Contribution Of Functional Groups Research Articles

Assessing the complexation of dissolved organic matter with heavy metals (Cu2+, Pb2+) in leachate from an old Japanese landfill site using fluorescence quenching.

Dissolved organic matter (DOM) in landfill leachate impacts the toxicity, bioavailability, and migration of heavy metals. The present study investigated the complexation of heavy metals (Cu2+ and Pb2+) with DOM from two landfill leachate samples, representing an old landfill site containing incineration residues and incombustible waste. The logarithms of the stability constant (log KM) and percentage of complexed fluorophores were calculated using both the Ryan-Weber non-linear model and the modified Stern-Volmer model, yielding good agreement. The log KM values (at pH = 6.0 ± 0.1) calculated using both methods for the two sampling points were 5.02-5.13 and 4.85-5.11 for Cu2+-DOM complexation, and 5.01-5.13 and 4.46-4.87 for Pb2+-DOM complexation, respectively. Log KM was slightly higher for binding of DOM with Cu2+ than Pb2+, and the quenching degree was stronger for complexation with Cu2+ (28.5-30.6% and 38.0-45.9%) than Pb2+ (6.5-7.1% and 10.0-15.4%) in both leachate samples. While log KM values were similar, differences in the contributions of functional groups and molecular composition led to varying degrees of quenching. This study reveals the potential for heavy metal binding by DOM in landfill leachate with a unique solid waste composition and emphasizes variations in fluorescence quenching between Cu2+ and Pb2+ despite similar log KM levels. These findings may be useful for assessing heavy metal behavior in landfill leachate and its impacts on the surrounding environment.

How Humans Run Faster: The Neuromechanical Contributions of Functional Muscle Groups to Running at Different Speeds.

How the neuromechanics of the lower limb functional muscle groups change with running speed remains to be fully elucidated, with implications for our understanding of human locomotion, conditioning, and injury prevention. This study compared the neuromechanics (ground reaction and joint kinetics, kinematics and muscle activity) of middle-distance athletes running on an instrumented treadmill at six wide-ranging speeds (2.78-8.33 m·s-1). Ground reaction forces and kinematics were analyzed using inverse dynamics to calculate flexor and extensor joint torques, and positive and negative work done by these torques. Contributions of each functional muscle group to the total positive and negative work done by the limb during stance, swing, and the whole stride were quantified. During stance, the ankle plantar flexors were the major energy generator and absorber (>60%) at all speeds, but their contribution to whole stride energy generation and absorption declined with speed. Positive work by the hip extensors rose superlinearly with speed during stance (3-fold) and especially during swing (12-fold), becoming the biggest energy generator across the whole stride at >5 m·s-1. Knee flexor and extensor negative work also rose superlinearly with speed during swing, with the knee flexors becoming the greatest energy absorber over the whole stride at >7.22 m·s-1. Across speeds, plantar flexor peak moment and positive work accounted for 97% and 96% of the variance in step length, and swing hip extension peak moment and positive work accounted for 98% and 99% of the variance in step frequency. There were pronounced speed, phase (stance/swing), and work (positive/negative) dependent contributions of the different functional muscle groups during running, with extensive implications for conditioning and injury prevention.

Species richness and dominant functional groups enhance aboveground biomass, with no effect on belowground biomass in Qinghai-Tibet Plateau's grasslands

