Plant gums in Pickering emulsions: A review of sources, properties, applications, and future perspectives.

Recently, there has been an increasing research interest in the development of Pickering emulsions stabilized with naturally derived biopolymeric particles. In this regard, plant gums, obtained as plant exudates or from plant seeds, are considered promising candidates for the development of non-toxic, biocompatible, biodegradable and eco-friendly Pickering stabilizers. The main objective of this review article is to provide a detailed overview and assess the latest advances in the formulation of Pickering emulsions stabilized with plant gum-based particles. The plant gum sources, types and properties are outlined. Besides, the current methodologies used in the production of plant gum particles formed solely of plant gums, or through interactions of plant gums with proteins or other polysaccharides are highlighted and discussed. Furthermore, the work compiles and assesses the innovative applications of plant gum-based Pickering emulsions in areas such as encapsulation and delivery of drugs and active agents, along with the utilization of these Pickering emulsions in the development of active packaging films, plant-based products and low-fat food formulations. The last part of the review presents potential future research trends that are expected to motivate and direct research to areas related to other novel food applications, as well as tissue engineering and environmental applications.

A Microporous Multi-Cage Metal-Organic Framework for an Effective One-Step Separation of Branched Alkanes Feeds.

The improvement of the Total Isomerization Process (TIP) for the production of high-quality gasoline with the ultimate goal of reaching a Research Octane Number (RON) higher than 92 requires the use of specific sorbents to separate pentane and hexane isomers into classes of linear, mono- and di-branched isomers. Herein we report the design of a new multi-cage microporous Fe(III)-MOF (referred to as MIP-214, MIP stands for materials of the Institute of Porous Materials of Paris) with a flu-e topology, incorporating an asymmetric heterofunctional ditopic ligand, 4-pyrazolecarboxylic acid, that exhibits an appropriate microporous structure for a thermodynamic-controlled separation of hydrocarbon isomers. This MOF produced via a direct, scalable, and mild synthesis route was proven to encompass a unique separation of C5/C6 isomers by classes of low RON over high RON alkanes with a sorption hierarchy: (n-hexane≫n-pentane≈2-methylpentane>3-methylpentane)low RON≫(2,3-dimethylbutane≈i-pentane≈2,2-dimethylbutane)high RON following the adsorption enthalpy sequence. We reveal for the first time that a single sorbent can efficiently separate such a complex mixture of high RON di-branched hexane and mono-branched pentane isomers from their low RON counterparts, which is a major achievement reported so far.

Disclosing the potential of Cupressus leylandii A.B. Jacks & Dallim, Eucalyptus globulus Labill., Aloysia citrodora Paláu, and Melissa officinalis L. hydrosols as eco-friendly antimicrobial agents.

Antimicrobial resistance is a major global health concern, threatening the effective prevention and treatment of infections caused by microorganisms. These factors boosted the study of safe and green alternatives, with hydrosols, the by-products of essential oils extraction, emerging as promising natural antimicrobial agents. In this context, four hydrosols obtained from Cupressus leylandii A.B. Jacks & Dallim, Eucalyptus globulus Labill., Aloysia citrodora Paláu and Melissa officinalis L. were studied. Their chemical composition comprises neral, geranial, 1,8-cineole, terpinen-4-ol, and oplopanonyl acetate, compounds with recognised antimicrobial activity. Concerning antimicrobial activity, significant differences were found using different hydrosol concentrations (10-20% v/v) in comparison to a control (without hydrosol), showing the potential of the tested hydrosols to inhibit the microbial growth of Escherichia coli, Staphylococcus aureus, and Candida albicans. A. citrodora hydrosol was the most effective one, inhibiting 90% of E. coli growth and 80% of C. albicans growth, for both hydrosol concentrations (p < 0.0001). With hydrosol concentration increase, it was possible to observe an improved antimicrobial activity with significant reductions (p < 0.0001). The findings of this work indicate the viability of reusing and valuing the hydrosols, encouraging the development of green applications for different fields (e.g., food, agriculture, pharmaceuticals, and cosmetics).

Sugarcane Light-Colored Lignin: A Renewable Resource for Sustainable Beauty.

