Electron Affinities Of Atoms Research Articles

Exploring the Trends and Patterns in Periodicity of Elements: from Mendeleev to Modern Periodic Table

Dmitri Mendeleev created the periodic table in 1869, and it has undergone significant modifications to become an essential tool in chemical science today. This abstract provides an informative summary of the evolution of periodic trends and patterns, from Mendeleev's work to the latest complexities in the current periodic table. The first step towards comprehending the periodicity of elements was Mendeleev's periodic table, which he offered as a means of classifying elements according to their atomic weights and chemical behaviours. The periodic table underwent additions and modifications during the ensuing decades as atomic theory and experimental methods advanced. Instead of focusing on atomic weights, the current periodic law is concerned with the precise atomic number. Henry Moseley's discovery of the atomic number altered the elemental positions. This modification allowed for a deeper examination of periodic trends between elements by clarifying elemental relationships. Periodic trend analysis takes into account several characteristics, such as atomic radius, ionisation energy, electron affinity, and electronegativity. This is evident from the fact that each group of elements, ranging from noble gases to alkali metals, has distinct tendencies in both physical and chemical properties. We gathered the necessary materials for this review from a variety of reliable sources, including physical chemistry by K. K. Sharma, inorganic chemistry by J. D. Lee, and other published works. In conclusion, Mendeleev's table's evolution to its current state demonstrates that scientists have been addressing the issue for many generations. The periodic table is still a vital tool for classifying and evaluating the wide range of elements and their characteristics, although there are still many uncharted territories in chemistry. Keywords: electronic configuration, group analysis, periodic trend, periodicity, atomic number, and quantum physics.

A fluorine-based strong and healable elastomer with unprecedented puncture resistance for high performance flexible electronics

There is usually a trade-off between high mechanical strength and dynamic self-healing because the mechanisms of these properties are mutually exclusive. Herein, we design and fabricate a fluorinated phenolic polyurethane (FPPU) elastomer based on octafluoro-4,4′-biphenol to overcome this challenge. This fluorine-based motif not only tunes interchain interactions through π−π stacking between aromatic rings and free-volume among polymer chains but also improves the reversibility of phenol-carbamate bonds via electron-withdrawing effect of fluorine atoms. The developed FPPU elastomer shows the highest recorded puncture energy (648.0 mJ), high tensile strength (27.0 MPa), as well as excellent self-healing efficiency (92.3%), along with low surface energy (50.9 MJ m−2), notch-insensitivity, and reprocessability compared with non-fluorinated counterpart biphenolic polyurethane (BPPU) elastomer. Taking advantage of the above-mentioned merits of FPPU elastomer, we prepare an anti-fouling triboelectric nanogenerator (TENG) with a self-healable, and reprocessable elastic substrate. Benefiting from stronger electron affinity of fluorine atoms than hydrogen atoms, this electronic device exhibits ultrahigh peak open-circuit voltage of 302.3 V compared to the TENG fabricated from BPPU elastomer. Furthermore, a healable and stretchable conductive composite is prepared. This research provides a distinct and general pathway toward constructing high-performance elastomers and will enable a series of new applications.

Unveiling the physical mechanisms driving delafossite crystal (ABX2) formation through interpretable machine learning.

A method integrating machine learning with first-principles calculations is employed to forecast the formation energy of delafossite crystals, facilitating the rapid identification of stable crystals. This approach identifies several stable candidates and highlights the importance of atomic ionization energy and electron affinity in the formation of delafossite crystals.

Predicting the critical superconducting temperature using the random forest, MLP neural network, M5 model tree and multivariate linear regression

Using a random forest regression (RFR) machine learning technique, the critical temperature (Tc) of a superconductor was predicted in the context of Industry 4.0 in this study using features derived from the material's physico-chemical properties, containing atomic mass, electron affinity, atomic radius, valence, and thermal conductivity. The same experimental data were also fitted with multilayer perceptron (MLP) artificial neural networks (ANN), M5 model tree and multivariate linear regression (MLR) model for comparison. The current investigation's findings show that the proposed RFR–relied model can successfully forecast the critical temperature of a superconductor. Additionally, the Tc estimate was reached with a correlation coefficient of 0.9565 and a coefficient of determination 0.9146, when the observed dataset was used to test this unique technique. Additionally, the outcomes from the MLP, M5, and MLR models are obviously worse than those from the RFR–relied model. When it comes to fully comprehending the superconductivity, this investigation is noteworthy. Regarding forecasting effectiveness and feature reduction rate, the RFR approach has obvious advantages and generalizability, and it also demonstrates suitability for high-temperature superconductor Tc forecasting. In fact, it offers a practical and affordable approach to data-driven superconductor investigation.