Understanding the role of plant diversity in maintaining grassland ecosystem functioning is of great importance in ecological research. Despite decades of research, ecologists have struggled to understand the biodiversity-ecosystem functioning relationships and how the dominance of plant functional groups impacts ecosystem function. In attempting to understand (i) the temporal patterns of above- and below-ground biomass (AGB and BGB) and species richness, (ii) whether species richness is consistently associated with AGB and BGB, and (iii) the relative contributions of plant functional groups (forb, grass, legume, and sedge) in stabilizing ecosystem function, we used biomass productivity data of meadow steppe and alpine meadow in the Qinghai-Tibet Plateau (QTP) for the period 2015–2019. Our results show that AGB for both grasslands increased, but BGB stayed steady over 5 years. The rising tendency of AGB was caused by the upward trend of AGB in forbs and grasses, which are the dominant functional groups in QTP, stressing the importance of dominant functional groups to ecosystem functioning. The biodiversity-ecosystem functioning relationships were significantly positive for AGB, stable for BGB, and negative for the BGB:AGB ratio, which highlights the crucial role of higher species richness in ecosystem functioning. Significant differences in mean species richness among sites (9–19 species in meadow steppe and 8–22 species in alpine meadow) highlight the varying levels of species diversity across sites in the QTP. While 42% of the sites showed stable species richness, the reported increasing trends in species richness at 58% of the sites indicate the potential for ecological changes or processes in these areas. AGB in both grasslands increased, while BGB remained stable with increasing precipitation. The top soil layer (0–10 cm) dominated the observed BGB in both grasslands, as abundant nutrients in the top layer provide favorable conditions for root proliferation. In meadow steppe, AGB formed an isometric relationship with BGB, indicating that AGB increased with BGB. This study concludes that species richness influenced ecosystem functioning, and forbs and grasses dominated biomass productivity, of which the topsoil layer contributed three-quarters of BGB. Our study (i) provides empirical evidence of stable to increasing species richness in both grasslands over 5 years, and (ii) highlights the role of greater species richness in enhancing ecosystem functioning. These findings serve as a scientific reference for policymaking regarding ecosystem stability.

Variation in the timing and duration of autumn leaf phenology among temperate deciduous trees, native shrubs and non-native shrubs.

The timing and duration of autumn leaf phenology marks important transitions in temperate deciduous forests, such as, start of senescence, declining productivity and changing nutrient cycling. Phenological research on temperate deciduous forests typically focuses on upper canopy trees, overlooking the contribution of other plant functional groups like shrubs. Yet shrubs tend to remain green longer than trees, while non-native shrubs, in particular, tend to exhibit an extended growing season that confers a competitive advantage over native shrubs. We monitored leaf senescence and leaf fall (2017-2020) of trees and shrubs (native and non-native) in an urban woodland fragment in Wisconsin, USA. Our findings revealed that, the start of leaf senescence did not differ significantly between vegetation groups, but leaf fall started (DOY 273) two weeks later in shrubs. Non-native shrubs exhibited a considerably delayed start (DOY 262) and end of leaf senescence (DOY 300), with leaf-fall ending (DOY 315) nearly four weeks later than native shrubs and trees. Overall, the duration of the autumn phenological season was longer for non-native shrubs than either native shrubs or trees. Comparison of the timing of spring phenophases with the start and end of leaf senescence revealed that when spring phenology in trees starts later in the season senescence also starts later and ends earlier. The opposite pattern was observed in native shrubs. In conclusion, understanding the contributions of plant functional groups to overall forest phenology requires future investigation to ensure accurate predictions of future ecosystem productivity and help address discrepancies with remote sensing phenometrics.

Exploration of rice husk ash as a green corrosion inhibitor immersed in NH4Cl 7.5 % solution

The study reports the development of a liquid smoke solution of rice husk ash (RHA) as a green corrosion inhibitor in NH4Cl solution in approaching corrosion protection for refinery facilities. The recent utilization of RHA has a partial solution to address the possible chemical to form a filming layer to disconnect bare metal and their environment. This work prepared the RHA solution by condensing the RHA vapor before adding it to various concentrations. The corrosion test of potentiodynamic and electrochemicals intends to discover the inhibitor's corrosion resistance before examining the electronic transition corresponding to the contribution of several functional groups using Ultraviolet Visible (UV–Vis) and Fourier-Transform Infrared Spectroscopy (FTIR). Surface evaluation intends to unveil the nature of the corrosion by utilizing the Scanning Electronic and Atomic Force Microscope. The corrosion test result shows the depression of corrosion rate to 0.120 mmpy with high efficiency beyond 96 % in the addition of 7.5 ppm RHA inhibitor. The greater Nyquist semicircle diameter at high concentrations increases the adsorption of the RHA on the surface of C1018. The electronic transition of n–π* and π –π* shows an extensive contribution of CC, CO, and –OH based on the UV–Vis and FTIR test. The formation of a complex compound of Fe-(NH4Cl-RHA)n blocks the corrosion active sites to reduce the corrosion. This study paves the way for using RHA as an organic compound under NH4Cl conditions, such as in a refinery process facility.

