Detection of Perfluorooctanoic and Perfluorodecanoic Acids on a Graphene-Based Electrochemical Sensor Aided by Computational Simulations.

Perfluoroalkyl carboxylic acids (PFCAs) exhibit high chemical and thermal stability, rendering them versatile for various applications. However, their notable toxicity poses environmental and human health concerns. Detecting trace amounts of these chemicals is crucial to mitigate risks. Electrochemical sensors surpass traditional methods in sensitivity, selectivity, and cost-effectiveness. In this study, a graphene nanosheet-based sensor was developed for detecting perfluorooctanoic acid (PFOA) and perfluorodecanoic acid (PFDA). Using the Hummer method, graphene nanosheets were synthesized and characterized in terms of morphology, structural ordering, and surface topology. Ab initio molecular dynamics simulations determined the molecular interaction of per- and poly-fluoroalkyl substances (PFASs) with the sensor material. The sensor exhibited high sensitivity (50.75 µA·µM-1·cm-2 for PFOA and 29.58 µA·µM-1·cm-2 for PFDA) and low detection limits (10.4 nM for PFOA and 16.6 nM for PFDA) within the electrode dynamic linearity range of 0.05-500.0 µM (PFOA) and 0.08-500.0 µM (PFDA). Under optimal conditions, the sensor demonstrated excellent selectivity and recovery in testing for PFOA and PFDA in environmental samples, including spiked soil, water, spoiled vegetables, and fruit samples.

Incorporating solvent effects in DFT: insights from cation exchange in faujasites.

Zeolites are versatile materials renowned for their extra-framework cation exchange capabilities, with applications spanning diverse fields, including nuclear waste treatment. While detailed experimental characterization offers valuable insight, density functional theory (DFT) proves particularly adept at investigating ion exchange in zeolites, owing to its atomic and electronic resolution. However, the prevalent occurrence of zeolitic ion exchange in aqueous environments poses a challenge to conventional DFT modeling, traditionally conducted in a vacuum. This study seeks to enhance zeolite modeling by systematically evaluating predictive differences across varying degrees of aqueous solvent inclusion. Specifically focusing on monovalent cation exchange in Na-X zeolites, we explore diverse modeling approaches. These range from simple dehydrated systems (representing bare reference states in vacuum) to more sophisticated models that incorporate aqueous solvent effects through explicit water molecules and/or a dielectric medium. Through comparative analysis of DFT and semi-empirical DFT approaches, along with their validation against experimental results, our findings underscore the necessity to concurrently consider explicit and implicit solvent effects for accurate prediction of zeolitic ionic exchange.

Reference-Quality Free Energy Barriers in Catalysis from Machine Learning Thermodynamic Perturbation Theory.

For the first time, we report calculations of the free energies of activation of cracking and isomerization reactions of alkenes that combine several different electronic structure methods with molecular dynamics simulations. We demonstrate that the use of a high level of theory (here Random Phase Approximation-RPA) is necessary to bridge the gap between experimental and computed values. These transformations, catalyzed by zeolites and proceeding via cationic intermediates and transition states, are building blocks of many chemical transformations for valorization of long chain paraffins originating, e.g., from plastic waste, vegetable oils, Fischer-Tropsch waxes or crude oils. Compared with the free energy barriers computed at the PBE+D2 production level of theory via constrained ab initio molecular dynamics, the barriers computed at the RPA level by the application of Machine Learning thermodynamic Perturbation Theory (MLPT) show a significant decrease for isomerization reaction and an increase of a similar magnitude for cracking, yielding an unprecedented agreement with the results obtained by experiments and kinetic modeling.

Ab Initio Screening of Divalent Cations for CH4, CO2, H2, and N2 Separations in Chabazite Zeolite.

