Electron Density Research Articles

Spin states of metal centers in electrocatalysis.

Understanding the electronic structure of active sites is crucial in efficient catalyst design. The spin state, spin configurations of d-electrons, has been frequently discussed recently. However, its systematic depiction in electrocatalysis is lacking. In this tutorial review, a comprehensive interpretation of the spin state of metal centers in electrocatalysts and its role in electrocatalysis is provided. This review starts with the basics of spin states, including molecular field theory, crystal field theory, and ligand field theory. It further introduces the differences in low spin, intermediate spin, and high spin, and intrinsic factors affecting the spin state. Popular characterization techniques and modeling approaches that can reveal the spin state, such as X-ray absorption microscopy, electron spin resonance spectroscopy, Mössbauer spectroscopy, and density functional theory (DFT) calculations, are introduced as well with examples from the literature. The examples include the most recent progress in tuning the spin state of metal centers for various reactions, e.g., the oxygen evolution reaction, oxygen reduction reaction, hydrogen evolution reaction, carbon dioxide reduction reaction, nitrogen reduction reaction, nitrate reduction reaction, and urea oxidation reaction. Challenges and potential implications for future research related to the spin state are discussed at the end.

Structure to Property: Chemical Element Embeddings for Predicting Electronic Properties of Crystals.

We present a new general-purpose machine learning model that is able to predict a variety of crystal properties, including Fermi level energy and band gap, as well as spectral ones such as electronic densities of states. The model is based on atomic representations that enable it to effectively capture complex information about each atom and its surrounding environment in a crystal. The accuracy achieved for band gaps exceeds results previously published. By design, our model is not restricted to the electronic properties discussed here but can be extended to fit diverse chemical descriptors. Its advantages are (a) its low computational requirements, making it an efficient tool for high-throughput screening of materials; and (b) the simplicity and flexibility of its architecture, facilitating implementation and interpretation, especially for researchers in the field of computational chemistry.

Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities.

A crucial aspect in the simulation of electrochemical interfaces consists in treating the distribution of electronic charge of electrode materials that are put in contact with an electrolyte solution. Recently, it has been shown how a machine-learning method that specifically targets the electronic charge density, also known as SALTED, can be used to predict the long-range response of metal electrodes in model electrochemical cells. In this work, we provide a full integration of SALTED with MetalWalls, a program for performing classical simulations of electrochemical systems. We do so by deriving a spherical harmonics extension of the Ewald summation method, which allows us to efficiently compute the electric field originated by the predicted electrode charge distribution. We show how to use this method to drive the molecular dynamics of an aqueous electrolyte solution under the quantum electric field of a gold electrode, which is matched to the accuracy of density-functional theory. Notably, we find that the resulting atomic forces present a small error of the order of 1 meV/Å, demonstrating the great effectiveness of adopting an electron-density path in predicting the electrostatics of the system. Upon running the data-driven dynamics over about 3ns, we observe qualitative differences in the interfacial distribution of the electrolyte with respect to the results of a classical simulation. By greatly accelerating quantum-mechanics/molecular-mechanics approaches applied to electrochemical systems, our method opens the door to nanosecond timescales in the accurate atomistic description of the electrical double layer.

Unveiling Atomic-Scaled Local Chemical Order of High-Entropy Intermetallic Catalyst for Alkyl-Substitution-Dependent Alkyne Semihydrogenation.