Green synthesis and characterization of Ag nanoparticles using fresh and dry Portulaca Oleracea leaf extracts: Enhancing light reflectivity properties of ITO glass

AbstractSilver (Ag) nanoparticles (NPs) are perceiving remarkable progress during the past few periods due to its exclusive properties in many applications. Recently, green synthesis method of NPs is racing against traditional chemical and physical methods by avoiding the use of many toxic chemicals, and expensive devices. Accordingly, in this study, dry and fresh Portulaca‐oleracea L. leaf extract has been employed for producing AgNPs as a reducing, capping and stabilizing agents. This process is simple, eco‐friendly and green. UV–vis spectra showed the formation of AgNPs represented by the change of a colorless liquid to brownish solution. The crystallinity of the AgNPs, was confirmed by X‐ray diffraction (XRD). The contribution of the available functional groups of the leaf extract in the reduction and capping process of NPs was demonstrated using Fourier transform infrared spectroscopy (FTIR). This study showed that fresh Portulaca‐oleracea L. leaf extract provides better NPs in terms of stability, purity, degree of crystallinity and spherical shape. The biosynthesized AgNPs from both procedures were coated on the indium tin oxide (ITO) glass substrates to enhance the reflectivity property. It has been shown that the utilized AgNPs, from fresh Portulaca‐oleracea L. extract, has smaller size and negligeable agglomeration, consequently lower light transmittance.

Ecology of aerobic anoxygenic phototrophs on a fine-scale taxonomic resolution in Adriatic Sea unravelled by unsupervised neural network

BackgroundAerobic anoxygenic phototrophs are metabolically highly active, diverse and widespread polyphyletic members of bacterioplankton whose photoheterotrophic capabilities shifted the paradigm about simplicity of the microbial food chain. Despite their considerable contribution to the transformation of organic matter in marine environments, relatively little is still known about their community structure and ecology at fine-scale taxonomic resolution. Up to date, there is no comprehensive (i.e. qualitative and quantitative) analysis of their community composition in the Adriatic Sea.ResultsAnalysis was based on pufM gene metabarcoding and quantitative FISH-IR approach with the use of artificial neural network. Significant seasonality was observed with regards to absolute abundances (maximum average abundances in spring 2.136 ± 0.081 × 104 cells mL−1, minimum in summer 0.86 × 104 cells mL−1), FISH-IR groups (Roseobacter clade prevalent in autumn, other Alpha- and Gammaproteobacteria in summer) and pufM sequencing data agglomerated at genus-level. FISH-IR results revealed heterogeneity with the highest average relative contribution of AAPs assigned to Roseobacter clade (37.66%), followed by Gammaproteobacteria (35.25%) and general Alphaproteobacteria (31.15%). Community composition obtained via pufM sequencing was dominated by Gammaproteobacteria clade NOR5/OM60, specifically genus Luminiphilus, with numerous rare genera present in relative abundances below 1%. The use of artificial neural network connected this community to biotic (heterotrophic bacteria, HNA and LNA bacteria, Synechococcus, Prochlorococcus, picoeukaryotes, heterotrophic nanoflagellates, bacterial production) and abiotic environmental factors (temperature, salinity, chlorophyll a and nitrate, nitrite, ammonia, total nitrogen, silicate, and orthophosphate concentration). A type of neural network, neural gas analysis at order-, genus- and ASV-level, resulted in five distinct best matching units (representing particular environments) and revealed that high diversity was generally independent of temperature, salinity, and trophic status of the environment, indicating a potentially dissimilar behaviour of aerobic anoxygenic phototrophs compared to the general bacterioplankton.ConclusionThis research represents the first comprehensive analysis of aerobic anoxygenic phototrophs in the Adriatic Sea on a trophic gradient during a year-round period. This study is also one of the first reports of their genus-level ecology linked to biotic and abiotic environmental factors revealed by unsupervised neural network algorithm, paving the way for further research of substantial contribution of this important bacterial functional group to marine ecosystems.