Accurate Ionization Potentials, Electron Affinities, and Band Gaps from the ωLH22t Range-Separated Local Hybrid Functional: No Tuning Required.

The optimal tuning (OT) of range-separated hybrid (RSH) functionals has been proposed as the currently most accurate DFT-based way to compute the relevant quantities required for charge-transfer processes in organic chromophores used in organic photovoltaics and related fields. The main drawback of OT-RSHs is that the system-specific tuning of the range-separation parameter is not size-consistent. It therefore also lacks transferability, e.g., when considering processes involving orbitals not involved in the tuning or for reactions between different chromophores. Here we show that the recently reported ωLH22t range-separated local hybrid functional provides ionization energies, electron affinities, and fundamental gaps on par with OT-RSH treatments, approaching the quality of GW results, without any need for system-specific tuning. This holds from relevant organic chromophores of varying sizes all the way to atomic electron affinities. ωLH22t also gives excellent outer-valence quasiparticle spectra and is a generally accurate functional for both main-group and transition-metal energetics, as well as for a variety of excitation types. Range-separated local hybrid functionals are suggested as promising new quantum-chemical tools in molecular electronics.

Electron affinities in the periodic table and an example for As

Based on our previous analysis of electron affinities of atoms and structures of atomic negative ions [J. Phys. Chem. Ref. Data 51, 021502 (2022)], this review provides a concise presentation of the electron affinities of atoms. We briefly describe and compare three commonly used experimental methods for determining electron affinities to highlight their respective advantages and disadvantages. To illustrate the features of the slow electron velocity-map imaging method utilized in our current study, we conducted measurements on the electron affinity of As and excited states of its anion. The electron affinity of As was determined to be 6488.61(5) cm−1 or 0.804485(6) eV. The fine structures of As− were well resolved, with values of 1029.94(18) cm−1 or 0.12770(3) eV for 3P1 and 1343.04(55) cm−1 or 0.16652(7) eV for 3P0 above the ground state 3P2, respectively.

Electron Affinities of Atoms and Structures of Atomic Negative Ions

This Review presents electron affinities of atoms and structures of atomic negative ions. The negative ion properties of many elements in the main groups of the Periodic Table were well known in the late 20th century. However, our knowledge of the atomic negative ions of transitional elements, lanthanides, and actinides was completely lacking or largely rather qualitative at that time. Substantial progress both on experimental and theoretical sides in this subject has happened during the last two decades. New developments in the experimental methods that yield accurate electron affinities are described in this Review. Based on the previous reviews, a survey of the electron affinity toward the completion of the Periodic Table is presented. A set of atomic electron affinities and energy levels of atomic anions is recommended.

Benchmarking ANO-R basis set for multiconfigurational calculations

The selection of basis sets is very important for multiconfigurational wave function calculation, due to a balance between a desired accuracy and computational costs. Recently, the atomic natural orbital-relativistic (ANO-R) basis set was published as a suggested replacement for the ANO-RCC basis set for scalar-relativistic correlated calculations Zobel et al (2021 J. Chem. Theory Comput. 16 278–294). Benchmarking ANO-R basis set against ANO-RCC for atoms (from H to Rn) and their compounds is the goal of this study. Many of these compounds (for instance, diatomic molecules containing transition metals) have open shells, for which reason a multiconfigurational approach is necessary and was primarily used throughout this project. Performance of the ANO-R basis set in multiconfigurational calculations is similar to the ANO-RCC basis set for the ionisation potential of atoms, and the bond distance in diatomic molecules. Deficiencies are noted for atomic electron affinities and dissociation energies of fluoride diatomic molecules. ANO-R basis sets are more compact in comparison to the corresponding ANO-RCC basis sets leading to smaller computational costs, which was demonstrated by chloroiron corrole molecule as an example.

