Sampling Lattice Research Articles

Influence of doped ions on the electrochemical hydrogen storage properties of LaFeO3-based solid solutions

Perovskite oxides LaFeO3 has been considered as one of the most promising candidates as the negative electrode material of Ni/MH batteries, due to its advantages such as low cost, outstanding corrosion resistance and environmentally friendly. Nevertheless, the low electrical conductivities and poor specific capacities are the main obstacles of developing this material to practical application. Doping is an effective method to solve these problems. In this paper, nanosized LaFeO3-based solid solutions doped with Co3+, Mn3+, and Li+ ions were synthesized via sol-gel method, and the contents of the doped ions are set as 0.10. The substitution positions of the doped ions were discussed. The microstructure tests revealed that the doped samples were single phase structures, and the crystallite sizes of the doped samples were smaller than that of the undoped LaFeO3. The dispersion degrees of the doped samples were improved. The results of the spectra tests demonstrated that the doped ions decreased the band gap energies, the Co3+ and Mn3+ ions influenced the frequencies of Fe–O stretching vibrations, and partial replacement of La3+ ions by Li+ ions induced the shift of vibration modes of the La–O bond. Electrochemical hydrogen storage measurements showed that the doped samples possess significantly better properties than that of the undoped LaFeO3. Thereinto, the maximum discharge capacity of the Co3+ ion doped sample reached to 414 mAh/g at the 14th cycle and remained stable at around 400 mAh/g within the following cycles. Kinetic results further proved that the doped samples showed better performances. The hydrogen storage properties of doped LaFeO3 are closely associated with the contents of the oxygen vacancies and defects in the lattice of samples. In addition, the characteristics of the doped ions also play important roles in improving the hydrogen storage properties of the LaFeO3-based oxides.

Numerical simulation of proton backscattering spectra in GEANT4 toolkit

Rutherford backscattering spectroscopy (RBS) is a widely used technique for the atomic-scale analysis of sample composition, lattice displacement and impurity profiling. RBS is based on the elastic scattering of incident charged particles by target nuclei and the subsequent detection of scattered particles. The interpretation of RBS spectra, however, poses challenges due to overlapping peaks, corresponding to scattering from different atomic species, and uncertainties from energy loss, scattering geometry and detector response. To address this, an open source simulation model based on the versatile GEANT4 simulation toolkit has been developed. The flexibility of the open source enables users to tailor the model to its specific requirements, such as the use of specific particle stopping powers, cross-sections, and physics processes. This work presents the results of the comparison between the experimental and simulated backscattering spectra in crystalline silicon, silicon carbide and silicon dioxide samples by 1–2.5 MeV energy protons, obtained in random orientation conditions. The results demonstrate the capability of the model to accurately simulate backscattering spectra in both amorphous materials and single crystals. The overall agreement between the simulated and experimental results is highly promising for future development and use in the interpretation and simulation of RBS spectra.

ХИМИЧЕСКАЯ СТАБИЛЬНОСТЬ, СТРУКТУРА И ТОПОЛОГИЯ ПОВЕРХНОСТИ ОТЕЧЕСТВЕННОЙ КОМПЛЕКСНО СТАБИЛИЗИРОВАННОЙ ДИОКСИДЦИРКОНИЕВОЙ КЕРАМИКИ В МОДЕЛИРУЕМЫХ АГРЕССИВНЫХ СРЕДАХ

Subject of the study is the chemical stability of a complex stabilized zirconium dioxide system of 3 mol.% Y2O3 15 mol.% CeO2 in simulated aggressive media (1 and 10% NaOH; 1 and 10% HCl; 1, 10 and 40% CH3COOH.
 The goal – to study the effect of various aggressive media on the structural and chemical stability of domestic comprehensively stabilized zirconium dioxide ceramics under experimental conditions.
 Methods. The tests were carried out on experimental samples of ceramic grinders (40 pcs.) of the same area and shape: the experimental group (20 pcs.) – stabilized zirconium dioxide ceramics, the control group (20 pcs.) – zirconium dioxide ceramics without stabilizing additives. The presence, severity and features of the reaction of zirconium dioxide ceramics to aggressive media were evaluated in a comparative aspect by changing the mass of samples, the microstructure of their surface and the Raman spectra.
 Results. The interaction of complexly stabilized zirconium dioxide with alkaline solutions does not lead to a statistically significant decrease in the mass of samples, under the action of solutions of organic and inorganic acids, a statistically insignificant (p<0.5) increase in total mass is observed. Scanning electron microscopy of ceramic samples of both groups after exposure to aggressive media did not reveal ultrastructural changes in the surface. Raman spectra of light before exposure in aggressive media showed more favorable values of Raman intensity for stabilized zirconium dioxide, which indicates its better degree of crystallization. After exposure to aggressive media, changes in the crystal lattice of the control samples were determined, for stabilized zirconium dioxide, the ratio I260/I320 did not change.
 Conclusions and Relevance. Stabilized zirconium dioxide of the system 3 mol.% Y2O3 15 mol.% CeO2 has increased resistance in aggressive environments, which is of practical importance when choosing a ceramic material for the manufacture of dentures, which are exposed to aggressive biological environments of the oral cavity during the entire service life.