Efficient Electrosynthesis of Hydrogen Peroxide Using Oxygen-Doped Porous Carbon Catalysts at Industrial Current Densities.

Metal-free carbon catalysts (MFCCs) are one of the commonly used catalysts for electrocatalytic two-electron oxygen reduction (2e- ORR) synthesis of hydrogen peroxide (H2O2). Oxygen doping is an effective means to improve the performance of MFCCs, but the performance of oxygen-doped carbon catalysts is still not high enough, and the contribution of different oxygen functional groups (OFGs) to the catalytic performance is still inconclusive. In this paper, carbon-based catalysts with different oxygen contents and ratios of OFGs were prepared, and the high 2e- ORR activity of COOH + C-OH was demonstrated by combining the results of experiments and theoretical calculations. The prepared oxygen-doped carbon-based catalyst C-0.1M80 achieved an onset potential of 0.795 V (vs RHE), a selectivity of up to 98.2% (0.6 V vs RHE), and a H2O2 oxidation current of 1.33 mA cm-2 (0.5 V vs RHE) in a rotating ring-disk electrode test (0.1 M KOH solution), which was an outstanding performance in MFCCs. In a solid electrolyte flow cell, C-0.1M80 achieved a Faraday efficiency of 97.5% at 200 mA cm-2 with a corresponding H2O2 production rate of 123.7 mg cm-2 h-1. In addition, a flow cell stability test was performed at an industrial current density (100 mA cm-2) with an astounding 200 h of uninterrupted operation, also achieving an outstanding average Faradaic efficiency (95.8%).

Species contributions to ecosystem stability change with disturbance type

Simultaneous exposure to multiple stressors complicates the challenge of predicting ecological responses to global environmental change. Here, we show that the contributions of individual species and functional groups to the overall stability of ecosystems can be modified by the presence of different stressors, both individually and in combination. By disturbing natural rocky shore communities with nutrients and sediments and simulating extinction of predatory whelks and grazers, we also found that consumers can simultaneously stabilise and destabilise communities along different stability dimensions, irrespective of their trophic position. Our results suggest that our experimental disturbances influenced consumer contributions to stability indirectly by modifying the interactions between consumers and macroalgae in different ways. These findings merit further exploration in different systems exposed to a range of different stressors to better understand how perturbations of different kinds can modify the multifaceted contributions of species to the overall stability of ecosystems.

Triboelectric Charging Properties of the Functional Groups of Common Pharmaceutical Materials Using Density Functional Theory Calculations.

Triboelectrification is a ubiquitous and poorly understood phenomenon in powder processing, particularly for pharmaceutical powders. Charged particles can adhere to vessel walls, causing sheeting; they can also cause agglomeration, threatening the stability of powder formulations, and in extreme cases electrostatic discharges, which present a serious fire and explosion hazard. Triboelectrification is highly sensitive to environmental and material conditions, which makes it very difficult to compare experimental results from different publications. In this work, density functional theory (DFT) is used to investigate the charge transfer characteristics of several functional groups of paracetamol in order to better understand the mechanisms of charging at the nanoscale and the influence of the environmental and material properties on charge transfer. This is achieved by studying the structure and electronic properties at the molecule-substrate interface. Using this molecule-substrate approach, the charging contributions of individual functional groups are explored by examining the Hirschfeld charges, the charge density difference between the molecule and substrate, the density of states, and the location of the frontier orbitals (HOMO and LUMO) of a paracetamol molecule. Charge density difference calculations indicate a significant transfer of charge from the molecule to the surface. Observable regions of electron density enrichment and depletion are evident around the electron-donating and -withdrawing groups, respectively. The density of states for the paracetamol molecule evolves as it approaches the surface, and the band gap disappears upon contact with the substrate. Hirshfeld charge analysis reveals asymmetry in the charge redistribution around the molecule, highlighting the varying charging tendencies of different atoms.

