Physchem

Feed-forward neural networks (NNs) are widely used for the machine learning of properties of materials and molecules from descriptors of their composition and structure (materials informatics) as well as in other physics and chemistry applications. Often, multilayer (so-called “deep”) NNs are used. Considering that universal approximator properties hold for single-hidden-layer NNs, we compare here the performance of single-hidden-layer NNs (SLNN) with that of multilayer NNs (MLNN), including those previously reported in different applications. We consider three representative cases: the prediction of the band gaps of two-dimensional materials, prediction of the reorganization energies of oligomers, and prediction of the formation energies of polyaromatic hydrocarbons. In all cases, results as good as or better than those obtained with an MLNN could be obtained with an SLNN, and with a much smaller number of neurons. As SLNNs offer a number of advantages (including ease of construction and use, more favorable scaling of the number of nonlinear parameters, and ease of the modulation of properties of the NN model by the choice of the neuron activation function), we hope that this work will entice researchers to have a closer look at when an MLNN is genuinely needed and when an SLNN could be sufficient. Full article

In recent years, perovskites have quickly gained popularity in applications related to photonic devices and in photovoltaic applications. Over the last several years, the efficiency of photovoltaic (PV) cells based on perovskites has matched the efficiency of PV cells based on silicon. CsPbBr₃ perovskite is gaining more and more popularity, but due to the too large band gap value, its use in photovoltaics is difficult. Another perovskite, very intensively researched and giving hope for further development of photovoltaics, is CsPbI₃. The CsPbI₃ band gap is smaller than the CsPbBr₃ band gap and more suitable for photovoltaic applications. However, CsPbI₃ is unstable under the conditions of solar cell operation. To reduce the band gap value and increase the perovskite stability, very intensive research, both theoretical and experimental, is devoted to structures with mixed halides, i.e., a mixture of bromine and iodine with the general formula CsPbBr_xI_3−x. Computational methods based on DFT have been successfully used for many years to determine the parameters and properties of materials. The use of computational methods significantly reduces the costs of the research performed compared to experimental techniques. The aim of this work is to understand the band gap changes based on DFT calculations as well as XRD and UV-Vis experiments for CsPbBr₃, CsPbI₃, and CsPbBr_xI_3x perovskites. Full article

In this paper, the benefits of using monodisperse polymeric particles as matrices to immobilize biosystems are presented and discussed. The nature of the polymer (natural, synthetic, or semisynthetic) and immobilization techniques were directly related to the performance of this process. In addition, this work reviews the major biological and synthetic entities that have been immobilized on monodisperse polymeric particles and their potential applications available in the literature. The research revealed that enzymes, proteins, cells, and drugs are the main entities immobilized on polymeric matrices. Several physicochemical characterization techniques were discussed to determine the presence of entities after the immobilization process. In addition, some applications of immobilized enzymes in different areas are also presented since this biomolecule was the most frequent entity in terms of immobilization on polymeric matrices. Finally, this review describes the main advances in polymeric materials used as supports for immobilizing biosystems due to their interesting physical and chemical properties. Full article

Na₃V₂(PO₄)₃ (NVP), a NASICON-type material, has gained attention as a promising battery cathode owing to its high sodium mobility and excellent structural stability. Using computational simulation techniques based on classical potentials and density functional theory (DFT), we examine the defect characteristics, diffusion mechanisms, and dopant behavior of the NVP. The study found that the Na Frenkel defect is the most favorable intrinsic defect, supporting the desodiation process necessary for capacity and enabling vacancy-assisted Na-ion migration. The Na migration is anticipated through a long-range zig-zag pathway with an overall activation energy of 0.70 eV. K and Sc preferentially occupy Na and V sites without creating charge-compensating defects. Substituting Mg at the V site can simultaneously increase Na content by forming interstitials and reducing the band gap. Additionally, doping Ti at the V site promotes the formation of Na vacancies necessary for vacancy-assisted migration, leading to a notable improvement in electronic conductivity. Full article

