Periodic Table Research Articles

The Impacts of Beaver Dams on Groundwater Regime and Habitat 6510

Changes in land usage, increasing climatic uncertainty, and dynamic development of the rate of natural population growth of the Eurasian beaver will lead to increasing benefits and disadvantages from beaver activity. During three growing seasons from 2020 to 2022, four cross-sections were marked on unused sub-irrigation systems with the periodic occurrence of beaver dams, located on organic soils in parts of the facility protected by the Habitats Directive (natural habitat 6510) in Central Poland. Periodic water table measurements in wells, the beds of adjacent ditches, and the riverbed were carried out. Identification of the states and structures of plant communities was done using the botanical-weight analysis of several samples with an area of 1 m2. Beaver dams increased water levels in the river, ditches, and groundwater depth in over 78% of events in 2020–2022 years. A large impact of precipitation on the hydraulic conditions in the meadow was observed. In the studied area, since a moderately moist habitat (6510) is protected within the Natura 2000 network, phenomena increasing soil moisture, in the absence of mowing of meadows and the occurrence of expansive herbaceous vegetation that tolerates increased moisture, may lead to the disappearance of these habitats, especially in the zone near the riverbed.

The Effects of Bisphenol A and its Analogs on Steroidogenesis in MA-10 Leydig Cells and KGN Granulosa Cells†.

Bisphenols are a family of chemicals used in the manufacture of consumer products containing polycarbonate plastics and epoxy resins. Studies have shown that exposure to bisphenol A (BPA) may disrupt steroidogenesis and induce adverse effects on male and female reproduction, but little is known about BPA replacements. We determined the effects of six bisphenols on the steroidogenic function of MA-10 Leydig cells and KGN granulosa cells by measuring the levels of progesterone and estradiol produced by these cells as well as the expression of transcripts involved in steroid and cholesterol biosynthesis. MA-10 and KGN cells were exposed for 48hours to one of six bisphenols (0.01-50μM): BPA, bisphenol F, bisphenol S, bisphenol AF, bisphenol M, or bisphenol TMC under both basal and dibutyryl cAMP (Bu2cAMP)-stimulated conditions. In MA-10 cells, most bisphenols increased the Bu2cAMP-stimulated production of progesterone. In KGN cells, there was a general decrease in progesterone production, while estradiol levels were increased following exposure to many bisphenols. qRT-PCR analyses revealed that all six bisphenols (≥1μM) upregulated the expression of STAR, a cholesterol transporter, in both cell lines after stimulation. Key transcripts directly involved in steroid and cholesterol biosynthesis were significantly altered in a cell line, chemical, and concentration-dependent manner. The expression of upstream genes was also differentially affected. Thus, BPA and five of its analogs can disrupt steroid production in two steroidogenic cell lines and alter the levels of transcripts involved in this process. Importantly, BPA replacements do not appear to have fewer effects than BPA.

Exploring Chemistry Confusions and Misconceptions in Nepalese Secondary Education

This study investigates the confusions and misconceptions in chemistry of ninth and tenth graders in Nepal. The primary objectives were to identify misconceptions in various areas of chemistry, determine their sources, and understand teachers' perceptions of these misconceptions. A concurrent mixed-method research design was employed, utilizing questionnaires and interviews for data collection. A random sample of 120 students from Grades 9 and 10 participated in the study. The findings revealed significant misconceptions in areas such as chemical reactions and stability, chemical equations, acids, bases and salts, and the periodic table. The main sources of these misconceptions were identified as common sense, textbooks, and teachers. The study highlights the importance of addressing these misconceptions to improve chemistry education. It provides valuable insights for future research, aiding in the planning and development of theoretical and conceptual frameworks to better understand and mitigate misconceptions in chemistry education.

Spin-based Atomic Periodic Model—Beyond the Periodic Table

The present article explores the potential re-arragement of all the periodic elements in terms of the spin of their valence electron, modeling them as up-spin or down-spin pointing triangles that together result in larger triangles precluding subshells, shells and the whole electron cloud (as a spin-balanced whole). Stratification of the elements according to their ratio of principal to azimuthal quantum number creates different angular cones, that not only align the elements into a compliante alternative interpretation to Mandelung’s rule, but ultimately result in a three dimensional periodic structure (that fans out and grows radially from the nucleus), resembling the shape of a flower. The model’s energetic umbrella predicts the elements Ununennium and Unbinilium. Electrical and thermal conductivities are mapped onto the new model, suggesting the existance of an instability (peak in 2D or axis in 3D) that governs the (non-) metal nature of the elements.

