Journal Description
Physchem
Physchem
is an international, peer-reviewed, open access journal on science and technology in physical chemistry published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science) and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 24.2 days after submission; acceptance to publication is undertaken in 4.9 days (median values for papers published in this journal in the second half of 2024).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Latest Articles
Enhanced Cadmium Removal by Raw Argan Shell Adsorbent: Experimental and Theoretical Investigations for Ecological Applications
Physchem 2025, 5(1), 13; https://doi.org/10.3390/physchem5010013 - 19 Mar 2025
Abstract
The removal of cadmium ions (Cd2+) using raw argan shells (ArS) was optimized through experimental and theoretical studies. Adsorption experiments revealed optimal conditions at an adsorbent dose of 3.5 g, an initial Cd2+ concentration of 20 mg·L−1, and
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The removal of cadmium ions (Cd2+) using raw argan shells (ArS) was optimized through experimental and theoretical studies. Adsorption experiments revealed optimal conditions at an adsorbent dose of 3.5 g, an initial Cd2+ concentration of 20 mg·L−1, and a pH of 8, achieving a maximum sorption capacity of 3.92 mg·g−1. The kinetic analysis showed that the adsorption followed a pseudo-second-order model (R2 = 0.98), and the Langmuir isotherm model predicted a maximum adsorption capacity of 4 mg·g−1. Thermodynamic analysis indicated an endothermic adsorption process, with ΔG° shifting from positive to negative as temperature increased, confirming that adsorption is favored at higher temperatures. Desorption studies demonstrated that HCl was the most effective eluting agent, achieving a desorption efficiency of 90.02%, followed by HNO3 (76.65%) and CH3COOH (71.59%). The varying desorption efficiencies were attributed to differences in acid strength and ionic interactions with Cd2+. This study demonstrates the potential of raw argan shells as an efficient, reusable, and sustainable biosorbent for cadmium removal, offering a promising solution for water treatment and environmental remediation.
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(This article belongs to the Section Kinetics and Thermodynamics)
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Open AccessArticle
Random Forest-Based Machine Learning Model Design for 21,700/5 Ah Lithium Cell Health Prediction Using Experimental Data
by
Sid-Ali Amamra
Physchem 2025, 5(1), 12; https://doi.org/10.3390/physchem5010012 - 16 Mar 2025
Abstract
In this research, the use of machine learning techniques for predicting the state of health (SoH) of 5 Ah—21,700 lithium-ion cells were explored; data from an experimental aging test were used to build the prediction model. The main objective of this work is
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In this research, the use of machine learning techniques for predicting the state of health (SoH) of 5 Ah—21,700 lithium-ion cells were explored; data from an experimental aging test were used to build the prediction model. The main objective of this work is to develop a robust model for battery health estimation, which is crucial for enhancing the lifespan and performance of lithium-ion batteries in different applications, such as electric vehicles and energy storage systems. Two machine learning models: support vector regression (SVR) and random forest (RF) were designed and evaluated. The random forest model, which is a novel strategy for SoH prediction application, was trained using experimental features, including current (A), potential (V), and temperature (°C), and tuned through a grid search for performance optimization. The developed models were evaluated using two performance metrics, including R2 and root mean squared error (RMSE). The obtained results show that the random forest model outperformed the SVR model, achieving an R2 of 0.92 and an RMSE of 0.06, compared to an R2 of 0.85 and an RMSE of 0.08 for SVR. These findings demonstrate that random forest is an effective and robust strategy for SoH prediction, offering a promising alternative to existing SoH monitoring strategies.
