bio-oil/bio-liquid production via fixed-bed pyrolysis of different biomass. The dataset includes physicochemical properties of the biomass, key pyrolysis operating conditions, and bio-liquid yield. Each observation was carefully standardized to resolve inconsistencies in the terminology and/or lack of standardization. Best results, obtained from XGBoost, showed a MAE of 2.0 and an R2 of 0.8. Critical analysis of results demonstrates that AI applied to biomass pyrolysis data displays very good predictive ability. However, the ability to reproduce known relationships among key variables of the biomass and of the process appears to be more problematic. This is well shown by analysis of PDP plots, where some inconsistencies with known trends emerge when assessing the influence of selected variables on bio-liquid yield. Moreover, pronounced discrepancies with previously published studies by other research groups are observed when analyzing directional trends.

The deployment of sugar-based biorefineries is limited by the availability of feedstocks and by the cost of enzymes. Cynara cardunculus and Arundo donax are relevant non-food crops for the development of sugar-based biorefineries. Enzymatic hydrolysis of C. cardunculus and A. donax stalks have been optimized in terms of biocatalyst dosage and reuse. Optimal utilization of a commercial biocatalyst cocktail was achieved assessing the enzyme adsorption on the biomass slurry prior to the hydrolysis stage. The partitioning of cellulases between the liquid the substrate has been characterized for raw and pretreated biomasses. Enzyme uptakes up to 18 mg/g were recorded with 5 % biomass slurries and 0.2-3 g/L initial enzyme concentrations for both C. cardunculus and A. donax. The nearly irreversible nature of the enzyme adsorption allowed a partial recovery of the unbound biocatalyst and the polysaccharides hydrolysis by adsorbed biocatalysts. In the best condition, 89 % glucans conversion was obtained in pretreated cardoon with 4 mg/g loading of adsorbed cellulases (lower than the saturation level) and in giant reed with 13 mg/g. Notably, the residual activity of the unbound biocatalyst was sufficient to hydrolyse more than 65 and 75 % of glucans in pretreated cardoon and giant reed, respectively. The proposed method can be applied routinely to any biorefinery feedstock and both commercial and in-situ produced cocktails to minimize the enzyme dosage.

Around 600 million m3 of wastewater and 6 million tonnes of leather solid wastes, are generated annually worldwide, with a chromium content of 1 to 4 %. In this context, the thermochemical valorisation of tannery sludge (TS) by hydrothermal liquefaction (HTL) process represents a promising route both for the reduction of the material to dispose in landfill and for the production of an energy carrier. HTL process produces bio-crude from wet biomasses in a hot pressurised water environment, thus avoiding the energy-intensive drying step commonly associated to other thermochemical processes. Moreover, HTL, not aiming at the complete oxidation of the organic component, potentially avoids the oxidation of Cr in its harmful hexavalent form. In this study, a TS was investigated as solid waste for HTL carried out in a 500 mL batch reactor to obtain a bio-crude for energy purposes. Results show that, under the best operating HTL condition (350 degrees C and 10 min), the H/C ratio of biocrude was similar to that of starting biomass while the O/C ratio was about three times smaller than in the parent TS. The bio-crude yield was about 25-30 % on dry and ash-free basis, with an associated energy recovery of about 40-45 %. NMR analysis of bio-crude revealed that it is a complex mixture mainly constituted by aliphatic units. Moreover, ICP-MS, atomic absorption and UV-visible spectroscopy analyses proved that inorganic elements are mainly retrieved in the solid residue, and that Cr was present in its starting trivalent form.

Biomass pyrolysis is a complex process, quite challenging to model physically and Modern AI methods could improve its prediction and characterization. However, AI model construction requires high-quality datasets. Existing datasets in literature, usually only a few hundred records, are inadequate for robust AI applications. A first goal of the study was to make best use of the currently available body of experimental data on fixed bed non-catalytic biomass pyrolysis by comprehensively compiling available data from nearly 160 sources into a new dataset of 1137 records. Each record was carefully standardized to overcome inconsistencies in terminology and lack of uniformity among different sources. This extended dataset (including biomass properties, pyrolysis operating conditions, and bioliquid yield), integrating previous ones, is intended to promote community-based data sharing. The compiled dataset was characterized by remarkable data sparsity, due to lack of completeness of the original data. A second goal was benchmarking different regression and data imputation models to assess the predictive ability of ML applied to the collected dataset. The most accurate estimates were obtained by leveraging a subset of about 500 instances without missing values, resulting in a Mean Absolute Error (MAE) of 2.28. Application of ML to the entire dataset with imputed missing data yielded a less accurate estimate (MAE = 3.45), a feature that underlines the criticality of missing data imputation, and of the sparsity of the dataset. A third and mostly relevant goal was the critical assessment of Explainable Artificial Intelligence (XAI) techniques that come into play when ML is aimed at evaluating the importance and directional trends of selected features. XAI tools, namely Partial Dependence Plots (PDP) and SHAP, have been applied to the dataset to assess their trustworthiness to support mechanistic inference of the importance and directional trends of key biomass properties and process operational parameters on pyrolysis yields. The result of this analysis is far from satisfactory. Significant discrepancies across studies, inconsistencies among different methods and somewhat erratic trends in PDP plots reflect the challenge in achieving consistent mechanistic insights from purely data-driven approaches, suggesting the adoption of physics-informed machine learning embodying physico-chemical relationships to improved Explainable AI.

Significant efforts have been made in recent years to develop alternative energy vectors to reduce fossil fuel resource use, greenhouse gas emissions, and the release of harmful particulates. Among the alternative vectors, hydrogen (H2) is a promising option for achieving carbon neutrality because its combustion produces only water. Moreover, H2 is considered an excellent candidate for energy applications owing to its high heating value and high-octane number. H2 production can occur through dark fermentation, a biotechnological process that uses anaerobic bacteria to generate H2 and by-products (such as volatile fatty acids and CO2) from organic substrates. Specifically, the bacterium Thermotoga neapolitana efficiently converts carbohydrates into biogas, producing approximately four molecules of H2 and acetic acid per mole of consumed glucose. This study focuses on optimizing the dark fermentation process with T. neapolitana, analysing the effects of various substrates (monosaccharides and disaccharides) on bacterial growth and the production of H2 and acetic acid. The results indicated that T. neapolitana grew on all tested substrates, with fructose yielding the highest amount of H2 and mannose yielding the highest amount of acetic acid.

Hydrothermal liquefaction (HTL) appears as the most promising solution for converting wet biomass, including sewage sludge, into valuable bio-crude oil while offering advantages such as waste volume reduction, energy and resource recovery, and reduced greenhouse gas emissions. In this study, a kinetic model including four lumped species (i.e. solid residue, aqueous phase, bio-crude and gas) along with a first-order ash dissolution kinetic model was developed based on the experimental data obtained at a heating rate of similar to 8 degrees C min(-1) and temperatures of 150-370 degrees C, utilizing a 500 mL batch apparatus for HTL. While the kinetic parameters were determined from curve-fitting of data obtained at 300 degrees C and 350 degrees C, the predictive ability of the model was verified against experimental data obtained at 370 degrees C. Furthermore, ultimate analysis of lumped species at various operating conditions were used to perform elemental balances and make generalizations about the time evolution of CHNSO elements and ash distribution among various lumped species during the course of HTL. The findings of this study allow determination of both the quantity and quality of all lumped species with minimum reliance on experimental measurements. This modelling approach can be used for optimization of sewage sludge HTL process efficiency in terms of bio-crude selectivity and quality, and wastewater valorisation.