High-entropy intermetallic (HEI) nanocrystals, composed of multiple elements with an ordered structure, are of immense interest in heterogeneous catalysis due to their unique geometric and electronic structures and the cocktail effect. Despite tremendous efforts dedicated to regulating the metal composition and structures with advanced synthetic methodologies to improve the performance, the surface structure, and local chemical order of HEI and their correlation with activity at the atomic level remain obscure yet challenging. Herein, by determining the three-dimensional (3D) atomic structure of quinary PdFeCoNiCu (PdM) HEI using atomic-resolution electron tomography, we reveal that the local chemical order of HEI regulates the surface electronic structures, which further mediates the alkyl-substitution-dependent alkyne semihydrogenation. The 3D structures of HEI PdM nanocrystals feature an ordered (intermetallic) core enclosed by a disordered (solid-solution) shell rather than an ordered surface. The lattice mismatch between the core and shell results in apparent near-surface distortion. The chemical order of the intermetallic core increases with annealing temperature, driving the electron redistribution between Pd and M at the surface, but the surface geometrical (chemically disordered) configurations and compositions are essentially unchanged. We investigate the catalytic performance of HEI PdM with different local chemical orders toward semihydrogenation across a broad range of alkynes, finding that the electron density of surface Pd and the hindrance effect of alkyl substitutions on alkynes are two key factors regulating selective semihydrogenation. We anticipate that these findings on surface atomic structure will clarify the controversy regarding the geometric and/or electronic effects of HEI catalysts and inspire future studies on tuning local chemical order and surface engineering toward enhanced catalysts.

MB38(M=Be and Zn): A Quasi-Planar Structure Rather Than A Core-Shell Octahedral Borospherene Structure.

In a recent paper (ChemPhysChem, 2023, 24, e202200947), based on the results computed using DFT method, the perfect core-shell octahedral configuration Be@B38 and Zn@B38 was reported to be the global minima of the MB38(M=Be and Zn) clusters. However, this paper presents the lower energy structures of MB38(M=Be and Zn) clusters as a quasi-planar configuration, the Be atom is found to reside on the convex surface of the quasi-planar B38 isomer, while the Zn atom tends to be attached to the top three B atoms of the quasi-planar B38 isomer. Our results show that quasi-planar MB38(M=Be and Zn) at DFT method have lower energy than core-shell octahedral configuration M@B38(M=Be and Zn). Natural atomic charges, valence electron density, electron localization function (ELF) analyses identify the MB38(M=Be and Zn) to be charge transfer complexes (Be2+B382-and Be1+B381-) and suggest primarily the electrostatic interactions between doped atom and B38 fragment. The photoelectron spectra of the corresponding anionic structures were simulated, providing theoretical basis for future structural identification.

Cryogenic electron microscopy reveals morphologically distinct subtypes of extracellular vesicles among porcine ejaculate fractions

Seminal plasma (SP) is rich in extracellular vesicles (EVs), which are still poorly studied, especially in livestock species. To better understand their functional role in both spermatozoa and endometrial epithelial cells, proper characterization of EVs is an essential step. The objective was to phenotypically characterize porcine seminal EVs (sEVs) using cryogenic electron microscopy (cryo-EM), which allows visualization of EVs in their native state. Porcine ejaculates are released in fractions, each containing SP from different source. This allows characterization sEVs released from various male reproductive tissues. Two experiments were performed, the first with SP from the entire ejaculate (n:6) and the second with SP from three ejaculate fractions (n:15): the first 10 mL of the sperm-rich ejaculate fraction (SRF-P1) with SP mainly from the epididymis, the remainder of the SRF (SRF-P2) with SP mainly from the prostate, and the post-SRF with SP mainly from the seminal vesicles. The sEVs were isolated by size exclusion chromatography and 1840 cryo-EM sEV images were acquired using a Jeol-JEM-2200FS/CR-EM. The size, electron density, complexity, and peripheral corona layer were measured in each sEV using the ImageJ software. The first experiment showed that sEVs were structurally and morphologically heterogeneous, although most (83.1%) were small (less than 200 nm), rounded, and poorly electrodense, and some have a peripheral coronal layer. There were also larger sEVs (16.9%) that were irregularly shaped, more electrodense, and few with a peripheral coronal layer. The second experiment showed that small sEVs were more common in SRF-P1 and SRF-P2, indicating that they originated mainly from the epididymis and prostate. Large sEVs were more abundant in post-SRF, indicating that they originated mainly from seminal vesicles. Porcine sEVs are structurally and morphologically heterogeneous. This would be explained by the diversity of reproductive organs of origin.