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(This article belongs to the Collection Batteries Beyond Mainstream)
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Open AccessArticle
Morphological Engineering of Battery-Type Cobalt Oxide Electrodes for High-Performance Supercapacitors
by
Boddu Haritha, Mudda Deepak, Obili M. Hussain and Christian M. Julien
Physchem 2025, 5(1), 11; https://doi.org/10.3390/physchem5010011 - 14 Mar 2025
Abstract
Nanomaterials have attracted significant attention in recent decades for their diverse applications, including energy storage devices like supercapacitors. Among these, cobalt oxide (Co3O4) nanostructures stand out due to their high theoretical capacitance, unique electrical properties, and tunable morphology. This
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Nanomaterials have attracted significant attention in recent decades for their diverse applications, including energy storage devices like supercapacitors. Among these, cobalt oxide (Co3O4) nanostructures stand out due to their high theoretical capacitance, unique electrical properties, and tunable morphology. This study explores the hydrothermal synthesis of Co3O4, revealing that the molar ratio of cobalt nitrate to potassium hydroxide significantly influences the morphology, crystal structure, and electrochemical performance. An optimized 1:1 molar ratio (COK 11) yielded well-defined cubic nanostructures with uniform elemental distribution, as confirmed by SEM, TEM, and EDS analyses. Structural characterization through XRD, XPS, and FTIR validated the formation of the Co3O4 spinel phase with distinctive lattice and surface oxygen features. Electrochemical property analysis demonstrated the superior performance of the COK 11 electrode, achieving a high specific capacity of 825 ± 3 F/g at a current density of 1 A/g, a rate capability of 56.88%, and excellent cycle stability of 88% at 3 A/g after 10,000 cycles. These properties are attributed to the nano-cubic morphology and interconnected porosity, which enhanced ion transport and active surface area. This study highlights the importance of synthesis parameters in tailoring nanomaterials for energy storage, establishing COK 11 as a promising candidate for next-generation high-performance supercapacitor applications.
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(This article belongs to the Collection Batteries Beyond Mainstream)
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Open AccessReview
Comprehensive Review of Wide-Bandgap (WBG) Devices: SiC MOSFET and Its Failure Modes Affecting Reliability
by
Ghulam Akbar, Alessio Di Fatta, Giuseppe Rizzo, Guido Ala, Pietro Romano and Antonino Imburgia
Physchem 2025, 5(1), 10; https://doi.org/10.3390/physchem5010010 - 3 Mar 2025
Abstract
Silicon carbide (SiC) MOSFETs, as a member of the emerging technology of wide-bandgap (WBG) semiconductors, are transforming high-power and high-temperature applications due to their superior electrical and thermal properties. Their potential to outperform traditional silicon-based devices, particularly in terms of efficiency and operational
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Silicon carbide (SiC) MOSFETs, as a member of the emerging technology of wide-bandgap (WBG) semiconductors, are transforming high-power and high-temperature applications due to their superior electrical and thermal properties. Their potential to outperform traditional silicon-based devices, particularly in terms of efficiency and operational stability, has made them a popular choice for power electronics. However, reliability issues about numerous failure types, including gate-oxide degradation, threshold voltage instability, and body diode degeneration, remain serious challenges. This article critically evaluates the key failure mechanisms that affect SiC MOSFET reliability and their impact on device performance. Furthermore, this paper discusses current advances in SiC technology, including both improvements and continued dependability difficulties. Key areas of future study are suggested, with an emphasis on improved material characterization, thermal management, and creative device architecture to improve SiC MOSFET performance and long-term reliability. The insights presented will help to improve the design and testing processes required for SiC MOSFETs’ widespread use in critical high-power applications.