Marine heatwaves disrupt ecosystem structure and function via altered food webs and energy flux

The prevalence and intensity of marine heatwaves is increasing globally, disrupting local environmental conditions. The individual and population-level impacts of prolonged heatwaves on marine species have recently been demonstrated, yet whole-ecosystem consequences remain unexplored. We leveraged time series abundance data of 361 taxa, grouped into 86 functional groups, from six long-term surveys, diet information from a new diet database, and previous modeling efforts, to build two food web networks using an extension of the popular Ecopath ecosystem modeling framework, Ecotran. We compare ecosystem models parameterized before and after the onset of recent marine heatwaves to evaluate the cascading effects on ecosystem structure and function in the Northeast Pacific Ocean. While the ecosystem-level contribution (prey) and demand (predators) of most functional groups changed following the heatwaves, gelatinous taxa experienced the largest transformations, underscored by the arrival of northward-expanding pyrosomes. We show altered trophic relationships and energy flux have potentially profound consequences for ecosystem structure and function, and raise concerns for populations of threatened and harvested species.

Thermodynamic Modeling of Solubility of Some Antibiotics in Supercritical Carbon Dioxide Using Simplified Equation of State Approach

Antibiotics are playing crucial role in the treatment of humans since the last few centuries. Their usage has several benefits along with side effects. The efficacy of antibiotics for the treatment of ailments may be retained by controlling the drug dosage. This may be achieved with supercritical fluid technology (SFT). The antibiotic drug solubility in supercritical carbon dioxide (scCO2) is available only at specific temperature and pressure conditions, for effective utilization of SFT, solubility at various conditions are required. Equation of state (EoS) method is used for solubility data modeling and it requires critical properties of the solute, molar volume of the solute and sublimation pressure of the solute along with fugacity coefficient, pressure and temperature. These properties are estimated using group contribution methods. For antibiotics solute critical properties, molar volume and sublimation pressure are unavailable and existing group contribution methods are also not applicable due to the lack of functional group contributions in their techniques. Thus, there is a need to address EoS methodology without using solute properties. Hence, a new EoS methodology for solubility modeling is, proposed without using critical properties of the solute, molar volume of the solute and vapour pressure of the solute. Thus, this study focuses on the development of new solubility model that correlates antibiotics using equation of state (EoS). Importantly, the proposed solubility model does not use the critical properties of the antibiotics. Correlating ability of the proposed model is indicated in terms of regression coefficient and arithmetic average relative deviation percentage (AARD %).

Development of antibody-engineered molecularly imprinted polymers for selective capture of aflatoxin B1 from starchy food and medicinal materials

Molecularly imprinted polymers(MIPs) have been widely used as selective recognition materials for analysis and detection of mycotoxins, such as aflatoxin B1(AFB1). However, little attention was given to investigate key factors that affecting selectivity and specificity of MIPs, such as functional monomers and imprinted cavity compatibility. Inspired by the recognition of antibody to antigen, we designed and employed amino acids as functional monomers with multiple interaction sites via hydrogen bonding and aromatic π-π stacking, meanwhile, synthesized structurally matched alternative template, 5,7-dimethoxycyclopentenone [2,3-c]coumarin(DMPC) to prepare MIPs via silica surface grafting. The adsorption of antibody-engineered MIPs was enhanced significantly compared to that of MIPs prepared by conventional functional monomers and dummy templates for selective capture of AFB1. And the specific recognition sites of MIPs left by DMPC conferred the most remarkable selectivity toward AFB1 among aflatoxins. The mechanism and contribution of functional groups and imprinted cavities for selective adsorption of AFB1 were elucidated, providing a different approach to improving functional monomers and templates in MIPs. The solid phase extraction cartridges packed DMPC-ATry-MIPs@SiO2 were used for enrichment of AFB1 in Lotus seeds and Coix seeds. The recoveries were 94.48–112.90 % and 83.32–116.04 % respectively, even after being used five times repeatedly. The cartridges could replace expensive and low-reusability immunoaffinity columns in the analysis and detection of AFB1 in real samples, providing a kind of promising sample pretreatment materials for trace analysis in food and drugs.