Fast electrochemical phenomena occurring in supercapacitors are hard to analyze by ex situ or in situ techniques because many of them are meta-stable (the supercapacitor relaxes once it is not further polarized). In a steady state, one observes the effect of charge storage but not necessarily the mechanism. This is a problem for Raman spectroscopy, too, even though Raman spectra of the electrodes of supercapacitors are commonly recorded ex situ or in a steady state in situ. Raman operando is desired, but it represents a technological challenge since the electrochemical events in a supercapacitor are very fast (occurring within seconds), and in contrast, Raman requires from seconds to minutes to collect enough photons for reliable spectra. This work presents the development of electrodes made of thin layers of iron oxide grown solvothermally on Si wafers, with a porosified surface and resistivity of 0.005 Ωcm, to study their performance as electrodes in supercapacitors and analyze their energy storage mechanisms by cyclic voltammetry and Raman operando. Being flat and containing just iron oxide and silicon, these electrodes allow for studying interfacial phenomena with minor interferents. Full article

In the present study, we report infrared and Raman spectra in both solution and the solid state, together with a state-of-the art inelastic neutron scattering spectrum, of the unusual molecule pagodane. Periodic DFT calculations have enabled a complete assignment of all the modes. The isolated molecule has D_2h symmetry, which is reduced to C_i in the solid state. However, the preservation of the centre of symmetry means that the selection rules for infrared and Raman spectroscopy are almost unchanged. The exceptions are the D_2hA_u modes that are forbidden in the isolated molecule but become allowed in the solid state. These have been located in the solid-state spectra. Full article

In today’s tech world of digitalization, engineers are leveraging tools such as artificial intelligence for analyzing data in order to enhance their capability in evaluating product quality effectively. This research study adds value by applying algorithms and various machine learning techniques—such as support vector regression, Gaussian process regression, and artificial neural networks—on a dataset related to the grinding process of UNS S34700 steel. What sets this study apart is its consideration of factors like three types of grinding wheels, four distinct cooling solutions, and seven varied depths of cut. These parameters are assessed for their impact on surface roughness and grinding forces, resulting in the conversion of information into insights. A relational equation with 25 coefficients is developed, using optimized algorithms to predict surface roughness with an 85 percent accuracy and grinding forces with a 90 percent accuracy rate. Learning from machine models like the Gaussian process regression exhibited stability, with an R² value of 0.98 and a mean accuracy of 93 percent. Artificial neural networks achieved an R² value of 0.96, and an accuracy rate of 90 percent. These findings suggest that machine learning techniques are versatile and precise when dealing with datasets. They align well with digitalization and predictive trends. In conclusion; machine learning provides flexibility and superior accuracy for predicting data trends compared to the formulaic approach, which is contained to existing datasets only. The versatility of machine learning highlights its significance in engineering practices for making data-informed decisions. Full article

Recently, a series of 8(meso)-pyridyl-BODIPYs (2-pyridyl, 3-pyridyl, and 4-pyridyl) and their 2,6-substituted derivatives were synthesized and their structure and photophysical properties were studied both experimentally and computationally. One of the main observed trends was that the 2-pyridyl-BODIPYs were consistently less fluorescent than their 3-pyridyl and 4-pyridyl analogs, regardless of the 2,6-substituents. Herein, we extend our previous computational studies and model not only the ground but also the excited states of the entire series of previously synthesized meso-pyridyl-BODIPYs with the aim of explaining the observed differences in the emission quantum yields. To better understand the trends and the effect of 2- and 2,6-substitution on the photophysical and electron-density-related properties, we also model the ground and excited states of BODIPYs that were not synthesized experimentally, however represent a logical part of the series. We calculate a variety of molecular properties and propose that the experimentally observed low quantum yields for all 2-pyridyl-BODIPYs could be due to the very flat potential energy surfaces with respect to the rotation of the 2-pyridyl ring in the excited states, and the stability of a non-planar and significantly less fluorescent meso-2-pyridyl-BODIPY structure. Full article

Acid mine drainage (AMD), wherein acidic water is generated from pyrite-containing waste rock, can be mitigated by encapsulating pyritic waste rock with cover materials to restrict the inflow of oxygen and water. However, acidic water inevitably forms during the construction of waste rock dumps before applying cover materials. Considering that the presence of waste rock containing carbonate minerals contributes to acid neutralization, a mixture of carbonate minerals and pyritic waste rock can be utilized to reduce AMD generation before the completion of the cover system as a temporary management strategy. This paper examines waste rock management using blending scenarios. Kinetic NAG and column leaching tests were employed to evaluate the blending ratio necessary to prevent acidic water generation. Geochemical analyses were conducted on rock and leachate samples, including pH and temperature measurements, XRD and XRF analyses, and Ion Chromatography. Consequently, the pH and temperature measurement results obtained during the kinetic NAG test are valuable for expressing the balance between acid generation and acid neutralization by the mixture material. Furthermore, the column leaching test demonstrated that the pH of the leachate remained neutral when the acid generation and acid neutralization reactions were well balanced. Blending waste rocks is an effective method for AMD reduction during the construction of waste rock dumps. Full article