Catalytic activity trends of pyrite transition metal dichalcogenides for oxygen reduction and evolution.

Transition metal dichalcogenides (TMDs) have been considered as promising materials for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) electrocatalysis. While there have been numerous studies focusing on layered TMDs, the ORR and OER catalytic activity trends of various cubic pyrite TMDs have not been systematically explored yet. Herein, we investigated 12 earth abundant element-based pyrite TMDs (MX2, where M = Mn, Fe, Co, Ni and X = S, Se, Te) using density functional theory (DFT) calculations. We initially constructed surface Pourbaix diagrams to determine the most stable surface coverages under the reaction conditions and found that the oxidized surfaces are most energetically preferred in all cases. We then calculated the binding free energies of reaction intermediates (O*, OH* and OOH*) and established their scaling relations. The electrochemical ORR and OER performances were then displayed on two-dimensional volcano plots, which suggest MnS2, FeS2, NiTe2 and CoSe2 to be ORR active, and CoTe2 and CoSe2 to be OER active. In addition, we built multivariate linear regression models to predict ΔGO* and ΔGOH* using only atomic and bulk properties to readily estimate the catalytic activities of pyrite TMDs and to explore correlations between those properties. Particularly, we found that the electron affinity and bulk Bader charges of metal atoms are critical in determining the ORR and OER catalytic activities, which could be used as a guidance for future catalyst design.

On the use of electronegativity and electron affinity based pseudo-molecular field descriptors in developing correlations for quantitative structure-activity relationship modeling of drug activities.

For quantitative structure-activity relationship (QSAR) modeling in ligand-based drug discovery programs, pseudo-molecular field (PMF) descriptors using intrinsic atomic properties, namely, electronegativity and electron affinity are studied. In combination with partial least squares analysis and Procrustes transformation, these PMF descriptors were employed successfully to develop correlations that predict the activities of target protein inhibitors involved in various diseases (cancer, neurodegenerative disorders, HIV, and malaria). The results show that the present QSAR approach is competitive to existing QSAR models. In order to demonstrate the use of this algorithm, we present results of screening naturally occurring molecules with unknown bioactivities. The pIC50 predictions can screen molecules that have desirable activity before assessment by docking studies.

Emergence of magnetic anisotropy by surface adsorption of transition metal dimers on γ-graphyne framework

In this paper a systematic study is carried out to demonstrate the structural stability and magnetic novelty of adsorbing transition metal (TM) dimers (A-B) on graphyne (GY) surface, GY@A-B. Our research points out that the dimers are strongly adsorbed onto GY due to their large natural pores and the electron affinity of the sp-hybridized carbon atoms. Electronic properties of these dimer-graphyne composite systems are of particular importance as they behave as degenerate semiconductors with partial occupation of states at E F. Furthermore, their remarkable spin polarization (>80%) at Fermi energy (E F) can be of paramount importance in spintronics applications. Most of the GY@A-B structures exhibit large magnetic anisotropies as well as magnetic moments along the out-of-plane direction with respect to the GY surface. Particularly, GY@Co–Ir, GY@Ir–Ir and GY@Ir–Os structures possess positive magnetic anisotropic energies (MAE) of 121 meV, 81 meV and 137 meV, respectively, which are comparable to other well-known TM dimer doped systems. The emergence of high MAE can be understood using the second-order perturbation theory on the basis of the strong spin–orbit coupling (SOC) between the two TMs and the degeneracy of their d-orbitals near E F. A close correspondence between the simulated and the analytical results has been established through our work. Further, a simple estimation shows that, GY@A-B structures have the potential to store data up to 64 PB m−2. These intriguing electronic characteristics along with magnetism suggest GY@A-B to be a promising material for future magnetic storage devices.