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(This article belongs to the Section Electrochemistry)
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Open AccessArticle
Exploring the Role of pH and Solar Light-Driven Decontamination with Singlet Oxygen in Removing Emerging Pollutants from Agri-Food Effluents: The Case of Acetamiprid
by
Víctor Fabregat
Physchem 2025, 5(1), 9; https://doi.org/10.3390/physchem5010009 - 22 Feb 2025
Abstract
Previously synthesized and tested water-dispersible photoactive polymeric microparticles have been employed as heterogenous photosensitizers to evaluate their performance in generating singlet oxygen through direct solar irradiation. This study utilizes these photocatalysts for the degradation of Acetamiprid in IWWTP wastewater effluents from the Agri-food
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Previously synthesized and tested water-dispersible photoactive polymeric microparticles have been employed as heterogenous photosensitizers to evaluate their performance in generating singlet oxygen through direct solar irradiation. This study utilizes these photocatalysts for the degradation of Acetamiprid in IWWTP wastewater effluents from the Agri-food industry, exploring, in addition to direct or simulated solar irradiation, the influence of pH on the photooxidation process. Over a thousand emerging pollutants, including pesticides like Acetamiprid, have been detected in aquatic environments in recent years, posing challenges due to the limitations of current wastewater treatment technologies. The developed method is particularly effective under basic or slightly basic conditions, aligning with the natural pH of wastewater and addressing a limitation of conventional Acetamiprid degradation methods, which typically require medium acidification to be effective. Polymers P3 and P4 exhibited high photocatalytic activity, achieving over 99% degradation of Acetamiprid through oxidation via singlet oxygen generated by Rose Bengal supported on the polymer matrix, while maintaining catalytic efficiency across multiple cycles. The results confirm that Acetamiprid removal from industrial wastewater via direct solar irradiation is feasible, though constrained by the availability of sufficient effective sunlight hours.
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(This article belongs to the Section Photophysics, Photochemistry and Photobiology)
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Open AccessArticle
Molecular Determinants for the Binding of the Highly Infectious SARS-CoV-2 Omicron (BA.1) Variant to the Human ACE2 Receptor
by
Majed S. Aljohani, Pawan Bhatta and Xiche Hu
Physchem 2025, 5(1), 8; https://doi.org/10.3390/physchem5010008 - 20 Feb 2025
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continually undergoes mutation, leading to variants with altered pathogenicity and transmissibility. The Omicron variant (B.1.1.529), first identified in South Africa in 2021, has become the dominant strain worldwide. It harbors approximately 50 mutations compared to the original strain, with 15 located in the receptor-binding domain (RBD) of the spike protein that facilitates viral entry via binding to the human angiotensin-converting enzyme 2 (ACE2) receptor. How do these mutated residues modulate the intermolecular interactions and binding affinity between the RBD and ACE2? This is a question of great theoretical importance and practical implication. In this study, we employed quantum chemical calculations at the B2PLYP-D3/def2-TZVP level of theory to investigate the molecular determinants governing Omicron’s ACE2 interaction. Comparative analysis of the Omicron and wild-type RBD–ACE2 interfaces revealed that mutations including S477N, Q493R, Q498R, and N501Y enhance binding through the formation of bifurcated hydrogen bonds, π–π stacking, and cation–π interactions. These favorable interactions counterbalance such destabilizing mutations as K417N, G446S, G496S, and Y505H, which disrupt salt bridges and hydrogen bonds. Additionally, allosteric effects improve the contributions of non-mutated residues (notably A475, Y453, and F486) via structural realignment and novel hydrogen bonding with ACE2 residues such as S19, leading to an overall increase in the electrostatic and π-system interaction energy. In conclusion, our findings provide a mechanistic basis for Omicron’s increased infectivity and offer valuable insights for the development of targeted antiviral therapies. Moreover, from a methodological perspective, we directly calculated mutation-induced binding energy changes at the residue level using advanced quantum chemical methods rather than relying on the indirect decomposition schemes typical of molecular dynamics-based free energy analyses. The strong correlation between calculated energy differences and experimental deep mutational scanning (DMS) data underscores the robustness of the theoretical framework in predicting the effects of RBD mutations on ACE2 binding affinity. This demonstrates the potential of quantum chemical methods as predictive tools for studying mutation-induced changes in protein–protein interactions and guiding rational therapeutic design.