Metal Ions’ Dynamic Effect on Metal-Assisted Catalyzed Etching of Silicon in Acid Solution

Metal-assisted catalyzed etching (MACE) technology is convenient and efficient for fabricating large-area silicon nanowires at room temperature. However, the mechanism requires further exploration, particularly the dynamic effect of various ions in the acid-etching solution. This paper investigated the MACE of silicon wafers predeposited with metal nanofilms in an HF-M(NO3)x-H2O etching solution (where M(NO3)x is the nitrate of the fourth-period elements of the periodic table). The oxidizing ability of Fe3+ and NO3− was demonstrated, and the dynamic influence of metal ions on the etching process was discussed. The results show that the MACE of silicon can be realized in various HF-M(NO3)x-H2O etching solutions, such as KNO3, Al(NO3)3, Cr(NO3)3, Mn(NO3)2, Ni(NO3)2, Co(NO3)2, HNO3, and Ca(NO3)2. It is confirmed that the concentration and type of cations in the etching solution affect the etching rate and morphology of silicon. Fe3+ and NO3− act as oxidants in catalytic etching. The fastest etching rate is about 5~6 μm/h in Ni(NO3)2, Co(NO3)2, and Ca(NO3)2 etching solutions. However, a high concentration of K+ hinders silicon etching. This study expands the application of MACE etching solution systems.

First principles study of the electronic and mechanical properties of a porous carbon

Carbon is a versatile element in the periodic table, which can form many allotropes with various properties in nature. In this work, the electronic and mechanical properties of a low energy porous carbon, a topological nodal line material, are studied by first principles method. Elastic and dynamical stabilities under hydrostatic pressure are investigated, which reveal that the dynamical instability occurs first. It is a material with negative linear compressibility along the a axis. Tension and compression strains are applied in different crystal orientations to obtain the corresponding stresses. The results indicate that the c axis can endure the smallest strains, the a axis can withstand moderate ones while the b axis can bear the largest ones, however, the resulted stresses have very different behaviors. Shear strains are exerted on different crystal planes to see the corresponding mechanical responses, which uncover that the (100,010] shear pattern has the lowest critical stress than other shear patterns. The crystal structure, dynamical stability, and electron density difference under the critical strains are checked. The reasons for the different mechanical behaviors under pressure and strain are proposed. The effects of pressure and strain on its topological property are also studied.

A Large Atomic Partition Model for Materials Discovery

Accurate and efficient prediction of benchmark properties is essential to the discovery of diverse functional materials, but searching vast element combinatorial and bonding configurational spaces presents formidable challenges to current computational techniques. Here, we devise a large atomic partition (LAP) model featuring a scheme to partition material properties into constituent atomic attributes, which are validated by a data-driven calibration procedure and assigned to elements across the periodic table, then utilized as raw ingredients to assemble and assess targeted properties of new materials. Distinct subtypes are designated for each element based on local atomic environments such as coordination number and valence state, and the parameter count of the LAP model can be tuned widely to tailor prediction accuracy and computational efficiency. As demonstrative case studies, we explore volumetric cohesive energy, bulk modulus, and shear modulus, and the results showcase superior accuracy, efficiency, universality, and interpretability of the LAP model compared to alternative approaches. Moreover, based on the predicted elastic moduli, we discovered a series of rare and highly sought-after compounds exhibiting concurrent superior hardness and toughness, highlighting the promise of the LAP model in high-throughput screening for advanced materials with targeted outstanding functionalities.

A Trp-574-Leu mutation in acetolactate synthase confers imazamox resistance in barnyardgrass (Echinochloa crus-galli) from China