Tutton salts have received considerable attention due to their potential applications in thermochemical energy storage (TCHS) systems. This technology requires high-purity materials that exhibit reversible dehydration reactions, significant variations in dehydration enthalpy, and high-temperature melting points. In this study, K₂Cu(SO₄)₂(H₂O)₆ Tutton salt in the form of single crystals was grown using the slow solvent evaporation method. Their structural, morphological, and thermal characteristics are presented and discussed, as well as temperature-induced phase transformations. At room temperature, the salt crystallizes in a monoclinic structure belonging to the P2₁/a space group, which is typical for Tutton salts. The lack of precise control over the solvent evaporation rate during crystal growth introduced structural disorder, resulting in defects on the crystal surface, including layer discontinuities, occlusions, and pores. Thermoanalytical analyses revealed two stages of mass loss, corresponding to the release of 4 + 2 coordinated H₂O molecules—four weakly coordinated and two strongly coordinated to the copper. The estimated dehydration enthalpy was ≈ 80.8 kJ/mol per mole of H₂O. Powder X-ray diffraction measurements as a function of temperature showed two phase transformations associated with the complete dehydration of the starting salt occurring between 28 and 160 °C, further corroborating the thermal results. The total dehydration up to ≈ 160 °C, high enthalpy associated with this process, and high melting point temperature make K₂Cu(SO₄)₂(H₂O)₆ a promising candidate for TCHS applications. Full article

The present work was the preliminary study of phase diagrams and miscibilities of low-temperature metallomesogen (MOM) model structures based on rod-like palladium (Pd) alkyl/alkoxy-azobenzene metal complexes and their mixtures with commercial liquid crystal materials for potential application. The initial results indicated the accessible temperature range and mesgenic miscibility between parent ligand, MOMs and commercial liquid crystal mixtures. The eutectic ligand/MOM composition with other MOMs and commercial nematic liquid crystal materials exhibited complete mesogenic miscibility and wide low-temperature mesogenic stability for eventual utilization in commercial liquid crystal devices. Full article

The adsorptive removal of Bisphenol A (BPA) with the PE meshes photografted with 2-(dimethylamino)ethyl methacrylate (DMAEMA) was performed by varying the grafted amount, pH value, BPA concentration, and temperature, and the adsorption performance was correlated by the equilibrium, kinetic, and isotherm models. In addition, the regeneration of DMAEMA-grafted PE (PE-g-PDMAEMA) meshes was discussed from the repetitive adsorption/desorption process. The adsorption capacity had the maximum value at the grafted amount of 2.6 mmol/g and at the initial pH value of 8.0. The increase in the protonation of dimethylamino groups on grafted PDMAEMA chains and the dissociation of phenol groups of BPA present in the outer solution during the adsorption process results in the increase in BPA adsorption. The adsorption process followed the pseudo second-order equation. The BPA adsorption was enhanced by increasing the BPA concentration and the equilibrium data fit to Langmuir equation. The adsorption capacity stayed almost constant with the increase in the temperature, whereas the k₂ value increased against the temperature. These results comprehensively emphasized that BPA adsorption occurred through the chemical interaction or ionic bonding of a BPA anion to a terminal protonated dimethylamino group. Desorption of BPA increased by increasing the NaOH concentration and BPA was entirely desorbed at more than 20 mM. The cycle of adsorption at pH 8.0 and desorption in a NaOH solution at 100 mM was repeated five times without loss or structural damage. These results indicate PE-g-PDMAEMA meshes can be used as a regenerative adsorbent for BPA removal from aqueous medium. Full article