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(This article belongs to the Section Theoretical and Computational Chemistry)
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Open AccessArticle
Synthesis and Characterization of Eco-Friendly Nanocomposites Using Galactomannan and Organomodified Montmorillonite
by
Razika Saihi, Lahcene Souli, Salem Fouad Chabira, Yazid Derouiche and Ulrich Maschke
Physchem 2025, 5(1), 7; https://doi.org/10.3390/physchem5010007 - 11 Feb 2025
Abstract
Galactomannan/organomodified montmoriollonite (G1M/OM-MMT) nanocomposites and G2M/OM-MMT nanocomposites were biosynthesized using galactomannan (GM) and organomodified montmorillonite (OM-MMT) with cetyltrimethylammonium bromide (CTAB, 10−2 M) designed for antioxidant activities. Furthermore, galactomannan (GM) was isolated from fruit rind of Punica granatum grown
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Galactomannan/organomodified montmoriollonite (G1M/OM-MMT) nanocomposites and G2M/OM-MMT nanocomposites were biosynthesized using galactomannan (GM) and organomodified montmorillonite (OM-MMT) with cetyltrimethylammonium bromide (CTAB, 10−2 M) designed for antioxidant activities. Furthermore, galactomannan (GM) was isolated from fruit rind of Punica granatum grown in the Djelfa region, in Algeria, and the nanoclay used in this work was an Algerian montmorillonite. Two different types of nanocomposites were synthetized using different amounts of GM and OM-MMT (w/w) [GM1/OM-MMT (0.5:1) and GM2/OM-MMT (0.5:2)] via a solution interaction method. FTIR analysis confirmed the intercalation of GM in the interlayer of OM-MMT. Moreover, X-ray diffraction (XRD) showed that the interlayer space of OM-MMT was increased from 124.6 nm to 209.9 nm, and regarding the intercalation of GM in the OM-MMT interlayers, scanning electron microscopy (SEM) and energy-dispersive X-ray (DEX) confirmed the intercalated structure of the nanocomposites, while thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) improved the thermal stability of the synthesized bionanocomposites. The antioxidant activities of the GM1/OM-MMT nanocomposites and GM2/OM-MMT nanocomposites were evaluated with a spectrophotometer and DPPH (1,1-diphenyl-2-picrylhydrazine) radical scavenging assay. GM1/OM-MMT nanocomposites and GM2/OM-MMT nanocomposites gave good antioxidant activity. Indeed, GM1/OM-MMT had an IC50 of 0.19 mg/mL and GM2/OM-MMT an IC50 of 0.28 mg/mL.
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(This article belongs to the Section Nanoscience)
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Open AccessArticle
Cost-Effective Method for Dissolved Oxygen Sensing with Electrodeposited n-Cu2O Thin-Film Semiconductors
by
H. E. Wijesooriya, J. A. Seneviratne, K. M. D. C. Jayathilaka, W. T. R. S. Fernando, P. L. A. K. Piyumal, A. L. A. K. Ranaweera, S. R. D. Kalingamudali, L. S. R. Kumara, O. Seo, O. Sakata and R. P. Wijesundera
Physchem 2025, 5(1), 6; https://doi.org/10.3390/physchem5010006 - 8 Feb 2025
Abstract
Dissolved oxygen (DO) is a crucial parameter in water quality monitoring because it directly affects the health of aquatic ecosystems. This study explored electrodeposited Cu2O thin-film semiconductors for DO sensing. Cu2O was chosen for its low cost, eco-friendliness, and
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Dissolved oxygen (DO) is a crucial parameter in water quality monitoring because it directly affects the health of aquatic ecosystems. This study explored electrodeposited Cu2O thin-film semiconductors for DO sensing. Cu2O was chosen for its low cost, eco-friendliness, and non-toxic nature. Cu2O films were electrodeposited on titanium (Ti) substrates using an acetate bath (0.1 M sodium acetate and 0.01 M cupric acetate) at −200 mV versus Ag/AgCl for 30 min, with a bath temperature of 55 °C, stirred at 50 rpm. The bath pH was systematically adjusted from 5.8 to 6.8 in 0.2 steps using NaOH and Acetic acid. A range of analyses including synchrotron X-ray diffraction (SXRD), scanning electron microscopy (SEM), surface wettability, capacitance–voltage (C-V), Raman spectroscopy, Fourier-transform infrared (FTIR) spectrum, and Electrochemical Impedance Spectroscopy (EIS) was performed to assess their properties and sensing performance. The results showed that Cu2O films deposited at pH 6.4 exhibited optimal performance for DO sensing, with a strong linear response, marking this pH, deposition time, and temperature as ideal for creating effective DO sensors. This study introduces a novel, cost-effective approach to dissolved oxygen sensing using electrodeposited n-Cu2O thin-film semiconductors, marking the first application of this material in such sensors and showcasing its potential for scalable and environmentally sustainable sensing technologies.