Lignin has emerged as a promising eco-friendly multifunctional ingredient for cosmetic applications, due to its ability to protect against ultraviolet radiation and its antioxidant and antimicrobial properties. However, its typical dark color and low water solubility limit its application in cosmetics. This study presents a simple process for obtaining light-colored lignin (LCLig) from sugarcane bagasse (SCB) alkaline black liquor, involving an oxidation treatment with hydrogen peroxide, followed by precipitation with sulfuric acid. The physico-chemical characterization, antioxidant and emulsifying potential of LCLig, and determination of its safety and stability in an oil-in-water emulsion were performed. A high-purity lignin (81.6%) with improved water solubility was obtained, as a result of the balance between the total aromatic phenolic units and the carboxylic acids. In addition, the antioxidant and emulsifying capacities of the obtained LCLig were demonstrated. The color reduction treatment did not compromise the safety of lignin for topical cosmetic applications. The emulsion was stable in terms of organoleptic properties (color, pH, and viscosity) and antioxidant activity over 3 months at 4, 25, and 40 °C.

A framework for predicting odor threshold values of perfumes by scientific machine learning and transfer learning.

Knowledge of odor thresholds is very important for the perfume industry. Due to the difficulty associated with measuring odor thresholds, empirical models capable of estimating these values can be an invaluable contribution to the field. This work developed a framework based on scientific machine learning strategies. A transfer learning-based strategy was devised, where information from a graph convolutional network predicting semantic odor descriptors was used as input data for the feedforward neural network responsible for estimating odor thresholds for chemical substances based on their molecular structures. The predictive performance of this model was compared to a benchmark odor threshold prediction model based on molecular structures that did not utilize transfer learning. Furthermore, the prediction was compared to a correlation previously proposed in the literature and a dummy regressor. Results demonstrated that the transfer learning-based strategy displayed a better predictive performance, suggesting this technique can be useful for predicting odor thresholds.

An Efficient Strategy for Electroreduction Reactor Outlet Fractioning into Valuable Products.

In this work, two industrial dual-step pressure swing adsorption (PSA) processes were designed and simulated to obtain high-purity methane, CO2, and syngas from a gas effluent of a CO2 electroreduction reactor using different design configurations. Among the set of zeolites that was investigated using Monte Carlo and molecular dynamics simulations, NaX and MFI were the ones selected. The dual-PSA process for case study 1 is only capable of achieving a 90.5% methane purity with a 95.2% recovery. As for case study 2, methane is obtained with a 97.5% purity and 95.3% recovery. Both case studies can produce CO2 with high purity and recovery (>97 and 95%, respectively) and syngas with a H2/CO ratio above 4. Although case study 2 allows methane to be used as domestic gas, a much higher value for its energy consumption is observed compared to case study 1 (64.9 vs 29.8 W h molCH4-1).

Metaheuristic Framework for Material Screening and Operating Optimization of Adsorption-Based Heat Pumps.

The current methods applied to material screening for adsorption-based heat pumps are based on a fixed set of temperatures or their independent variation, providing a limited, insufficient, and unpractical evaluation of different adsorbents. This work proposes a novel strategy for the simultaneous optimization and material screening in the design of adsorption heat pumps by implementing a meta-heuristic approach, particle swarm optimization (PSO). The proposed framework can effectively evaluate variable and broad operation temperature intervals to search for viable zones of operation for multiple adsorbents at once. The criteria for selecting the adequate material were the maximum performance and the minimum heat supply cost, which were considered the objective functions of the PSO algorithm. First, the performance was assessed individually, followed by a single-objective approximation of the multi-objective problem. Next, a multi-objective approach was also adopted. With the results generated during the optimization, it was possible to find which adsorbents and temperature sets were the most suitable according to the main objective of the operation. The Fisher-Snedecor test was applied to expand the results obtained during PSO application and a feasible operating region built around the optima, enabling the arrangement of close-to-optima data into practical design and control tools. This approach allowed for a fast and intuitive evaluation of multiple design and operation variables.

Carbon dioxide separation and capture by adsorption: a review.

Rising adverse impact of climate change caused by anthropogenic activities is calling for advanced methods to reduce carbon dioxide emissions. Here, we review adsorption technologies for carbon dioxide capture with focus on materials, techniques, and processes, additive manufacturing, direct air capture, machine learning, life cycle assessment, commercialization and scale-up.

Generating Flavor Molecules Using Scientific Machine Learning.