In recent years, ionic liquids (ILs) have served as potential solvents to dissolve organic, inorganic, and polymer materials. A copolymer (for example, Pluronic) can undergo self-organization by forming a micelle-like structure in pure IL medium, and its assembly depends upon the composition of IL. To evaluate the role of ILs, accurate coarse-grained (CG) modeling of IL is needed. Here, we modeled 1-ethyl-3-methylimidazolium dicyanamide ([EMIM][DCA]) ionic liquid (IL) using a CG framework. We optimized CG parameters for the [DCA]⁻ anion by tuning the non-bonded parameters and selecting different kinds of beads. The molecular density (ρ) and radial distribution function (RDF) of our CG model reveal a good agreement with the all-atom (AA) simulation data. We further validated our model by choosing another imidazolium-based cation. Our modified CG model for the anion shows compatibility with the cation and the obtained density matches well with the experimental data. The strategies for developing the CG model will provide a guideline for accurate modeling of new types of ILs. Our CG model will be useful in studying the micellization of non-ionic Pluronic in the [EMIM][DCA] IL medium. Full article

Antioxidants of plant extract play an important role in the phytosynthesis of silver nanoparticles (phyto-AgNPs), providing the reduction of silver ions and capping and stabilization of nanoparticles. Despite the current progress in the studies of phytosynthesis, there is no approach to the selection of plant extract for obtaining phyto-AgNPs with desired properties. This work shows that antioxidant activity (AOA) of plant extracts is a key parameter for targeted phytosynthesis. In support of this fact, the synthesis of phyto-AgNPs was carried out using extracts of four plants with different AOA, increasing in the order Ribes uva-crispa < Lonicera caerulea < Fragaria vesca < Hippophae rhamnoides. Phyto-AgNPs have been characterized using Fourier-transform infrared spectroscopy, transmission electron microscopy, energy-dispersive X-ray spectroscopy, selected area electron diffraction technique, ultraviolet–visible spectroscopy, electrochemical impedance spectroscopy and cyclic voltammetry. It was established that the change in the AOA of the plant extract is accompanied by a size-dependent change in the optical and electrochemical properties of phyto-AgNPs. In particular, an increase in the extract AOA leads to the formation of smaller phyto-AgNPs with higher electrochemical activity and low charge transfer resistance. A “blue shift” and an increase in the plasmon resonance band of silver sols are observed with an increase in the extract AOA. The obtained regularities prove the existence of the “AOA–size–properties” triad, which can be used for controlled phytosynthesis and prediction of phyto-AgNPs’ properties. Full article

Asphalt binder performance grades (PGs) are important metrics in designing pavements for effective transportation infrastructure. The PG system relies on the binder’s stiffness and is determined through energy- and time-intensive physical testing. Physical properties, like stiffness, can also be determined by spin–lattice NMR relaxometry, a non-destructive chemical method. NMR relaxometry can quantify the molecular mobility of materials by determining relaxation times from exponential decays of excited nuclear magnetization. While relaxation times have been used to determine physical properties of materials, a quantitative relation to the PG grades of asphalt binder is yet to be established. In this study, T₁ NMR relaxation analyses were used to differentiate between solid asphalt binders and determine the fastest yet still-reliable method of modeling exponential decay data. Algorithms that fit exponential decay relaxation data using one, two, or three independent relaxation times were compared with a 128-coefficient discrete inverse Laplace transformation to determine the best mathematical fit for a comparative analysis. The number of data points was then reduced from 256 to 64 to 16 and finally to 8 data points on a relaxation curve to reduce the testing time and determine the minimum number of data points needed for comparison. Two batches of PG 64-22 asphalt binder, along with samples of PG 76-22 and 94-10 binders, were investigated. The best compromise between measuring time and data reliability was found by acquiring 64 data points and then using a biexponential model to fit the experimental data. The PG 64-22 sources provided similar results, indicating similar physical properties. The PG 64-22 and PG 76-22 binders could also be compared via monoexponential data fits, but the PG 94-10 samples required an additional relaxation parameter for comparison. To differentiate all three binder grades, the primary relaxation times, along with their relative ratios, were utilized. Full article