Effect of Pyrrolidinedithiocarbamate Ligand on the Luminescence Properties of Heteroligand Samarium and Europium Complexes: Experimental and Theoretical Study.

The photophysical properties of two isostructural heteroligand lanthanide complexes of general formula Ln(pdtc)3(phen) (pdtc = pyrrolidinedithiocarbamate anion, phen = 1,10-phenanthroline), Ln = Sm3+ (1), Eu3+ (2)) were studied in solid state and dichloromethane (DCM) solution. The two lanthanide complexes were investigated by experimental techniques for structural (single-crystal X-ray diffraction analysis of 1, powder XRD, TG-DTA) and spectroscopic [electron paramagnetic resonance (EPR), infrared (IR), ultraviolet-visible (UV-vis), photoluminescence (PL)] characterization. DFT/TDDFT/ωB97xD and multireference SA-CASSCF/NEVPT2 calculations with perturbative spin-orbit coupling corrections were applied to construct the Jablonski energy diagrams and to discuss the excited state energy transfer mechanism with competing excited state processes and possible sensitized mechanism of metal-centered emission. The first excited state (S1) involved in the excited state energy transfer L(antenna)-to-Ln was predicted to have interligand (pdtc-to-phen) charge transfer character in contrast to the previously predicted ligand-to-metal charge transfer character. The theoretical consideration showed similar relaxation paths and luminescence quenching channels and appropriate Donor*(phen)-Acceptor*(Ln3+) energy gap for 1 and 2. The experimental measurements in the solid state, however, showed efficient luminescence and good ability to convert UV to visible light only for the Sm(pdtc)3(phen) complex. The minor emission of 2 was explained by partial reduction of Eu3+, confirmed by EPR and calculated electron density distribution data.

Energetic Information from Information-Theoretic Approach in Density Functional Theory as Quantitative Measures of Physicochemical Properties.

The Hohenberg-Kohn theorem of density functional theory (DFT) stipulates that energy is a universal functional of electron density in the ground state, so energy can be thought of having encoded essential information for the density. Based on this, we recently proposed to quantify energetic information within the framework of information-theoretic approach (ITA) of DFT (J. Chem. Phys. 2022, 157, 101103). In this study, we systematically apply energetic information to a variety of chemical phenomena to validate the use of energetic information as quantitative measures of physicochemical properties. To that end, we employed six ITA quantities such as Shannon entropy and Fisher information for five energetic densities, yielding twenty-six viable energetic information quantities. Then, they are applied to correlate with physicochemical properties of molecular systems, including chemical bonding, conformational stability, intermolecular interactions, acidity, aromaticity, cooperativity, electrophilicity, nucleophilicity, and reactivity. Our results show that different quantities of energetic information often behave differently for different properties but a few of them, such as Shannon entropy of the total kinetic energy density and information gain of the Pauli energy density, stand out and strongly correlate with several properties across different categories of molecular systems. These results suggest that they can be employed as quantitative measures of physicochemical properties. This work not only enriches the body of our knowledge about the relationship between energy and information, but also provides scores of newly introduced explicit density functionals to quantify physicochemical properties, which can serve as robust features for building machine learning models in future studies.

Spin vacuum switching.

Ultrafast control over the magnetic orientation of matter represents a vital element of potential future spin-based electronics ("spintronics"). While physical mechanisms underpinning spin switching are established for picosecond time scales, we here present a physical route to magnetization toggle control, i.e., multiple switching events, at <100 femtoseconds. A minority spin current injected into a ferromagnet is shown to generate rapid depopulation of the minority channel below the ground-state Fermi level, creating a minority "spin vacuum" that then drives rapid charge redistribution from the majority channel and spin switching. We demonstrate that this mechanism reproduces many of the features of recent subpicosecond switching of ferromagnetic Co/Pt multilayers and provide simple practical rules for the design of materials via tailoring the electronic density of states to optimize spin vacuum control over magnetic order.