Unraveling Atomic Contributions to the London Dispersion Energy: Insights into Molecular Recognition and Reactivity.

We present a general framework that enables quantification with atomic resolution of the overall London dispersion energy, which can be readily integrated with currently available energy decomposition schemes. This approach can be used to determine the contribution of individual atoms and functional groups to molecular recognition, conformational preferences, molecular stability, and reactivity. Its efficacy across diverse realms of molecular chemistry and biology is demonstrated with application to molecular balances in solution, asymmetric organocatalytic transformations, and a subcomplex of the F1FO ATP synthase.

Adsorption of levofloxacin hydrochloride by microplastics with or without oxygen functional groups

Functional groups can alter the properties of microplastics (MPs), thereby affecting their adsorption of antibiotics.This study selected oxygen free plastics polyvinyl chloride (PVC), polystyrene (PS), and oxygen containing plastics polyethylene terephthalate (PET) as representative MPs to investigate the adsorption behavior of MPs on levofloxacin hydrochloride (LEV) before and after ultraviolet (UV) aging.The research results indicated that the adsorption capacity of PET before and after aging was the strongest (from 0.430 to 0.859 mg/g), followed by PVC (from 0.406 to 0.733 mg/g) and PS (from 0.326 to 0.526 mg/g). After aging, PVC and PS generated C = O, and –OH functional groups, and the content of PET -COOR and –OH has increased. As the pH increases from 2 to 12, the saturated adsorption capacity of MPs first increased and then decreased. The adsorption capacities were suppressed with the presence of NaCl. Pb2+ and Cd2+ inhibited adsorption, as the complexation of oxygen-containing functional groups with metals reduced the saturation adsorption. In the mechanism calculation, the contribution of microporous filling was the most, while the contribution of functional groups was small. The increase of oxygen-containing functional groups enhanced the electrostatic interaction and hydrogen bond.

ICVD Polymer Thin Film Bio‐Interface‐Performance for Fibroblasts, Cancer‐Cells, and Viruses Connected to Their Functional Groups and In Silico Studies

AbstractThin polymer coatings are used to improve the interface between biological species and functional materials. Their interaction is significantly influenced by the functional groups and roughness of the polymer film and prediction of the interaction is thus of great interest. However, for conventional polymer films, this cannot be examined independently because of the interplay of defects, residual solvent molecules, roughness, and functional groups. Solvent‐free polymer films prepared by initiated chemical vapor deposition (iCVD) exhibit conformal, defect‐free characteristics and enable precise tailoring of the functional groups. This facilitates to isolate the contribution of functional groups on the bio‐interface performance. Consequently, in silico studies can enable a prediction of ligand interaction in anti‐viral activity for SARS‐CoV‐2 based on defined polymer and key protein structures. Furthermore, the cell viability of human fibroblasts can be traced back to the functional groups of the repeating units. For human liver cancer cell culture, it turns out that more sophisticated models are needed. The insilico‐iCVD approach can enable precise tailoring of complex polymer films optimized for the respective interfaces. In addition, this first big scan of the bio‐interface performance of iCVD films enables a solid starting point in areas like anticancer, antiviral, and biocompatibility for future studies.

Plant-substrate biochar properties critical for mediating reductive debromination of 1,2-dibromoethane

Dibromoethane is a widespread, persistent organic pollutant. Biochars are known mediators of reductive dehalogenation by layered FeII-FeIII hydroxides (green rust), which can reduce 1,2-dibromoethane to innocuous bromide and ethylene. However, the critical characteristics that determine mediator functionality are lesser known. Fifteen biochar substrates were pyrolyzed at 600 °C and 800 °C, characterized by elemental analysis, X-ray photo spectrometry C and N surface speciation, X-ray powder diffraction, specific surface area analysis, and tested for mediation of reductive debromination of 1,2-dibromoethane by a green rust reductant under anoxic conditions. A statistical analysis was performed to determine the biochar properties, critical for debromination kinetics and total debromination extent. It was shown that selected plant based biochars can mediate debromination of 1,2-dibromoethane, that the highest first order rate constant was 0.082/hr, and the highest debromination extent was 27% in reactivity experiments with 0.1 µmol (20 µmol/L) 1,2-dibromoethane, ≈ 22 mmol/L FeIIGR, and 0.12 g/L soybean meal biochar (7 days). Contents of Ni, Zn, N, and P, and the relative contribution of quinone surface functional groups were significantly (p < 0.05) positively correlated with 1,2-dibromoethane debromination, while adsorption, specific surface area, and the relative contribution of pyridinic N oxide surface groups were significantly negatively correlated with debromination.