The efficient separation and adsorption of critical gases are, more than ever, a major focus point in important energy processes, such as CH4 enrichment of biogas or natural gas, CO2 separation and capture, and H2 purification and storage. Thanks to its physicochemical properties, cation-exchanged chabazite is a potent zeolite for such applications. Previous computational screening investigations have mostly examined chabazites exchanged with monovalent cations. Therefore, in this contribution, periodic density functional theory (DFT) calculations in combination with dispersion corrections have been used for a systematic screening of divalent cation exchanged chabazite zeolites. The work focuses on cheap and readily available divalent cations, Ca(II), Mg(II), and Zn(II), Fe(II), Sn(II), and Cu(II) and investigates the effect of the cation nature and location within the framework on the adsorption selectivity of chabazite for specific gas separations, namely, CO2/CH4, N2/CH4, and N2/H2. All the cationic adsorption sites were explored to describe the diversity of sites in a typical experimental chabazite with a Si/Al ratio close to 2 or 3. The results revealed that Mg-CHA is the most promising cation for the selective adsorption of CO2. These predictions were further supported by ab initio molecular dynamics simulations performed at 300 K, which demonstrated that the presence of CH4 has a negligible impact on the adsorption of CO2 on Mg-CHA. Ca(II) was found to be the most favorable cation for the selective adsorption of H2 and CO2. Finally, none of the investigated cations were suitable for the preferential capture of N2 and H2 in the purification of CH4 rich mixtures. These findings provide valuable insights into the factors influencing the adsorption behavior of N2, H2, CH4, and CO2 and highlight the crucial role played by theoretical calculations and simulations for the optimal design of efficient adsorbents.

Potential of nanostructured carbon materials for iodine detection in realistic environments revealed by first-principles calculations.

In the context of effective detection of iodine species (I2, CH3I) formed in nuclear power plants and nuclear fuel reprocessing facilities, we perform a comparative study of the potential sensing performance of four expectedly promising 2D materials (8-Pmmn borophene, BC3, C3N, and BC6N) towards the iodine-containing gases and, with the view of checking selectivity, towards common inhibiting gases in the containment atmosphere (H2O and CO), applying methods of dispersion-corrected density functional theory with periodic boundary conditions. A covalent bond is formed between the CO molecule and boron in BC3 or in 8-Pmmn borophene, compromising the anticipated applicability of these materials for iodine detection. The presence of nitrogen atoms in BC6N-2 prevents the formation of a covalent bond with CO; however, the closeness of adsorption energies for all the four gases studied does not distinguish this material as specifically sensitive to iodine species. Finally, the energies of adsorption on C3N yield a significant and promising discrimination between the adsorption energies of (I2, CH3I) vs. (CO, H2O), revealing possibilities for this material's use as an iodine sensor. The conclusions are supported by simulations at finite temperature; underlying electronic structures are also discussed.

The boson peak in silicate glasses: insight from molecular dynamics.

In the low-frequency regime, ≈1 THz, glasses show an anomalous excess in their vibrational density of states called the boson peak (BP). The origin of BP has been a subject of debate since its first discovery a few decades ago. Although BP has been the focus of numerous studies, no conclusive answers have been found about its origins, which remained elusive to date. Here, we present results based on molecular dynamics of several binary and ternary silicate glasses with different network intermediates and modifier oxides. The vibrational density of states and the BP are reported for all the studied glasses. Their correlation with the elastic constant C44, structural, and dynamical properties are extensively discussed in terms of Voronoi atomic volume and the vibrational mean square displacement of Q4 species specifically. We also question the classical classification of alkali oxides as modifiers, and we suggest that Li2O plays the role of pseudo-intermediate oxide in lithium silicate glasses. This claim is supported by the effect of Li on various vibrational modes, and this effect differs from the other alkali metals. Furthermore, we demonstrate a correlation between the BP intensities and both the Voronoi volume of the Q4 and Q3 units and vibrational mean square displacements.

Wastewater reuse in agriculture: Prospects and challenges.