Machine learning-based prediction of the electron energy distribution function and electron density of argon plasma from the optical emission spectra

Machine learning-based prediction of the electron energy distribution function and electron density of argon plasma from the optical emission spectra

Using radio occultation-based electron density profiles for studying sporadic E layer spatial and temporal characteristics

An improved method for identifying sporadic E (Es) layer properties from radio occultation (RO) electron density profiles (EDPs) is presented. The data used are sourced from COSMIC-1 RO EDPs collected between 2006 and 2019, which cover altitudes from 75 to 145 km. Initially, we evaluate the reliability of EDPs using the International Reference Ionosphere 2016 (IRI-2016) model and select only those profiles with a reliability score of 0.6 or higher (on a scale up to 1) for further analysis. Preliminary Es layer inversion results are obtained and validated against electron density data derived from ionosonde fbEs measurements, demonstrating a linear correlation with a coefficient of 0.72 and a mean absolute percentage error of 36.08%. Further verification using RO S4max data shows that this research method achieved an accuracy of 85.3% in identifying Es events. We perform a detailed analysis of Es layer relative occurrence rates, intensity, and thickness. The Es intensity is expressed by NmμEs (the layer’s maximum electron density (Nm) corresponding to the metal (μ) ion), which is estimated from the measured layer peak electron density NmEs by subtracting the ambient E region electron density NeE(hEs) at the height of the layer’s peak hEs, computed from the IRI-2016 model. Our findings reveal that Es layers predominantly occur in mid-latitude regions during summer, with average intensities between 5×104and8×104el/cm3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$5\ imes {10}^{4 }\ ext{ and }8\ imes {10}^{4 }\ ext{el}/{\ ext{cm}}^{3}$$\\end{document}. The most likely thickness of Es layers is approximately 1.4 km. Additionally, the present study shows that because NeE(hEs) increases during daytime, which leads to increases in NmEs, confirming that NmμEs is the proper parameter for assessing the Es layer intensity, in line with what is suggested by Haldoupis et al. (Haldoupis et al., J Atmos Sol Terr Phys 206:105327, 2020).Graphical

Using radio occultation-based electron density profiles for studying sporadic E layer spatial and temporal characteristics

An improved method for identifying sporadic E (Es) layer properties from radio occultation (RO) electron density profiles (EDPs) is presented. The data used are sourced from COSMIC-1 RO EDPs collected between 2006 and 2019, which cover altitudes from 75 to 145 km. Initially, we evaluate the reliability of EDPs using the International Reference Ionosphere 2016 (IRI-2016) model and select only those profiles with a reliability score of 0.6 or higher (on a scale up to 1) for further analysis. Preliminary Es layer inversion results are obtained and validated against electron density data derived from ionosonde fbEs measurements, demonstrating a linear correlation with a coefficient of 0.72 and a mean absolute percentage error of 36.08%. Further verification using RO S4max data shows that this research method achieved an accuracy of 85.3% in identifying Es events. We perform a detailed analysis of Es layer relative occurrence rates, intensity, and thickness. The Es intensity is expressed by NmμEs (the layer’s maximum electron density (Nm) corresponding to the metal (μ) ion), which is estimated from the measured layer peak electron density NmEs by subtracting the ambient E region electron density NeE(hEs) at the height of the layer’s peak hEs, computed from the IRI-2016 model. Our findings reveal that Es layers predominantly occur in mid-latitude regions during summer, with average intensities between 5×104and8×104el/cm3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$5\ imes {10}^{4 }\ ext{ and }8\ imes {10}^{4 }\ ext{el}/{\ ext{cm}}^{3}$$\\end{document}. The most likely thickness of Es layers is approximately 1.4 km. Additionally, the present study shows that because NeE(hEs) increases during daytime, which leads to increases in NmEs, confirming that NmμEs is the proper parameter for assessing the Es layer intensity, in line with what is suggested by Haldoupis et al. (Haldoupis et al., J Atmos Sol Terr Phys 206:105327, 2020).Graphical