Standard molar enthalpies of formation of 3-methylglutaric and 3,3-dimethylglutaric anhydrides

In this research, both the standard molar enthalpy of formation in the crystalline phase and in the gas phase of 3-methylglutaric anhydride was calculated from experimental data. The temperature and enthalpy of fusion, as well as the molar heat capacity in solid phase was calculated by differential scanning calorimetry; the molar enthalpy of sublimation at 298.15 K by the Knudsen effusion method, the molar enthalpy of vaporization at 298.15 K by thermogravimetric analysis, and the standard massic combustion energy by combustion adiabatic calorimetry. Since 3,3-dimethylglutaric anhydride presented crystal transitions (with endothermic points at 352.76 K, 356.98 K and 397.15 K), some of its thermochemical properties were estimated from the functional group-contribution methods proposed by Benson, Gani and Naef and from application of Machine Learning based models.

Biomass-Derived Carbon-Based Electrodes for Electrochemical Sensing: A Review.

The diverse composition of biomass waste, with its varied chemical compounds of origin, holds substantial potential in developing low-cost carbon-based materials for electrochemical sensing applications across a wide range of compounds, including pharmaceuticals, dyes, and heavy metals. This review highlights the latest developments and explores the potential of these sustainable electrodes in electrochemical sensing. Using biomass sources, these electrodes offer a renewable and cost-effective route to fabricate carbon-based sensors. The carbonization process yields highly porous materials with large surface areas, providing a wide variety of functional groups and abundant active sites for analyte adsorption, thereby enhancing sensor sensitivity. The review classifies, summarizes, and analyses different treatments and synthesis of biomass-derived carbon materials from different sources, such as herbaceous, wood, animal and human wastes, and aquatic and industrial waste, used for the construction of electrochemical sensors over the last five years. Moreover, this review highlights various aspects including the source, synthesis parameters, strategies for improving their sensing activity, morphology, structure, and functional group contributions. Overall, this comprehensive review sheds light on the immense potential of biomass-derived carbon-based electrodes, encouraging further research to optimize their properties and advance their integration into practical electrochemical sensing devices.

PBRICS: A Novel Fragmentation Method for Explainable Property Prediction of Drug-Like Small Molecules.

Generative artificial intelligence algorithms have shown to be successful in exploring large chemical spaces and designing novel and diverse molecules. There has been considerable interest in developing predictive models using artificial intelligence for drug-like properties, which can potentially reduce the late-stage attrition of drug candidates or predict the properties of novel AI-designed molecules. Concurrently, it is important to understand the contribution of functional groups toward these properties and modify them to obtain property-optimized lead compounds. As a result, there is an increasing interest in the development of explainable property prediction models. However, current explainable approaches are mostly atom-based, where, often, only a fraction of a fragment is shown to be significant. To address the above challenges, we have developed a novel domain-aware molecular fragmentation approach termed post-processing of BRICS (pBRICS), which can fragment small molecules into their functional groups. Multitask models were developed to predict various properties, including the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties. The fragment importance was explained using the gradient-weighted class activation mapping (Grad-CAM) approach. The method was validated on data sets of experimentally available matched molecular pairs (MMPs). The explanations from the model can be useful for medicinal chemists to identify the fragments responsible for poor drug-like properties and optimize the molecule. The explainability approach was also used to identify the reason behind false positive and false negative MMP predictions. Based on evidence from the existing literature and our analysis, some of these mispredictions were justified. We propose that the quantity, quality, and diversity of the training data will improve the accuracy of property prediction algorithms for novel molecules.