Flavor is an essential component in the development of numerous products in the market. The increasing consumption of processed and fast food and healthy packaged food has upraised the investment in new flavoring agents and consequently in molecules with flavoring properties. In this context, this work brings up a scientific machine learning (SciML) approach to address this product engineering need. SciML in computational chemistry has opened paths in the compound's property prediction without requiring synthesis. This work proposes a novel framework of deep generative models within this context to design new flavor molecules. Through the analysis and study of the molecules obtained from the generative model training, it was possible to conclude that even though the generative model designs the molecules through random sampling of actions, it can find molecules that are already used in the food industry, not necessarily as a flavoring agent, or in other industrial sectors. Hence, this corroborates the potential of the proposed methodology for the prospecting of molecules to be applied in the flavor industry.

A Reinforcement Learning Framework to Discover Natural Flavor Molecules.

Flavor is the focal point in the flavor industry, which follows social tendencies and behaviors. The research and development of new flavoring agents and molecules are essential in this field. However, the development of natural flavors plays a critical role in modern society. Considering this, the present work proposes a novel framework based on scientific machine learning to undertake an emerging problem in flavor engineering and industry. It proposes a combining system composed of generative and reinforcement learning models. Therefore, this work brings an innovative methodology to design new flavor molecules. The molecules were evaluated regarding synthetic accessibility, the number of atoms, and the likeness to a natural or pseudo-natural product. This work brings as contributions the implementation of a web scraper code to sample a flavors database and the integration of two scientific machine learning techniques in a complex system as a framework. The implementation of the complex system instead of the generative model by itself obtained 10% more molecules within the optimal results. The designed molecules obtained as an output of the reinforcement learning model's generation were assessed regarding their existence or not in the market and whether they are already used in the flavor industry or not. Thus, we corroborated the potentiality of the framework presented for the search of molecules to be used in the development of flavor-based products.

The potential of almonds, hazelnuts, and walnuts SFE-CO2 extracts as sources of bread flavouring ingredients.

Nuts have been part of the human diet since our early ancestors, and their use goes beyond nutritional purposes, for example, as aromatic sources for dairy products. This work explores the potential of almond (Prunus dulcis (Mill.) DA Webb), hazelnut (Corylus avellana L.), and walnut (Juglans regia L.) extracts as sources of food flavouring agents, suggesting a new added-value application for lower quality or excess production fruits. The extracts were obtained by supercritical fluid extraction with carbon dioxide and characterized by: quantification of the volatile fraction by HS-SPME GC-MS; sensory perception and description; and cytotoxicity against Vero cells. All extracts revealed potential as flavouring ingredients due to terpene abundance. No significant differences were observed for the minimal sensory perception, in which the odour threshold values ranged from 8.3 × 10-4 to 6.9 × 10-3 µg·mL-1 for walnuts and almonds extracts, respectively. In contrast, the cytotoxic potential differed significantly among the extracts, and P. dulcis extract presented lower cytotoxicity. Notes as woody, fresh, and green were identified in the volatile intensifiers obtained from the P. dulcis extract. Thus, almond extract was identified as the most promising ingredient to increase the sensory value of food products, namely bread. This potential was verified by an increase in the odour perception of bread after adding 4 µL of extract to each 100 g of bread dough. The quantified eucalyptol and d-limonene terpenes - found in the P. dulcis extract - have improved the release of the pleasant and natural volatile compounds from bread crust and crumb compared to the control bread chemical and sensory profiles.

Novel Framework for Simulated Moving Bed Reactor Optimization Based on Deep Neural Network Models and Metaheuristic Optimizers: An Approach with Optimality Guarantee.

Model-based optimization of simulated moving bed reactors (SMBRs) requires efficient solvers and significant computational power. Over the past years, surrogate models have been considered for such computationally demanding optimization problems. In this sense, artificial neural networks-ANNs-have found applications for modeling the simulated moving bed (SMB) unit but not yet been reported for the reactive SMB (SMBR). Despite ANNs' high accuracy, it is essential to assess its capacity to represent the optimization landscape well. However, a consistent method for optimality assessment using surrogate models is still an open issue in the literature. As such, two main contributions can be highlighted: the SMBR optimization based on deep recurrent neural networks (DRNNs) and the characterization of the feasible operation region. This is done by recycling the data points from a metaheuristic technique-optimality assessment. The results demonstrate that the DRNN-based optimization can address such complex optimization while meeting optimality.

Microwave-Assisted Lignin Wet Peroxide Oxidation to C4 Dicarboxylic Acids.