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(This article belongs to the Section Electrochemistry)
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Open AccessArticle
Artificial Neural Networks for the Simulation and Modeling of the Adsorption of Fluoride Ions with Layered Double Hydroxides
by
Julio Cesar Estrada-Moreno, Eréndira Rendón-Lara, María de la Luz Jiménez-Núñez and Jacob Josafat Salazar Rábago
Physchem 2025, 5(1), 5; https://doi.org/10.3390/physchem5010005 - 23 Jan 2025
Abstract
Adsorption is a complex process since it is affected by multiple variables related to the physicochemical properties of the adsorbate, the adsorbent and the interface; therefore, to understand the adsorption process in batch systems, kinetics, isotherms empiric models are commonly used. On the
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Adsorption is a complex process since it is affected by multiple variables related to the physicochemical properties of the adsorbate, the adsorbent and the interface; therefore, to understand the adsorption process in batch systems, kinetics, isotherms empiric models are commonly used. On the other hand, artificial neural networks (ANNs) have proven to be useful in solving a wide variety of complex problems in science and engineering due to their combination of computational efficiency and precision in the results; for this reason, in recent years, ANNs have begun to be used for describing adsorption processes. In this work, we present an ANN model of the adsorption of fluoride ions in water with layered double hydroxides (LDHs) and its comparison with empirical kinetic adsorption models. LHD was synthesized and characterized using X-Ray diffraction, FT-Infrared spectroscopy, BET analyses and zero point of charge. Fluoride ion adsorption was evaluated under different experimental conditions, including contact time, initial pH and initial fluoride ion concentration. A total of 262 experiments were conducted, and the resulting data were used for training and testing the ANN model. The results indicate that the ANN can accurately forecast the adsorption conditions with a determination coefficient of 0.9918.
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(This article belongs to the Section Application of New Technologies: Artificial Intelligence, Virtual Reality, Quantum Computing and Machine Learning)
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Open AccessArticle
On the Sufficiency of a Single Hidden Layer in Feed-Forward Neural Networks Used for Machine Learning of Materials Properties
by
Ye Min Thant, Sergei Manzhos, Manabu Ihara and Methawee Nukunudompanich
Physchem 2025, 5(1), 4; https://doi.org/10.3390/physchem5010004 - 16 Jan 2025
Cited by 1
Abstract
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
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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.
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(This article belongs to the Section Application of New Technologies: Artificial Intelligence, Virtual Reality, Quantum Computing and Machine Learning)
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Open AccessArticle
The Modeling of Perovskite Materials CsPbX3 (X = I, Br) by Changing the Concentration of Halide: Experimental and DFT Study
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Alicja Mikłas, Zbigniew Starowicz, Marek Lipiński, Marek J. Wójcik, Takahito Nakajima and Mateusz Z. Brela
Physchem 2025, 5(1), 3; https://doi.org/10.3390/physchem5010003 - 7 Jan 2025
Abstract
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. CsPbBr
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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 CsPbBrxI3−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 CsPbBrxI3x perovskites.
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(This article belongs to the Section Solid-State Chemistry and Physics)
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Open AccessReview
An Approach to Monodisperse Polymeric Particles as Matrices for Immobilization of Biosystems
by
Mariana P. Cabrera, Geraldo V. de Lima Júnior, William S. Soares, Luiz B. Carvalho Júnior, Carlos Yure B. Oliveira, Evando S. Araújo and David F. M. Neri
Physchem 2025, 5(1), 2; https://doi.org/10.3390/physchem5010002 - 2 Jan 2025
Abstract
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
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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.