Abstract Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] is increasingly infesting imidazolinone-tolerant (IMI-T) rice fields in China, imazamox resistance of E. crus-galli has become the major concern for weed management in IMI-T rice fields. In this study, the susceptible population JLGY-3 (S) and the suspected resistant population JHXY-2 (R) collected from IMI-T rice fields were used as research subjects. When treated with imazamox, JHXY-2 (R) population showed a high level of herbicide resistance with a resistance index (RI) of 31.2. JHXY-2 (R) was cross-resistant to all five acetolactate synthase (ALS) inhibitors from different chemical families, but sensitive to herbicides inhibiting acetyl-CoA carboxylase (ACCase). In order to understand the reason why JHXY-2 (R) was resistant to imazamox, we performed experiments to characterize potential TSR and NTSR mechanisms. A trp-574-leu amino acid mutation in ALS and low imazamox ALS sensitivity were the main mechanism underlying imazamox resistance in this JHXY-2 (R) population. There was no significant difference in ALS gene expression and ALS protein abundance between R and S populations. High-performance liquid chromatography-tandem mass spectrometry analysis showed enhanced metabolism of imazamox in JHXY-2 (R), which was in contrast to the results of pretreatment with a metabolic enzyme inhibitor. Treatments with the P450/GST inhibitors did not alter the resistance level of JHXY-2 (R) against imazamox. To further clarify the NTSR mechanism of JHXY-2 (R), transcriptome sequencing showed that there was almost no significant difference in the expression of P450 and GST metabolic enzyme genes between R and S populations, and only GST-U1 showed a significant induction in R population. In conclusion, amino acid mutation and higher enzyme activity of ALS are the main causes of imazamox resistance in JHXY-2 (R). However, given the differences in imazamox residues in the leaves of the E. crus-galli, there may still be undetectable NTSR that are causing imazamox resistance in the R population.

Mechanical Properties of Two-Dimensional Metal Nitrides: Numerical Simulation Study.

It is expected that two-dimensional (2D) metal nitrides (MNs) consisting of the 13th group elements of the periodic table and nitrogen, namely aluminium nitride (AlN), gallium nitride (GaN), indium nitride (InN) and thallium nitride (TlN), have enhanced physical and mechanical properties due to the honeycomb, graphene-like atomic arrangement characteristic of these compounds. The basis for the correct design and improved performance of nanodevices and complex structures based on 2D MNs from the 13th group is an understanding of the mechanical response of their components. In this context, a comparative study to determine the elastic properties of metal nitride nanosheets was carried out making use of the nanoscale continuum modelling (or molecular structural mechanics) method. The differences in the elastic properties (surface shear and Young's moduli and Poisson's ratio) found for the 2D 13th group MNs are attributed to the bond length of the respective hexagonal lattice of their diatomic nanostructure. The outcomes obtained contribute to a benchmark in the evaluation of the mechanical properties of AlN, GaN, InN and TlN monolayers using analytical and numerical approaches.

Alchemical insights into approximately quadratic energies of iso-electronic atoms.

Accurate quantum mechanics based predictions of property trends are so important for material design and discovery that even inexpensive approximate methods are valuable. We use the alchemical integral transform to study multi-electron atoms and to gain a better understanding of the approximately quadratic behavior of energy differences between iso-electronic atoms in their nuclear charges. Based on this, we arrive at the following simple analytical estimate of energy differences between any two iso-electronic atoms, ΔE≈-(1+2γNe-1)ΔZZ̄. Here, γ ≈ 0.3766 ± 0.0020 Ha corresponds to an empirical constant, and Ne, ΔZ, and Z̄, respectively, to electron number, nuclear charge difference, and average. We compare the formula's predictive accuracy using experimental numbers and non-relativistic, numerical results obtained via density functional theory (pbe0) for the entire periodic table up to Radon. A detailed discussion of the atomic helium-series is included.

XElemNet: towards explainable AI for deep neural networks in materials science

Recent progress in deep learning has significantly impacted materials science, leading to accelerated material discovery and innovation. ElemNet, a deep neural network model that predicts formation energy from elemental compositions, exemplifies the application of deep learning techniques in this field. However, the “black-box” nature of deep learning models often raises concerns about their interpretability and reliability. In this study, we propose XElemNet to explore the interpretability of ElemNet by applying a series of explainable artificial intelligence (XAI) techniques, focusing on post-hoc analysis and model transparency. The experiments with artificial binary datasets reveal ElemNet’s effectiveness in predicting convex hulls of element-pair systems across periodic table groups, indicating its capability to effectively discern elemental interactions in most cases. Additionally, feature importance analysis within ElemNet highlights alignment with chemical properties of elements such as reactivity and electronegativity. XElemNet provides insights into the strengths and limitations of ElemNet and offers a potential pathway for explaining other deep learning models in materials science.