Electron affinities for highly charged groups 15 and 16 anions

Electron affinity, electronegativity, and electrophilicity are chemical concepts that have been related to electron accepting power of chemical species. In the literature, although there are many theoretical approaches proposed to calculate the electronegativity and electrophilicity of atoms, ions, and molecules, just a few approaches suggested are related to the prediction of sequential electron affinities of atoms. In the present work, the electron affinities for highly charged groups 15 and 16 anions are calculated by the semi-empirical (PM6) method. The obtained values are compared with those from literature. So far, the authors are concerned, the third and fourth electron affinities for S, P, As and Sb are calculated for the first time. It is well-known that in the calculation of the lattice energy of any inorganic ionic crystal via Born-Haber thermochemical cycle, many parameters regarding any crystal the atoms forming the crystal are considered. One of these parameters is electron affinity. It should be noted that our electron affinity values calculated are in good agreement with both experimental data, other theoretical approaches, and the data obtained in the light of the Born- Haber cycle.

Self-Interaction-Corrected Random Phase Approximation.

The short-range correlation energy of the random phase approximation (RPA) is too negative and is often corrected by local or nonlocal methods. These beyond-RPA corrections usually lead to a mixed performance for thermodynamics and dissociation properties. RPA+ is an additive correction based on density functional approximations that often gives realistic total energies for atoms or solids. RPA+ adds a moderate correction to the ionization energies/electron affinities of RPA but does not yield an improvement beyond RPA for atomization energies of molecules. This incompleteness results in severely underestimated atomization energies just like in RPA. Exchange-correlation kernels within the Dyson equation could simultaneously improve atomization, ionization energies, and electron affinities, but their implementation is computationally less feasible in localized basis set codes. In preceding work ( Phys. Rev. A 100, 2019022515), two of the authors proposed a computationally efficient generalized RPA+ (gRPA+) that changes RPA+ only for spin-polarized systems by making gRPA+ exact for all one-electron densities. gRPA+ was found to yield a large improvement of ionization energies and electron affinities of light atoms over RPA, and a smaller improvement over RPA+. Within this work, we investigate to what extent this improvement transfers to atomization energies, ionization energies, and electron affinities of molecules, using a modified gRPA+ (mgRPA+) method that can be applied in codes with localized basis functions. We thereby aim to understand the applicability of beyond-RPA corrections based on density functional approximations.

Quantifying electron-correlation effects in small coinage-metal clusters via ab initio calculations.

We investigate many-electron correlation effects in neutral and charged coinage-metal clusters Cun, Agn, and Aun (n = 1-4) via ab initio calculations using fixed-node diffusion Monte Carlo (FN-DMC) simulations, density functional theory (DFT), and the Hartree-Fock (HF) method. From very accurate FN-DMC total energies of the clusters and the HF results in the infinity large complete-basis-set limit, we obtain correlation energies in these strongly correlated many-electron clusters involving d orbitals. The obtained bond lengths of the clusters, atomic binding and dissociation energies, ionization potentials, and electron affinities are in satisfactory agreement with the available experiments. In the analysis, the electron correlation effects on these observable physical quantities are quantified by relative correlation contributions determined by the difference between the calculated FN-DMC and HF results. We show that the correlation contribution is not only significant for the quantities related to electronic structures of the coinage-metal clusters, such as electron affinity, but it is also essential for the stability of the atomic structures of these clusters. For example, the electron correlation contribution is responsible for more than 90% of the atomic binding energies of the small neutral copper clusters. We also demonstrate the orbital-occupation dependence of the correlation energy and electron pairing of the valence electrons in these coinage-metal clusters from the electron correlation-energy gain and spin-multiplicity change in the electron addition processes, which are reflected in their ionization potentials and electron affinities.

Accurate atomic electron affinities calculated by using anionic Gaussian basis sets

The computation of accurate electron affinity (EA) remains one of the most difficult tasks in quantum chemistry. A major source of error in EA calculations is the inadequacy of the basis set (BS) to represent the anionic system, since the Gaussian exponents are normally optimized for the neutral atom energy. To overcome this problem, one must augment the BSs with diffuse functions, which allow a better description of long-range interactions in anionic systems. Here, we report a new methodology to generate BSs for accurate EA computation that consists in the direct optimization of the Gaussian exponents in an anionic environment. By using the anionic basis sets (ABSs), we substantially reduce the errors in EA calculation for boron, carbon, oxygen and fluorine. A graphical analysis of the ABS parameters shows that their exponents are able to span important regions for short- and long-ranged interactions, which permit the ABSs to properly describe both neutral and anionic systems.

