Sustainable plant polyesters as substrates for optical gas sensors

Impact of the Cationic Moiety of Ionic Liquids on Chemoselective Artificial Olfaction

Ionogels and derived materials are assemblies of polymers and ionic liquids characterized by high stability and ionic conductivity, making them interesting choices as gas sensors. In this work, we assessed the effect of the ionic liquid moiety to generate ionogels and hybrid gels as electrical and optical gas sensors. Six ionic liquids consisting of a constant anion (chloride) and distinct cationic head groups were used to generate ionogels and hybrid gels and further tested as gas sensors in customized electronic nose devices. In general, ionogel-based sensors yielded higher classification accuracies of standard volatile organic compounds when compared to hybrid material-based sensors. In addition, the high chemical diversity of ionic liquids is further translated to a high functional diversity in analyte molecular recognition and sensing.

Purification of archetypal soybean root suberin mostly comprising alka(e)noic acids using an ionic liquid catalyst

Soybean (Glycine max) is an increasingly relevant crop due to its economic importance and also a model plant for the study of root symbiotic associations with nodule forming rhizobia. Plant polyesters mediate plant-microbe interactions with both pathogenic and beneficial microbes; suberin has been hypothesized to play a key role during the early steps of rhizobia attachment to the root. The downside is that suberin chemistry in soybean root is still scarcely studied. This study addresses this outstanding question by reporting a straightforward workflow for a speedy purification of suberin from soybean root and for its subsequent detailed chemical analysis. To purify suberin, cholinium hexanoate (an ionic liquid) was used as the catalyst. The ensuing suberin is highly esterified as observed by a precise Nuclear Magnetic Resonance quantification of each ester type, discriminating between primary and acylglycerol esters. Moreover, the composing hydrolysable monomers detected through GC-MS revealed that hexadecanoic acid is the most abundant monomer, similar to that reported before by others. Overall, this study highlights the adequacy of the ionic liquid catalyst for the isolation of suberin from soybean roots, where the polymer natural abundance is low, and builds new knowledge on the specificities of its chemistry; essential to better understand the biological roles of suberin in roots.

Nanoscale Events on Cyanobiphenyl-Based Self-Assembled Droplets Triggered by Gas Analytes

Liquid crystals (LCs) are prime examples of dynamic supramolecular soft materials. Their autonomous self-assembly at the nanoscale level and the further nanoscale events that give rise to unique stimuli-responsive properties have been exploited for sensing purposes. One of the key features to employ LCs as sensing materials derives from the fine-tuning between stability and dynamics. This challenging task was addressed in this work by studying the effect of the alkyl chain length of cyanobiphenyl LCs on the molecular self-assembled compartments organized in the presence of ionic liquid molecules and gelatin. The resulting multicompartment nematic and smectic gels were further used as volatile organic compound chemical sensors. The LC structures undergo a dynamic sequence of phase transitions, depending on the nature of the LC component, yielding a variety of optical signals, which serve as optical fingerprints. In particular, the materials incorporating smectic compartments resulted in unexpected and rich optical textures that have not been reported previously. Their sensing capability was tested in an in-house-assembled electronic nose and further assessed via signal collection and machine-learning algorithms based on support vector machines, which classified 12 different gas analytes with high accuracy scores. Our work expands the knowledge on controlling LC self-assembly to yield fast and autonomous accurate chemical-sensing systems based on the combination of complex nanoscale sensing events with artificial intelligence tools.

Quantification of Structure-Property Relationships for Plant Polyesters Reveals Suberin and Cutin Idiosyncrasies

Polyesters, as they exist in planta, are promising materials with which to begin the development of "green" replacements. Cutin and suberin, polyesters found ubiquitously in plants, are prime candidates. Samples enriched for plant polyesters, and in which their native backbones were largely preserved, were studied to identify "natural" structural features; features that influence critical physical properties. Quantitative nuclear magnetic resonance (NMR), differential scanning calorimetry (DSC), and X-ray scattering methods were used to quantify structure-property relationships in these polymeric materials. The degree of esterification, namely, the presence of acylglycerol linkages in suberin and of secondary esters in cutin, and the existence of mid-chain epoxide groups defining the packing of the aliphatic chains were observed. This packing determines polymer crystallinity, the resulting crystal structure, and the melting temperature. To evaluate the strength of this rule, tomato cutin from the same genotype, studying wild-type plants and two well-characterized mutants, was analyzed. The results show that cutin's material properties are influenced by the amount of unbound aliphatic hydroxyl groups and by the length of the aliphatic chain. Collectively, the acquired data can be used as a tool to guide the selection of plant polyesters with precise structural features, and hence physicochemical properties.