A Natural Event of Radioactivity

Abstract Natural radioactivity was first discovered in 1896 by the French physicist Beck Kerelem. As a result of recent research, Pierre and Marie Curie discovered that the nucleus of atoms of some elements spontaneously transforms into the nucleus of atoms of other elements, and during this, the radiation of particles occurs. Most naturally occurring radioactive elements form a radioactive family in which each radioactive element originates from the preceding radioactive element and in turn transforms into the next radioactive element. The transformations continue until the end product is an isotope of a stable element. In nature, there are also radioactive elements that this transformation occurs only once . In 1934, French scientists Irene and Fredrik Joluo-Curie irradiated aluminum, boron and manganese with particles and obtained isotopes of phosphorus, nitrogen and silicon elements, which do not exist in nature. This type of radioactivity is called artificial radioactivity. Later, by irradiating various elements with proton, deuteron and neutron particles, they obtained isotopes of all chemical elements in the Mendeleev table.

Genome-Wide Identification of MKK Gene Family and Response to Hormone and Abiotic Stress in Rice.

Mitogen-activated protein kinase (MAPK/MPK) cascades are pivotal and highly conserved signaling modules widely distributed in eukaryotes; they play essential roles in plant growth and development, as well as biotic and abiotic stress responses. With the development of sequencing technology, the complete genome assembly of rice without gaps, T2T (Telomere-to-Telomere)-NIP (version AGIS-1.0), has recently been released. In this study, we used bioinformatic approaches to identify and analyze the rice MPK kinases (MKKs) based on the complete genome. A total of seven OsMKKs were identified, and their physical and chemical properties, chromosome localization, gene structure, subcellular localization, phylogeny, family evolution, and cis-acting elements were evaluated. OsMKKs can be divided into four subgroups based on phylogenetic relationships, and the family members located in the same evolutionary branch have relatively similar gene structures and conserved domains. Quantitative real-time PCR (qRT-PCR) revealed that all OsMKKs were highly expressed in rice seedling leaves. The expression levels of all OsMKKs were more or less altered under exogenous hormone and abiotic stress treatments, with OsMKK1, OsMKK6, and OsMKK3 being induced under almost all treatments, while the expression of OsMKK4 and OsMKK10-2 was repressed under salt and drought treatments and IAA treatment, respectively. In this study, we also summarized the recent progress in rice MPK cascades, highlighted their diverse functions, and outlined the potential MPK signaling network, facilitating further studies on OsMKK genes and rice MPK cascades.

Students’ Ability to Work with the Periodic Table: The Use of Three-Tier Tasks

Students’ Ability to Work with the Periodic Table: The Use of Three-Tier Tasks

High-order harmonic generation in the laser-induced plasmas produced on the surfaces of transition metals (Rh, Ru, Nb, and Zr) from the fifth period of periodic table

High-order harmonic generation in the laser-induced plasmas produced on the surfaces of transition metals (Rh, Ru, Nb, and Zr) from the fifth period of periodic table

VOCs conversion in He/H2O plasma produced in a micro-capillary tube at atmospheric pressure

Abstract A non-equilibrium plasma is created in a micro-capillary quartz tube (800 µm of internal diameter), by a DC-pulsed micro-dielectric barrier discharge (micro-DBD) and the propagation of an ionisation wave, in mixtures of He/H2O/VOC at atmospheric pressure where the studied volatile organic compounds (VOCs) are representative of molecules belonging to different chemical families: alcohols (methanol, ethanol, isopropanol, tert-butanol), ketones (acetone), nitriles (acetonitrile), and aromatic hydrocarbons (toluene). The conversion efficiency of these VOCs is studied as a function of the applied voltage on the micro-DBD (or electrical energy deposited in the plasma) and of the initial concentration of the molecules in the range from 1 ppm up to 3000 ppm (depending on the molecule), with the help of high-resolution real-time mass spectrometry Fourier transform ion cyclotron resonance associated to chemical ionisation (CI-FTICR) using H3O+ as precursor ion. A variety of by-products resulting from the conversion of VOCs are identified and quantified, emphasising that the micro-capillary plasma is able to induce a complex chemical reactivity. A qualitative analysis of the involved kinetics, based on the existing literature, reveals that helium species (ions and metastable states) and radicals coming from the dissociation of the water molecules (O and OH) are the most probable candidates to explain the formation of all compounds detected by the CI-FTICR apparatus. Quenching processes of the metastable He(23S) by the VOCs, leading to the dissociation of the molecules, are suggested to explain some of the experimental results.