Erratum: Simple self-interaction correction to random-phase-approximation-like correlation energies [Phys. Rev. A 100, 022515 (2019)

The random phase approximation (RPA) is exact for the exchange energy of a many-electron ground state, but RPA makes the correlation energy too negative by about 0.5 eV/electron. That large short-range error, which tends to cancel out of iso-electronic energy differences, is largely corrected by an exchange-correlation kernel, or (as in RPA+) by an additive local or semilocal correction. RPA+ is by construction exact for the homogeneous electron gas, and it is also accurate for the jellium surface. RPA+ often gives realistic total energies for atoms or solids in which spin-polarization corrections are absent or small. RPA and RPA+ also yield realistic singlet binding energy curves for H2 and N2, and thus RPA+ yields correct total energies even for spin-unpolarized atoms with fractional spins and strong correlation, as in stretched H2 or N2. However, RPA and RPA+ can be very wrong for spin-polarized one-electron systems (especially for stretched H2+), and also for the spin-polarization energies of atoms. The spin-polarization energy is often a small part of the total energy of an atom, but important for ionization energies, electron affinities, and the atomization energies of molecules. Here we propose a computationally efficient generalized RPA+ (gRPA+) that changes RPA+ only for spin-polarized systems by making gRPA+ exact for all one-electron densities, in the same simple semilocal way that the correlation energy densities of many meta-generalized gradent approximations are made self-correlation free. By construction, gRPA+ does not degrade the exact RPA+ description of jellium. gRPA+ is found to greatly improve upon RPA and RPA+ for the ionization energies and electron affinities of light atoms. Many versions of RPA with an approximate exchange-correlation kernel fail to be exact for all one-electron densities, and they can also be self-interaction corrected in this way.

Improvements in the orbitalwise scaling down of Perdew-Zunger self-interaction correction in many-electron regions.

The Perdew-Zunger (PZ) method provides a way to remove the self-interaction (SI) error from density functional approximations on an orbital by orbital basis. The PZ method provides significant improvements for the properties such as barrier heights or dissociation energies but results in over-correcting the properties well described by SI-uncorrected semi-local functional. One cure to rectify the over-correcting tendency is to scale down the magnitude of SI-correction of each orbital in the many-electron region. We have implemented the orbitalwise scaled down SI-correction (OSIC) scheme of Vydrov et al. [J. Chem. Phys. 124, 094108 (2006)] using the Fermi-Löwdin SI-correction method. After validating the OSIC implementation with previously reported OSIC-LSDA results, we examine its performance with the most successful non-empirical SCAN meta-GGA functional. Using different forms of scaling factors to identify one-electron regions, we assess the performance of OSIC-SCAN for a wide range of properties: total energies, ionization potentials and electron affinities for atoms, atomization energies, dissociation and reaction energies, and reaction barrier heights of molecules. Our results show that OSIC-SCAN provides superior results than the previously reported OSIC-LSDA, -PBE, and -TPSS results. Furthermore, we propose selective scaling of OSIC (SOSIC) to remove its major shortcoming that destroys the -1/r asymptotic behavior of the potentials. The SOSIC method gives the highest occupied orbital eigenvalues practically identical to those in PZSIC and unlike OSIC provides bound atomic anions even with larger powers of scaling factors. SOSIC compared to PZSIC or OSIC provides a more balanced description of total energies and barrier heights.