The effect of the electron κ-distribution on the dust particle charging in the Radio-frequency thermal-sheaths

Abstract In order to investigate collisionless radiofrequency plasma sheaths&amp;#xD;containing dust particles, three models are utilized:&amp;#xD;the novel kinetic scheme. Ensemble-in-Spacetime (EST) model for calculating sheath parameters, the Dust&amp;#xD;Particle Charging model, and the Single Dust Particle model. The EST model has&amp;#xD;been modified to account for κ-electron distributions.&amp;#xD;This model is applicable to radiofrequency plasma sheaths found in tokamaks equipped with an ion cyclotron&amp;#xD;radiofrequency (ICRF) wave heating system, such as JET, West(Tore Supra), EAST,&amp;#xD;ASDEX-U, and KSTAR. The calculated sheath parameters are utilized to determine&amp;#xD;the electron and ion currents of the dust particles. In the intermediate radio-frequency&amp;#xD;regime, when the ion plasma frequency is comparable to the ICRF, the flux and energy&amp;#xD;of the ions are modulated in time within the sheath. The ions are not inertialess, and&amp;#xD;the value of κ affects the electron and ion densities.&amp;#xD;As the value of κ increases, the time-averaged electron and ion densities, sheath edge position, and area of the&amp;#xD;sheath voltage-sheath charge hysteresis loop also increase. However, the ion energy&amp;#xD;distribution remains insensitive to the κ distribution. The dust particles are charged&amp;#xD;with different negative charges based on their radius, position within the sheath, κ-&amp;#xD;electron distribution, and sheath potential. These particles exhibit oscillatory motion&amp;#xD;due to their interactions with the plasma and gravitational fields and are accelerated&amp;#xD;toward the plasma core.

Discontinuities of Kinetic Energy Densities within Finite and Complete Basis Sets.

Although electron densities are always continuous, other ingredients of density-functional approximations can be sharply discontinuous at isolated points. In particular, the positive-definite, Weizsäcker, and Pauli kinetic energy densities expressed in terms of Slater-type orbitals all have discontinuities at the positions of the atomic nuclei in molecules. The first two of those quantities are similarly discontinuous even in the basis-set limit. These striking features are not as widely recognized as they deserve to be. We show in detail how discontinuities of kinetic energy densities arise from asymmetric electron-nucleus cusps of molecular wave functions and point out instances of their significance in electronic structure theory.

Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities.

A crucial aspect in the simulation of electrochemical interfaces consists in treating the distribution of electronic charge of electrode materials that are put in contact with an electrolyte solution. Recently, it has been shown how a machine-learning method that specifically targets the electronic charge density, also known as SALTED, can be used to predict the long-range response of metal electrodes in model electrochemical cells. In this work, we provide a full integration of SALTED with MetalWalls, a program for performing classical simulations of electrochemical systems. We do so by deriving a spherical harmonics extension of the Ewald summation method, which allows us to efficiently compute the electric field originated by the predicted electrode charge distribution. We show how to use this method to drive the molecular dynamics of an aqueous electrolyte solution under the quantum electric field of a gold electrode, which is matched to the accuracy of density-functional theory. Notably, we find that the resulting atomic forces present a small error of the order of 1 meV/Å, demonstrating the great effectiveness of adopting an electron-density path in predicting the electrostatics of the system. Upon running the data-driven dynamics over about 3ns, we observe qualitative differences in the interfacial distribution of the electrolyte with respect to the results of a classical simulation. By greatly accelerating quantum-mechanics/molecular-mechanics approaches applied to electrochemical systems, our method opens the door to nanosecond timescales in the accurate atomistic description of the electrical double layer.