Heterometallic Molecular and Ionic Isomers.

Numerous descriptions of structural isomerism in metal complexes do not list any molecular vs ionic isomers. At the same time, one of the most striking examples of structural isomerism in organic chemistry is molecular urea, which has the same atomic composition as the chemically distinct ionic ammonium cyanate. This iconic organic couple now meets its inorganic heterometallic counterpart. We introduce a new class of structural isomers, molecular vs ionic, that can be consummated in complex and coordinatively unsaturated polynuclear/heterometallic compounds. We report inorganic molecular and ionic isomers of the composition [NaCrFe (acac)3(hfac)3] (acac = acetylacetonate; hfac = hexafluoroacetylacetonate). Heterometallic molecular [CrIII(acac)3-Na-FeII(hfac)3] (1m) and ionic {[CrIII(acac)3-Na-CrIII(acac)3]+[FeII(hfac)3-Na-FeII(hfac)3]-} (1i) isomers have been isolated in pure form and characterized. While both ions are heterobimetallic trinuclear entities, the neutral counterpart is a heterotrimetallic trinuclear molecule. The two isomers exhibit distinctly different characteristics in terms of solubility, volatility, mass spectrometry ionization, and thermal behavior. Unambiguous assignment of the positions and oxidation/spin states of the Periodic Table neighbors, Fe and Cr, in both isomers have been made by a combination of characterization techniques that include synchrotron X-ray resonant diffraction, synchrotron X-ray fluorescence spectroscopy, Mössbauer spectroscopy, and DART mass spectrometry. The transformation between the two isomers that does take place in solutions of noncoordinating solvents has also been tested.

Metal single-atom interaction with graphitic C3N4 surface based on density functional theory calculations and linear regression analysis

This paper discusses the adsorption of metal single-atoms (SAs) on graphitic C3N4 (gCN) multilayered surface models based on density functional theory (DFT) calculations. We systematically searched stable adsorption sites on gCN and showed that the cavity site is preferred for metal SAs. We also discussed the usefulness of several descriptors, such as the distance between the SA and gCN, charge donation (electron transfer), and atomic radius, for evaluating the SA adsorption energy, based on the linear regression method. In addition, the most stable adsorption energy for fifth- and sixth-row metals can be predicted using only the “group” descriptor of the periodic table. The group descriptor is closely related to the atomic radius, and hence the stability of fifth- and sixth-row metals is determined from the fit between the SA radius and the gCN cavity size. The study findings facilitate the development of various metal-dopant techniques for gCN-based applications.

A Microbial Cocaine Bioreporter

The continuous emergence of new illegal compounds, particularly psychoactive chemicals, poses significant challenges for current drug detection methods. Developing new protocols and kits for each new drug requires substantial time, effort, and dedicated manpower. Whole-cell bacterial bioreporters have been proven capable of detecting diverse hazardous compounds in both laboratory and field settings, identifying not only single compounds but also chemical families. We present the development of a microbial bioreporter for the detection of cocaine, the nervous system stimulant that is the second-most widely used illegal drug in the US. Escherichia coli was transformed with a plasmid containing a bacterial luxCDABEG bioluminescence gene cassette, activated by a cocaine-responsive signaling cascade. The engineered bioreporter is demonstrated to be a sensitive and specific first-generation detection system for cocaine, with detection thresholds of 17 ± 8 μg/L and 130 ± 50 μg/L in a buffer solution and in urine, respectively. Further improvement of the sensor’s performance was achieved by altering the nucleotide sequence of the PBen gene promoter, the construct’s sensing element, using accelerated site-directed evolution. The applicability of ready-to-use paper strips with immobilized bioreporter cells was demonstrated for cocaine detection in aqueous solutions.

Metallization of Hydrogen Under High Pressure: Challenges and Experimental Progress

AbstractHydrogen, the first element in the periodic table, is predicted to become metallic at extremely high‐pressure conditions. Solid metallic hydrogen is believed to possess extraordinary physical properties, such as room‐temperature superconductivity and superfluidity, earning it the title of the “holy grail” in high‐pressure research. The pursuit of solid metallic hydrogen has spanned nine decades. Despite numerous fascinating discoveries related to dense hydrogen, metallic hydrogen has yet to be experimentally realized. This article aims to provide an overview of the major progress made in this field and offers an outlook on future developments.