Fluorine edge decoration on zigzag silicene nanoribbons

Abstract We used the density functional theory (DFT) to explore the effects of fluorine (F) edge decoration on zigzag silicene nanoribbons (ZSiNR). Due to the strong electron affinity of fluorine atoms, a strong chemical bond between Si atoms and F atoms is formed. The formation energy also indicated that the fluorination configurations had higher stability than for the ZSiNR. The fluorination sites at the edges efficiently modulate the electronic and magnetic properties of the ZSiNR. In particular, we found a significant change from a metallic to a semiconductor characteristic in asymmetric edge fluorinated ZSiNR, in a mono-fluorinated system with one single edge, which was attributed to the weakening of the σ-π mixing effect. In contrast, a half-metallic character with a 100% spin polarization was induced in another other two full asymmetric fluorination systems due to the contribution from the F-Py, F-Pz, and Si-Py orbitals. All asymmetric fluorinations maintained a ferromagnetic character. Symmetric edge fluorinated ZSiNR maintained a ferromagnetic metallic characteristic or an antiferromagnetic semi-conductor characteristic due to the Coulomb repulsion from both edges. The interesting and useful physical properties in ZSiNR with edge fluorination including the half-metallic character and the spin polarization implied that edge-fluorinated ZSiNR can be effectively used in spintronic devices.

Nitrogen-doped graphene oxide as a catalyst for the oxidation of Rhodamine B by hydrogen peroxide: application to a sensitive fluorometric assay for hydrogen peroxide.

The authors report that nitrogen-doped graphene oxide (NGO) catalyzes the oxidative decomposition of the fluorophore Rhodamine B (RhB) by hydrogen peroxide. The catalytic decomposition of hydrogen peroxide yields free hydroxyl radicals that destroy RhB so that the intensity of the yellow fluorescence is reduced. Nitrogen doping enhances the electronic and optical properties and surface chemical reactivities of GO such as widening of bandgap, increase in conductivity, enhanced quenching and adsorbing capabilities etc. The catalytic properties of NGO are attributed to its large specific surface and high electron affinity of nitrogen atoms. The chemical and structural properties of GO and NGO were characterized by XRD, FTIR, SEM, UV-visible and Raman spectroscopies. The method was optimized by varying the concentration of RhB, nitrogen dopant and hydrogen peroxide. The fluorescent probe, best operated at excitation/emission wavelengths of 554/577nm, allows hydrogen peroxide to be determined in concentrations as low as 94 pM with a linear range spanning from 1nM to 1μM. Graphical abstract Schematic illustration of a fluorescence quenching method for the determination of H2O2. Upon addition of H2O2, nitrogen-doped graphene oxide (NGO) catalyzes the oxidation of Rhodamine B dye due to hydroxyl radical generation, which leads to a sensitive quenchometric methd for H2 O2.

Simple self-interaction correction to random-phase-approximation-like correlation energies

The random-phase approximation (RPA) is exact for the exchange energy of a many-electron ground state, but RPA makes the correlation energy too negative by about 0.5 eV/electron. That large short-range error, which tends to cancel out of isoelectronic energy differences, is largely corrected by an exchange-correlation kernel, or (as in RPA+) by an additive local or semilocal correction. RPA+ is by construction exact for the homogeneous electron gas, and it is also accurate for the jellium surface. RPA+ often gives realistic total energies for atoms or solids in which spin-polarization corrections are absent or small. RPA and RPA+ also yield realistic singlet binding energy curves for ${\mathrm{H}}_{2}$ and ${\mathrm{N}}_{2}$, and thus RPA+ yields correct total energies even for spin-unpolarized atoms with fractional spins and strong correlation, as in stretched ${\mathrm{H}}_{2}$ or ${\mathrm{N}}_{2}$. However, RPA and RPA+ can be very wrong for spin-polarized one-electron systems (especially for stretched ${{\mathrm{H}}_{2}}^{+}$), and also for the spin-polarization energies of atoms. The spin-polarization energy is often a small part of the total energy of an atom, but important for ionization energies, electron affinities, and the atomization energies of molecules. Here we propose a computationally efficient generalized RPA+ (gRPA+) that changes RPA+ only for spin-polarized systems by making gRPA+ exact for all one-electron densities, in the same simple semilocal way that the correlation energy densities of many metageneralized gradient approximations are made self-correlation free. By construction, gRPA+ does not degrade the exact RPA+ description of jellium. gRPA+ is found to greatly improve upon RPA and RPA+ for the ionization energies and electron affinities of light atoms. Many versions of RPA with an approximate exchange-correlation kernel fail to be exact for all one-electron densities, and they can also be self-interaction corrected in this way.