Sustainable water recycling and wastewater reuse are urgent nowadays considering water scarcity and increased water consumption through human activities. In 2015, United Nations Sustainable Development Goal 6 (UN SDG6) highlighted the necessity of recycling wastewater to guarantee water availability for individuals. Currently, wastewater irrigation (WWI) of crops and agricultural land appears essential. The present work overviews the quality of treated wastewater in terms of soil microbial activities, and discusses challenges and benefits of WWI in line with wastewater reuse in agriculture and aquaculture irrigation. Combined conventional-advanced wastewater treatment processes are specifically deliberated, considering the harmful impacts on human health arising from WWI originating from reuse of contaminated water (salts, organic pollutants, toxic metals, and microbial pathogens i.e., viruses and bacteria). The comprehensive literature survey revealed that, in addition to the increased levels of pathogen and microbial threats to human wellbeing, poorly-treated wastewater results in plant and soil contamination with toxic organic/inorganic chemicals, and microbial pathogens. The impact of long-term emerging pollutants like plastic nanoparticles should also be established in further studies, with the development of standardized analytical techniques for such hazardous chemicals. Likewise, the reliable, long-term and extensive judgment on heavy metals threat to human beings's health should be explored in future investigations.

Valorization of biowastes for clean energy production, environmental depollution and soil fertility.

The mother earth is a source of natural resources that, in conjunction with anthropogenic activities, generates a wide spectrum of different biowastes. These biomaterials can be used as low-cost raw feedstock to produce bioenergy, value-added products, and other commodities. However, the improper management and disposal of these biowastes can generate relevant environmental impacts. Consequently, it is imperative to explore alternative technologies for the valorization and exploitation of these wastes to obtain benefits for the society. This review covers different aspects related to valorization of biowastes and their applications in water pollution, soil fertility and green energy generation. The classification and characteristics of different biowastes (biosolids, animal wastes and effluents, plant biomass, wood and green wastes) including their main generation sources are discussed. Different technologies (e.g., pyrolysis, hydrothermal carbonization, anaerobic digestion, gasification, biodrying) for the transformation and valorization of these residues are also analyzed. The application of biowastes in soil fertility, environmental pollution and energy production are described and illustrative examples are provided. Finally, the challenges related to implement low-cost and sustainable biowaste management strategies are highlighted. It was concluded that reliable simulation studies are required to optimize all the logistic stages of management chain of these residues considering the constraints generated from the economic, environmental and social aspects of the biowaste generation sources and their locations. The recollection and sorting of biowastes are key parameters to minimize the costs associated to their management and valorization. Also, the concepts of Industry 4.0 can contribute to achieve a successful commercial production of the value-added products obtained from the biowaste valorization. Overall, this review provides a general outlook of biowaste management and its valorization in the current context of circular economy.

Ab initio molecular dynamics investigation of the co-adsorption of iodine species with CO and H2O in silver-exchanged chabazite.

In the field of nuclear energy, there is particular interest for the trapping of harmful iodine species (I2 and CH3I) that could be released during a nuclear accident, due to their dangereous impact on the human metabolic processes and the environment. Here, the adsorption of these iodine molecules versus several inhibitory compounds (CO, H2O, CH3Cl and Cl2) in the silver exchanged chabazite zeolite is studied in detail using ab initio molecular dynamics simulations at a realistic temperature and composition. Interestingly, we found that the iodine molecules remain attached to the cations even when the number of water molecules inside the structure is greater than two times the number of cations per cell at T = 413 K. For CO, we found that CH3I is more perturbed than I2 by the presence of this inhibitor. Overall, our results indicate that the silver-exchanged chabazite zeolite is a promising candidate to trap iodine species in the case of a severe nuclear accident.

Effect of the sulfur termination on the properties of Hf2CO2 MXene.

A computational study was carried out to investigate the effect of surface termination on Janus Hf2COS MXene by substituting partly the O-terminated layer with S atoms. Our predictions confirm that this chemical strategy allows one to tailor the band gap of MXenes. Indeed, the semiconducting character of Hf2CO2 MXene decreases by the exchange of O by S atoms. From a structural point of view, dynamical, mechanical, and thermal analysis confirm the thermodynamic stability of the Janus Hf2COS MXene, which shows metallic character. Furthermore, topological chemical analysis indicates an ionic nature of Hf2CO2 MXene that tends to be reduced by increasing the concentration of S atoms, promoting a covalent character. Shortly, the present study illustrates how the properties of MXenes can be tailored by functionalizing them with different chemical terminations.