Innovative methodologies, such as microwave-assisted reaction, can help to valorize lignin with higher productivity and better energy efficiency. In this work, microwave heating was tested in the wet peroxide oxidation of three lignins (Indulin AT, Lignol, and Eucalyptus globulus lignins) as a novel methodology to obtain C4 dicarboxylic acids. The effect of temperature, time, and catalyst type (TS-1 or Fe-TS1) was evaluated in the production of these acids. The TS-1 catalyst improved succinic acid yield, achieving up to 9.4 wt % for Lignol lignin. Moreover, the microwave heating specifically enhanced Lignol conversion to malic acid (34 wt %), even without catalyst, showing to be an attractive path for the future valorization of organosolv lignins. Overall, compared to conventional heating, microwave heating originated a rapid lignin conversion. Nevertheless, for prolonged times, conventional heating led to better results for some target products, e.g., malic and succinic acids.

On the Oxidative Valorization of Lignin to High-Value Chemicals: A Critical Review of Opportunities and Challenges.

The efficient valorization of lignin is crucial if we are to replace current petroleum-based feedstock and establish more sustainable and competitive lignocellulosic biorefineries. Pulp and paper mills and second-generation biorefineries produce large quantities of low-value technical lignin as a by-product, which is often combusted on-site for energy recovery. This Review focuses on the conversion of technical lignins by oxidative depolymerization employing heterogeneous catalysts. It scrutinizes the current literature describing the use of various heterogeneous catalysts in the oxidative depolymerization of lignin and includes a comparison of the methods, catalyst loadings, reaction media, and types of catalyst applied, as well as the reaction products and yields. Furthermore, current techniques for the determination of product yields and product recovery are discussed. Finally, challenges and suggestions for future approaches are outlined.

Separation of Branched Alkanes Feeds by a Synergistic Action of Zeolite and Metal-Organic Framework.

Zeolites and metal-organic frameworks (MOFs) are considered as "competitors" for new separation processes. The production of high-quality gasoline is currently achieved through the total isomerization process that separates pentane and hexane isomers while not reaching the ultimate goal of a research octane number (RON) higher than 92. This work demonstrates how a synergistic action of the zeolite 5A and the MIL-160(Al) MOF leads to a novel adsorptive process for octane upgrading of gasoline through an efficient separation of isomers. This innovative mixed-bed adsorbent strategy encompasses a thermodynamically driven separation of hexane isomers according to the degree of branching by MIL-160(Al) coupled to a steric rejection of linear isomers by the molecular sieve zeolite 5A. Their adsorptive separation ability is further evaluated under real conditions by sorption breakthrough and continuous cyclic experiments with a mixed bed of shaped adsorbents. Remarkably, at the industrially relevant temperature of 423 K, an ideal sorption hierarchy of low RON over high RON alkanes is achieved, i.e., n-hexane ≫ n-pentane ≫ 2-methylpentane > 3-methylpentane ⋙ 2,3-dimethylbutane > isopentane ≈ 2,2-dimethylbutane, together with a productivity of 1.14 mol dm-3 and a high RON of 92, which is a leap-forward compared with existing processes.

Hardwood and softwood lignins from sulfite liquors: Structural characterization and valorization through depolymerization.

This work aims to evaluate the structural characteristics and study the oxidative depolymerization of lignins obtained from hardwood and softwood sulfite liquors. Lignins were obtained after ultrafiltration and freeze-drying of the sulfite liquors and characterized based on inorganic content, nitrobenzene oxidation, 13C NMR, and molecular weight determination. The structural characteristics achieved allow evaluating the potential of each lignin through oxidative depolymerization to produce added-value phenolic monomers. Hardwood and softwood lignins were submitted to alkaline oxidation with oxygen and the reaction conditions optimized to obtain a final oxidation mixture with the maximum yield of phenolic monomers. Through oxidation with O2, hardwood lignin generates mostly syringaldehyde while lignin from softwood biomass mainly produces vanillin; moreover, a lower reaction time and the interruption of O2 admission avoid the degradation of the oxidation products in the final mixture for both lignins, more evidenced to hardwood lignin due to its higher reactivity. From the results, it is possible to conclude that a phenolic aldehyde-rich oxidation mixture could be obtained, confirming the viability of lignin as raw material to produce added-value products as vanillin and syringaldehyde.

Chemical and organoleptic properties of bread enriched with Rosmarinus officinalis L.: The potential of natural extracts obtained through green extraction methodologies as food ingredients.