Investigation of Numerical Transport Models in Protein-Based Molecular Junctions with Cofactors of Diverse Chemical Natures

Abstract The cofactors of proteins dictate the charge transport mechanism across molecular junctions when self-assembled protein monolayers are sandwiched between two metal electrodes. Here, we summarized how the chemical coordination nature of cofactors in various proteins modulates electrical conductance by investigating electronic transport studies across different protein-based molecular junctions under various forces applied under the AFM tip. We have utilized several numerical techniques of electronic transport to analyse the experimentally obtained current-voltage measurements across various protein-based molecular junctions and depicted the origin of electronic modulation in the electrical conductance under different external stimuli. We could also find the origin of electronic conductance modulation under external stimuli at various applied forces by obtaining several analytical transport parameters such as energy barrier, coupling strength, and electrical conductance values. Utilizing density-function-theory calculations, we further validate that the electronic density of states present in the cofactors within the proteins dominates the electronic transport behaviors across protein-based molecular junctions. Our findings reveal the limiting factor for applying various external stimuli on different proteins, which could be further valuable in bioelectronic applications. We have also found that the organic cofactor containing protein follows all the tunneling mechanism-related numerical transport models. The electronic transport across proteins with pure inorganic cofactors follows Landauer transport formalism.

Comparative analysis of absorption resonances between carbynes and cyclo[n]carbons.

Two approaches are presented here to analyze the absorption resonances between carbynes and cyclo[n]carbons, namely the analytical tight-binding model to calculate the optical selection rules of cumulenic atomic rings and chains and theab initiotime-dependent density functional theory for the optical investigation of polyynic carbon ring and chains. The optical absorption spectra of the carbon ring match that of the finite chain when their eigen energies align following theNring= 2Nchain+ 2 rule, which states that the number of atoms in an atomic ringNringis twice the number of atoms on a finite chainNchainwith two additional atoms. Two representative atomic chains are chosen for our numerical calculations, specifically carbynes withN= 7 and 8 carbon atoms as optical resonance spectra match to a recently synthesized carbon ring called cyclo$[18]$carbon. Despite the mismatch in resonance peaks, molecular orbital transitions of both carbynesN= 7 and 8 and cyclo[n]carbons reveal a wave function symmetry change from inversion to reflection and vice versa for allowed molecular orbital transitions, which results in electron density redistribution along the polyynic carbyne axis or the cyclo[n]carbons circumference. Our investigation of the correlation of optical absorption peaks between carbynes and cyclo[n]carbons is a step towards enhancing the reliability of allotrope identification in advanced molecular device spectroscopy. Moreover, this work could facilitate the non-invasive, rapid and crucial assessment of these sensitive 1D allotropes by providing accurate descriptions of their electronic and optical properties, particularly in controlled synthesis environments.

Detecting outliers in local ionospheric model for GNSS precise positioning

Global Navigation Satellite System fast precise positioning can be achieved with accurate ionospheric corrections computed from an adequate number of GNSS stations in a local region. In low-latitude regions, the presence of electron density gradients over short distances can lead to outliers in the map of ionospheric corrections and decrease its accuracy. In this study, we explored outlier detection in ionospheric correction mapping through statistical residuals during a four-month test in 2021. Our findings indicate that the residuals of the local ionospheric model conform to the Laplace distribution. To determine outliers, we use an empirical rule for the Laplace distribution, setting thresholds at μ ± 3b, μ ± 3.5b, and μ ± 5.8b for data retention rates of 95%, 97%, and 99.7%, respectively. Here, μ represents the location parameter, which corresponds to the median of data, and b is the scale parameter, calculated as the medium absolute deviation. We found that while removing outliers can improve model accuracy, it may result in unavailable prediction due to a lack of data in a spare network. For example, applying a μ ± 3.5b threshold for outlier removal led to approximately 2.5% of recording time having no ionospheric corrections map in low-latitude regions, however, the local model has the potential to improve its mean accuracy by up to 50% for both low and mid-latitudes. Therefore, choosing the appropriate percentile threshold depends on the network configuration and the desired accuracy. Removing erroneous satellite data to improve ionospheric accuracy brings positive impacts on precise positioning.