Adsorption of NO, NO2 and H2O in divalent cation faujasite type zeolites: a density functional theory screening approach.

Emissions of diesel exhaust gas in confined work environments are a major health and safety concern, because of exposition to nitrogen oxides (NOx). Removal of these pollutants from exhaust gas calls for engineering of an optimum sorbent for the selective trapping of NO and NO2 in the presence of water. To this end, periodic density functional theory calculations along with a recent dispersion correction scheme, namely the Tkatchenko-Scheffler scheme coupled with iterative Hirshfeld partitioning TS/HI, were performed to investigate the interactions between NO, NO2, H2O and a series of divalent cation (Be2+, Mg2+, Ca2+, Sr2+, Ba2+, Fe2+, Cu2+, Zn2+, Pd2+, and Pt2+) faujasites. This enabled the identification of the optimum zeolites to selectively capture NOx in the presence of H2O, with respect to two important criteria, such as thermodynamic affinity and regeneration. Our results revealed that Pt2+ and Pd2+ containing faujasites are the best candidates for effective capture of both NO and NO2 molecules, which paves the way towards the use of these sorbents to address this challenging application.

Hybrid localized graph kernel for machine learning energy-related properties of molecules and solids.

Nowadays, the coupling of electronic structure and machine learning techniques serves as a powerful tool to predict chemical and physical properties of a broad range of systems. With the aim of improving the accuracy of predictions, a large number of representations for molecules and solids for machine learning applications has been developed. In this work we propose a novel descriptor based on the notion of molecular graph. While graphs are largely employed in classification problems in cheminformatics or bioinformatics, they are not often used in regression problem, especially of energy-related properties. Our method is based on a local decomposition of atomic environments and on the hybridization of two kernel functions: a graph kernel contribution that describes the chemical pattern and a Coulomb label contribution that encodes finer details of the local geometry. The accuracy of this new kernel method in energy predictions of molecular and condensed phase systems is demonstrated by considering the popular QM7 and BA10 datasets. These examples show that the hybrid localized graph kernel outperforms traditional approaches such as, for example, the smooth overlap of atomic positions and the Coulomb matrices.

Low-dimensional HfS2 as SO2 adsorbent and gas sensor: effect of water and sulfur vacancies.

First-principles based on density functional theory (DFT) calculations were performed to investigate the interaction of two-dimensional (2D) HfS2 with SO2, a harmful gas with implications for climate change. In particular, we describe the effect of water and sulfur vacancies on such interaction. The former promotes the physisorption of SO2, whereas the latter promotes its chemisorption with structural changes on the absorbing surface. The results show that both structures are exothermic to adsorb the SO2 molecules, but the adsorption type is different. The reaction of the stable structure in the presence of water with the sulfur oxides is a physisorption interaction that enhances the band gap value of the isolated monolayer. However, for the defective structure, we have a chemisorption interaction type, where the adsorption of SO2 molecules widens the band gap values. To understand this behavior, we used Bader charge calculations and the noncovalent interactions index. While the water enhances the charge transfer between the monolayer and the adsorbed gas, the results show, however, that the defective structure is a more favorable gas sensor due to the metallic edge of the active site.

Adsorption of water in Na-LTA zeolites: an ab initio molecular dynamics investigation.

The very wide range of applications of LTA zeolites, including the storage of tritiated water, implies that a detailed and accurate atomic-scale description of the adsorption processes taking place in their structure is crucial. To unravel with an unprecedented accuracy the mechanisms behind the water filling in NaA, we have conducted a systematic ab initio molecular dynamics investigation. Two LTA structural models, the conventional Z4A and the reduced one ZK4, have been used for static and dynamic ab initio calculations, respectively. After assessing this reduced model with comparative static DFT calculations, we start the filling of the α and ß cages by water, molecule by molecule. This allowed us to thoroughly study the interaction of water molecules with the zeolite structure and between water molecules, progressively forming H-bond chains and ring patterns as the cage is being filled. The adsorption energies could then be calculated with an unprecedented accuracy, which showed that the interaction of the molecules with the zeolite weakens as their number increases. By these methods, we have been able to highlight the primary role of Na+ cations in the interaction of water with zeolite, and inversely, the role of water in the displacement of cations when it is sufficiently solvated, allowing the passage between the α and ß cages. This phenomenon is possible thanks to the inhomogeneous distribution of water molecules on the cationic sites, as shown by our AIMD simulations, which allows the formation of water clusters. These results are important because they help in understanding how the coverage of cationic sites by water will affect the adsorption of other molecules inside the Na-LTA zeolite.