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(This article belongs to the Section Surface Science)
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Atomic-Scale Study of NASICON Type Electrode Material: Defects, Dopants and Sodium-Ion Migration in Na3V2(PO4)3
by
Vijayabaskar Seshan, Poobalasuntharam Iyngaran, Poobalasingam Abiman and Navaratnarajah Kuganathan
Physchem 2025, 5(1), 1; https://doi.org/10.3390/physchem5010001 - 30 Dec 2024
Abstract
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),
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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.
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(This article belongs to the Collection Batteries Beyond Mainstream)
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Open AccessArticle
Magnetite Thin Films by Solvothermal Synthesis on a Microstructured Si Substrate as a Model to Study Energy Storage Mechanisms of Supercapacitors
by
Karina Chavez and Enrique Quiroga-González
Physchem 2024, 4(4), 536-547; https://doi.org/10.3390/physchem4040037 - 12 Dec 2024
Abstract
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
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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.
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(This article belongs to the Collection Batteries Beyond Mainstream)
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Open AccessArticle
Pagodane—Solution and Solid-State Vibrational Spectra
by
Stewart F. Parker, Hannah E. Mason, Campbell T. Wilson and Adam J. Jackson
Physchem 2024, 4(4), 524-535; https://doi.org/10.3390/physchem4040036 - 6 Dec 2024
Abstract
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.
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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 D2h symmetry, which is reduced to Ci 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 D2hAu modes that are forbidden in the isolated molecule but become allowed in the solid state. These have been located in the solid-state spectra.
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(This article belongs to the Section Experimental and Computational Spectroscopy)
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Open AccessArticle
Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects
by
Mohsen Dehghanpour Abyaneh, Parviz Narimani, Mohammad Sadegh Javadi, Marzieh Golabchi, Samareh Attarsharghi and Mohammadjafar Hadad
Physchem 2024, 4(4), 495-523; https://doi.org/10.3390/physchem4040035 - 3 Dec 2024
Abstract
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
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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.
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(This article belongs to the Section Application of New Technologies: Artificial Intelligence, Virtual Reality, Quantum Computing and Machine Learning)
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Substituent Effects on the Photophysical Properties of a Series of 8(meso)-Pyridyl-BODIPYs: A Computational Analysis of the Experimental Data
by
Petia Bobadova-Parvanova, Dylan Goliber, Elijuah Hernandez, Daniel LaMaster and Maria da Graça H. Vicente
Physchem 2024, 4(4), 483-494; https://doi.org/10.3390/physchem4040034 - 29 Nov 2024
Abstract
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
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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.
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(This article belongs to the Section Photophysics, Photochemistry and Photobiology)
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Open AccessArticle
Mitigation of Acid Mine Drainage Using Blended Waste Rock in Near-Equatorial Climates—Geochemical Analysis and Column Leaching Tests
by
Akihiro Hamanaka, Takashi Sasaoka, Hideki Shimada, Shinji Matsumoto, Ginting Jalu Kusuma and Mokhamad Candra Nugraha Deni
Physchem 2024, 4(4), 470-482; https://doi.org/10.3390/physchem4040033 - 28 Nov 2024
Abstract
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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
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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.
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Open AccessArticle
Temperature-Induced Phase Transformations in Tutton Salt K2Cu(SO4)2(H2O)6: Thermoanalytical Studies Combined with Powder X-Ray Diffraction
by
João G. de Oliveira Neto, Ronilson S. Santos, Kamila R. Abreu, Luzeli M. da Silva, Rossano Lang and Adenilson O. dos Santos
Physchem 2024, 4(4), 458-469; https://doi.org/10.3390/physchem4040032 - 16 Nov 2024
Cited by 2
Abstract
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
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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.
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(This article belongs to the Section Solid-State Chemistry and Physics)
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Low-Temperature Metallomesogen Model Structures and Mixtures as Potential Materials for Application in Commercial Liquid Crystal Devices
by
Hassanali Hakemi
Physchem 2024, 4(4), 447-457; https://doi.org/10.3390/physchem4040031 - 5 Nov 2024
Cited by 1
Abstract
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
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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.
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(This article belongs to the Section Physical Organic Chemistry)
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