Multiple intermolecular H-bonding interactions play a pivotal role in determining the macroscopic state of ionic liquids (ILs). Hence, the relationship between the microscopic and the macroscopic properties is key for a rational design of new imidazolium ILs. In the present work, we investigated how the physicochemical property of hydroxyl-functionalized imidazolium chloride is connected to the molecular structure and intermolecular interactions. In the isolated ion pair, strong N-H···Cl H-bonding interactions are observed rather than H-bonding interactions at the acidic C₂-H site and alkyl-OH···Cl of the hydroxyl-functionalized imidazolium chloride. However, the N-H···Cl H-bonding interaction of the cation plays a significant role in ion-pair formations and polymeric clusters. For 3-(2-Hydroxy)-1H-imidazolium chloride (EtOHImCl), the oxygen atom (O) engages in two significant interactions within its homodimeric ion-pair cluster: N-H···O and alkyl OH···Cl. Vibrational spectroscopy and DFT calculations reveal that the chloride ion (Cl⁻) forms a hydrogen bond with the C2-H group via a C2-H···Cl interaction site. Natural Bond Orbital (NBO) analysis indicates that the O-H···Cl hydrogen-bonding interaction is crucial for the stability of the IL, with a second-order perturbation energy of approximately 133.8 kJ/mol. Additional computational studies using Atoms in Molecules (AIMs), non-covalent interaction (NCI) analysis, Electron Localization Function (ELF), and Localized Orbital Locator (LOL) provide significant insights into the properties and nature of non-covalent interactions in ILs. Ab initio molecular dynamics (AIMD) simulations of the IL demonstrate its stable states with relatively low energy values around −1680.6510 atomic units (a.u.) at both 100 fs and 400 fs due to O-H···Cl and C-H···Cl interactions. Full article

The main objective was to evaluate the use of common bean flour (CBF), corn flour, and semolina to obtain instant noodles by means of a hot dry and frying process. The hot drying process was conducted at 60 °C for 4 h, and frying was conducted at 140 °C and 160 °C for 1 and 3 min. Proximate analysis, total phenolic content (TPC), the 2,2-diphenyl-1-picrylhydrazyl (DPPH) test, the oxygen radical absorbance capacity (ORAC) assay, phenolic acids and flavonoids profile by UPLC-ESI-MS/MS, the optimal cooking time (OCT), and color and texture analysis (TPA) were conducted. The general linear model and regression analysis were used. The incorporation of CBF resulted in an elevated protein content and TPC of the noodles. The noodles (hot dry) with CBF exhibited an enhanced antioxidant capacity. The adhesiveness has a direct correlation with the cinnamic, chlorogenic, and caffeic acid content (r² = 0.95 or higher), as well as an inverse relationship with the vanillic, ferulic, and sinapic acids (r² = −0.80 to −0.85). The dry hot noodles exhibited the lowest value of hardness (31.0 ± 1.5 N). The incorporation of common bean flour and corn flour enhances the nutritional profile of noodles. However, hot dry process affects their mechanical characteristics in comparison to the frying process. Full article

Asphalt binders in pavements lose their stability through aging and eventually fail in the field. Using nuclear magnetic resonance (NMR) to monitor the primary longitudinal relaxation time of asphalt samples and the ratio of material that carries this primary relaxation time has been shown to indicate the impact of ultraviolet (UV) radiation on the aging of asphalt pavements. Longitudinal NMR relaxation was used to investigate two types of proposed asphalt rejuvenators, a bio-oil-based rejuvenator and a crude-oil-based rejuvenator. Two different binders with the performance grades (PG) 64-22 and 76-22 were considered for their interactions with the rejuvenators. After 72 h of exposure to intense UV radiation, specifically designed NMR relaxometry experiments were applied to compare the rejuvenation capabilities of the two rejuvenator samples. The crude oil-based rejuvenator was found to exhibit relaxation times similar to the binder samples while the bio-based material showed relaxation times that pointed to different nuclear hydrogen environments. Both rejuvenators reduced the primary relaxation time of the PG 76-22 binder, which indicates that their stiffness was reduced. Both types of rejuvenators also seemed to prevent the effects of UV aging. Two mechanisms of rejuvenation were identified by NMR relaxometry. The primary relaxation time can be used to indicate a change in stiffness while the primary ratio of the material is tied to oxidative aging. Oxidative aging creates distinct hydrogen environments due to asphaltene aggregation. The bio-based rejuvenator only reduced the binder’s stiffness, while the crude oil-based rejuvenator also reduced the aggregation of asphaltenes. Consequently, the bio-based rejuvenator could be classified as an asphalt softener, while the oil-based material acted like a true rejuvenator. Full article

The partition coefficients of seven low molecular weight compounds were tested in different aqueous two-phase systems. The ionic composition of each system included specific salt additives, and it was found that there is a linear relationship between the solute partition coefficients and the presence of different salt additives. The study suggests that the solute structure and the type of ions influence the solute response to the ionic environment. Additionally, it was observed that the solutes’ polar surface area and the solvent-accessible surface area are the essential structural features governing partitioning in aqueous two-phase systems. Full article