Tunable Photoluminescence from Monolayer Molybdenum Disulfide

AbstractMonolayer molybdenum disulfide (1L MoS2), a promising optoelectronic material, emits strong visible photoluminescence (PL). Systematic control of the intensity, energy, and spectral width of PL from 1L MoS2 on silicon dioxide/silicon (SiO2/Si) is demonstrated via simple external treatments. Treating MoS2 with solutions formed from the superacid bis‐(trifluoromethanesulfonyl)amide (TFSA) enhances, blueshifts, and sharpens the PL. Treatments with solutions from structurally analogous chemicals that lack sulfur, in the case of bis(trifluoroacetamide) (BTFA), or lack fluorine, in the case of methanesulfonamide (MSA), show the same trend, suggesting a two‐component mechanism for TFSA involving the presence of electronegative species and sulfur vacancy passivation. Up to ≈100× enhancement of the PL intensity is achieved, with the peak blueshifted by ≈30 meV and the spectral linewidth halved. Conversely, direct thermal atomic layer deposition (ALD) of aluminum oxide (Al2O3) or hafnium oxide (HfO2) is found to suppress the PL by up to a factor of ≈3, redshift by up to ≈70 meV, and broaden by ≈3×. Single‐spot and mapping Raman/PL techniques are combined in a robust characterization process to associate changes in the PL character to charge doping. This work demonstrates the convenient tunability of the optical behavior of 1L MoS2 by varying the electron density.

Multi-planar dual adversarial network based on dynamic 3D features for MRI-CT head and neck image synthesis.

Head and neck radiotherapy planning requires electron densities from different tissues for dose calculation.&#xD;Dose calculation from imaging modalities such as MRI remains an unsolved problem since this imaging modality does not provide information about the density of electrons. &#xD;Approach. We propose a generative adversarial network (GAN) approach that synthesizes CT (sCT) images from T1-weighted MRI acquisitions in head and neck cancer patients. Our contribution is to exploit new features that are relevant for improving multimodal image synthesis, and thus improving the quality of the generated CT images. More precisely, we propose a Dual branch generator based on the U-Net architecture and on an augmented multi-planar branch. The augmented branch learns specific 3D dynamic features, which describe the dynamic image shape variations and are extracted from different view-points of the volumetric input MRI. The architecture of the proposed model relies on an end-to-end convolutional U-Net embedding network.&#xD;Results. The proposed model achieves a mean absolute error (MAE) of $18.76 (5.167)$ in the target Hounsfield unit (HU) space on sagittal head and neck patients, with a mean structural similarity (MSSIM) of $0.95 (0.09)$ and a Frechet inception distance (FID) of $145.60 (8.38)$. The model yields a MAE of $26.83 (8.27)$ to generate specific primary tumor regions on axial patient acquisitions, with a Dice score of $0.73 (0.06)$ and a FID distance equal to $122.58 (7.55)$. The improvement of our model over other state-of-the-art GAN approaches is of $3.8\%$, on a tumor test set. On both sagittal and axial acquisitions, the model yields the best peak signal-to-noise ratio (PSNRs) of $27.89 (2.22)$ and $26.08 (2.95)$ to synthesize MRI from CT input.&#xD;Significance. The proposed model synthesizes both sagittal and axial CT tumor images, used for radiotherapy treatment planning in head and neck cancer cases. The performance analysis across different imaging metrics and under different evaluation strategies demonstrates the effectiveness of our dual CT synthesis model to produce high quality sCT images compared to other state-of-the-art approaches. Our model could improve clinical tumor analysis, in which a further clinical validation remains to be explored.