The potential of R. officinalis L. (RO) extracts as a source of aromas was accessed by hydrodistillation (HD) and supercritical fluid extraction using carbon dioxide (SFE-CO2), followed by a series of analysis: quantification by GC-MS, sensory perception and description, and cytotoxicity against Vero cells. The extracts shown abundancy of α-pinene, eucalyptol, S-verbenone and camphor, contributing for the green, fresh, citric, and woody as main sensory notes. The odour threshold (ODT) value (less than 3.0 × 10-3 µg·mL-1) and the cytotoxic potential (ca. 220 µg∙mL-1) defined the concentration range for food application. The most promising extract was added to bread doughs and the final volatile profile was characterised by GC-MS through HS-SPME over time. Among the 34 compounds found, furfural showed an evident contribution in the bread crust aroma, which persisted over four hours of storage, contributing to a pleasant bread fragrance according to the evaluators. This study aims to represent a stepping stone for the use of natural aromas as ingredients for the development of innovative food products.

Obtaining Aromatic Extracts from Portuguese Thymus mastichina L. by Hydrodistillation and Supercritical Fluid Extraction with CO2 as Potential Flavouring Additives for Food Applications.

Humans often respond to sensory impulses provided by aromas, and current trends have generated interest in natural sources of fragrances rather than the commonly used synthetic additives. For the first time, the resulting aroma of a selected culture of Thymus mastichina L. was studied as a potential food ingredient. In this context, dried (DR) and fresh (FR) samples were submitted to carbon dioxide (CO2) supercritical extraction (SFE) and hydrodistillation (HD) methods. The extracts were characterised according to their volatile composition by GC-MS, cytotoxicity against a non-tumour cell culture, and sensory attributes (odour threshold and olfactive descriptors). The most abundant aromas were quantified, and the analysis performed by GC-MS revealed an abundance of terpenoids such as thymol chemotype, followed by the precursors α-terpinene and p-cymene. DR and FR extracts (EX) obtained from SFE-CO2 show the highest content of thymol, achieving 52.7% and 72.5% of the isolated volatile fraction. The DR essential oil (EO) contained the highest amount of terpenoids, but it was also the most cytotoxic extract. In contrast, SFE-CO2 products showed the lowest cytotoxic potential. Regarding FR-OE, it had the lowest extraction yield and composition in aroma volatiles. Additionally, all samples were described as having green, fresh and floral sensory notes, with no significant statistical differences regarding the odour detection threshold (ODT) values. Finally, FR-EX of T. mastichina obtained by SFE-CO2 presented the most promising results regarding food application.

Novel Adsorption-Reaction Process for Biomethane Purification/Production and Renewable Energy Storage.

This work proposes an innovative method for the simultaneous upgrading of biogas streams and valorization of the separated CO2, through its conversion to renewable methane. To this end, two sorptive reactors were filled with a layered bed containing a CO2 sorbent (K-promoted hydrotalcite) and a methanation catalyst (Ru/Al2O3). The continuous cyclic operation of the parallel sorptive reactors was carried out by alternately feeding a biogas stream (CO2/CH4 mixture) or H2. The CO2/CH4 mixture is fed to the sorptive reactor during the sorption stage, with CO2 being captured by the sorbent and CH4 exiting as a purified stream (i.e., as biomethane). During the reactive regeneration stage, the inlet stream is switched to pure H2, which reacts with the previously captured CO2 at the methanation catalyst active sites thus producing additional methane. For continuous operation, the two sorptive reactors were operated 180° out of phase and cyclic steady-state could be reached after ca. five cycles. The performance of the cyclic sorptive-reactive unit was assessed through a parametric study to evaluate the influence of different operating conditions, namely, the inlet flow rate and CO2 content during the sorption stage, the hydrogen inlet flow rate during the reactive regeneration stage, the stage duration, and temperature. The inclusion of an inert purge after the reactive regeneration stage was also tested. The performance of the unit was compared to the case of direct hydrogenation of biogas, and conclusions were drawn regarding future optimization, with special attention being given to CH4 productivity and purity. During the parametric study, a compromise between these process indicators, i.e., a productivity of 1.63 molCH4 kgcat -1 h-1 with 70.3% of CH4 purity, was obtained at 350 °C. However, biomethane purities above 80% were easily achieved, though at the expense of methane productivities.