Make it clean, make it safe: A review on virus elimination via adsorption.

Recently, the potential dangers of viral infection transmission through water and air have become the focus of worldwide attention, via the spread of COVID-19 pandemic. The occurrence of large-scale outbreaks of dangerous infections caused by unknown pathogens and the isolation of new pandemic strains require the development of improved methods of viruses' inactivation. Viruses are not stable self-sustaining living organisms and are rapidly inactivated on isolated surfaces. However, water resources and air can participate in the pathogens' diffusion, stabilization, and transmission. Viruses inactivation and elimination by adsorption are relevant since they can represent an effective and low-cost method to treat fluids, and hence limit the spread of pathogen agents. This review analyzed the interaction between viruses and carbon-based, oxide-based, porous materials and biological materials (e.g., sulfated polysaccharides and cyclodextrins). It will be shown that these adsorbents can play a relevant role in the viruses removal where water and air purification mostly occurring via electrostatic interactions. However, a clear systematic vision of the correlation between the surface potential and the adsorption capacity of the different filters is still lacking and should be provided to achieve a better comprehension of the global phenomenon. The rationalization of the adsorption capacity may be achieved through a proper physico-chemical characterization of new adsorbents, including molecular modeling and simulations, also considering the adsorption of virus-like particles on their surface. As a most timely perspective, the results on this review present potential solutions to investigate coronaviruses and specifically SARS-CoV-2, responsible of the COVID-19 pandemic, whose spread can be limited by the efficient disinfection and purification of closed-spaces air and urban waters.

Adsorption of Toluene and Water over Cationic-Exchanged Y Zeolites: A DFT Exploration.

In this study, density functional theory (DFT) calculations have been performed to investigate the adsorption mechanisms of toluene and water onto various cationic forms of Y zeolite (LiY, NaY, KY, CsY, CuY and AgY). Our computational investigation revealed that toluene is mainly adsorbed via π-interactions on alkalis exchanged Y zeolites, where the adsorbed toluene moiety interacts with a single cation for all cases with the exception of CsY, where two cations can simultaneously contribute to the adsorption of the toluene, hence leading to the highest interaction observed among the series. Furthermore, we find that the interaction energies of toluene increase while moving down in the alkaline series where interaction energies are 87.8, 105.5, 97.8, and 114.4 kJ/mol for LiY, NaY, KY and CsY, respectively. For zeolites based on transition metals (CuY and AgY), our calculations reveal a different adsorption mode where only one cation interacts with toluene through two carbon atoms of the aromatic ring with interaction energies of 147.0 and 131.5 kJ/mol for CuY and AgY, respectively. More importantly, we show that water presents no inhibitory effect on the adsorption of toluene, where interaction energies of this latter were 10 kJ/mol (LiY) to 47 kJ/mol (CsY) higher than those of water. Our results point out that LiY would be less efficient for the toluene/water separation while CuY, AgY and CsY would be the ideal candidates for this application.

DNA Nucleobase under Ionizing Radiation: Unexpected Proton Transfer by Thymine Cation in Water Nanodroplets.

The effect of ionizing radiation on DNA constituents is a widely studied fundamental process using experimental and computational techniques. In particular, radiation effects on nucleobases are usually tackled by mass spectrometry in which the nucleobase is embedded in a water nanodroplet. Here, we present a multiscale theoretical study revealing the effects and the dynamics of water droplets towards neutral and ionized thymine. In particular, by using both hybrid quantum mechanics/molecular mechanics and full ab initio molecular dynamics, we reveal an unexpected proton transfer from thymine cation to a nearby water molecule. This leads to the formation of a neutral radical thymine and a Zundel structure, while the hydrated proton localizes at the interface between the deprotonated thymine and the water droplet. This observation opens entirely novel perspectives concerning the reactivity and further fragmentation of ionized nucleobases.

Disclosing the behavior under hydrostatic pressure of rhombohedral MgIn2Se4 by means of first-principles calculations.

AM2X4 crystalline materials display important technological electronic, optical and magnetic properties that are sensitive to general stress effects. In this paper, the behavior under hydrostatic pressure of the ambient condition rhombohedral phase of MgIn2Se4 is investigated in detail for the first time. We carried out first-principles calculations within the density functional theory framework aimed at determining the pressure-induced polymorphic sequence of this selenide. To accurately evaluate transition pressures at room temperature, thermal corrections have been included after the computation of phonon dispersion curves in potential candidate phases, namely the initial rhombohedral R3[combining macron]m one, inverse and direct spinels, LiTiO2-type and defective I4[combining macron] structures. Only the transition from the R3[combining macron]m to the inverse spinel phase was found to fulfill the thermodynamic and mechanical stability criteria. The direct spinel could appear as metastable if kinetic effects hinder the above transition. Additionally, electronic band structures and chemical bonding properties were analyzed from the outcome of our quantum-mechanical solutions reporting band gap values and ionicity and noncovalent interaction indexes. It is shown that the investigated compound keeps behaving as a semiconductor, loses its van der Waals interactions, and becomes more covalent as hydrostatic pressure is applied.

Incorporation of trivalent cations in NaX zeolite nanocrystals for the adsorption of O2 in the presence of CO2.

The O2 and CO2 sorption properties of nanosized zeolite X with faujasite type structure through a partial ionic exchange of sodium (Na+) by trivalent cations (Gd3+ and Ce3+) were evaluated. Three faujasite samples were studied, the as-synthesized Na-X possessing Na+ solely, and the modified samples Na-Gd-X and Na-Ce-X containing Gd3+ (1.8 wt%) and Ce3+ (0.82 wt%), respectively. Incorporating scarce amounts of trivalent cations modified the adsorption affinity of zeolites towards O2 and CO2 as demonstrated by in situ Fourier-transform infrared spectroscopy (FTIR). While Na-Ce-X encounters the highest O2 physisorption capacity, the Na-Gd-X is adsorbing the highest quantities of molecular CO2. All three samples exhibit the chemisorbed CO2 in the form of carbonates, while the Na-X stores carbonates in monodentate and polydentate forms, the Na-Gd-X and Na-Ce-X allow the formation of polydentate carbonates only. Density functional theory (DFT) calculations revealed that trivalent cations tend to adsorb gases through two cations simultaneously which explains the presence of polydentate carbonates exclusively in the corresponding modified zeolites. The DFT results confirmed the higher affinity of Na-Gd-X and Na-Ce-X nanocrystals towards O2 in the presence of CO2. The affinity of Na-Gd-X and Na-Ce-X nanocrystals towards O2 opens the door of their use as oxygen transporters for medical applications where CO2 is constantly present. The toxicity of the nanosized zeolites and their performance in O2 release are reported too.

Grafting of iron on amorphous silica surfaces from ab initio calculations.

Iron over silica catalytic systems have attracted considerable attention due to their activity and selectivity in different reactions, for instance, in the hydrodeoxygenation process. Here, the grafting mechanisms of iron under various forms (one atom, two atoms, or a cluster) on silica surfaces are studied using ab initio calculations. Various geometries with different locations of iron on the silica structure have been investigated, and it is found that a strong interaction between iron and the silanol groups takes place, mostly driven by the formation of Fe-O-Si bonds, and in few cases by nearby surface OH groups, creating Fe-OH-Si bonds. For the cluster, we show that the most favorable adsorption mode induces a strong effect on the silica surface accompanied with a large charge transfer, making it very stable and promising for a large panel of applications.