SYNTHESIS AND CHARACTERIZATION OF MAGNETITE FE3O4 NANOPARTICLES FROM NATURAL IRON SAND in GELAR RIVER

Fe3O4 nanoparticles made from the natural iron sands of the Gelar River have been successfully synthesized using the coprecipitation method. Test the content of Fe elements in pure iron sand and characterize them using XRF after separation. Fe3O4 nanoparticle characterization uses XRD to determine the sample's lattice parameters and crystal size. The nanoparticles' morphology, structure, particle shape, and elemental content were characterized using SEM-E DX. Magnetic properties and magnetic saturation values are characterized using VSM. XRF yield on iron sand before separation contains Fe 59.46%. After separation, the Fe content rose to 84.72%. The synthesis results obtained brownish-black Fe3O4 nanoparticle powder that permanent magnets can attract. Based on the XRD results, the crystal structure formed is cubic inverse spinel with crystal lattice Å with a particle size of 14.8 nm. The SEM-EDX results show the morphology of spherical nanoparticles with multiple agglomerations. Particle size is 40 nm. The EDX spectrum confirmed the formation of Fe3O4 nanoparticles in the presence of Fe (51.79%) and O (25.68%). The VSM results show that Fe3O4 samples have ferromagnetic properties with saturation magnetization (MS) = 27.36 emu/g, remanent magnetization (Mr) = -0.01 emu/g, and coercivity field (Hc) = 0.01 T.

Utilization of Pt Nanoparticle Catalysts during Capillary Condensation Phenomenon in PEMFC: A Lattice DFT Simulation Based on 3D Reconstruction of TEM Images

The use of porous carbon support particles in Cathode Catalyst Layer (CCL) of Polymer Electrolyte Membrane Fuel Cell (PEMFC) has gained significant interest due to their ability to enable proper dispersion of Platinum (Pt) nanoparticles [1]. This offers a key advantage of avoiding the Pt nanoparticles from potential poisoning by sulfonate anion functional groups in the ionomer that is deposited on the surface of the support particles [2]. Furthermore, the presence of condensed liquid water is essential for effective utilization of the Pt nanoparticles that are dispersed both inside and outside of the porous carbon support particles. This is because water plays a crucial role as a proton pathway for hydrogen ions during the electrochemical reaction, thus a requisite amount of condensed liquid water is also needed to promote efficient catalytic activity and maximize the performance of Pt nanoparticle catalysts. It has been demonstrated that the microstructure characteristics of the porous carbon support particles have a significant impact on the performance of Pt utilization, which is attributed to the varying behavior of water condensation [2]. Microstructure properties such as pore size, surface area, and wettability properties, can influence the distribution of condensed liquid water, thereby affecting the electrochemical performance of Pt nanoparticles in the catalyst layer of PEMFC. Understanding the effect of capillary water condensation in the porous carbon support particles is therefore crucial for maximizing the utilization and catalytic activity of Pt nanoparticles in fuel cell systems.To investigate the behavior of water condensation in the CCL particles of PEMFC, we conducted simulations based on reconstructed structural data obtained from Transmission Electron Microscopy (TEM) images, as shown in Figure 1. The CCL particle used in this study is taken from the Toyota MIRAI Gen 2 model, an emerging commercial PEMFC-based vehicle in Japan. Here, we used the lattice Density Functional Theory (DFT) to simulate the process of capillary water condensation within the pore network of the particle. The lattice DFT method, which is based on the mean-field lattice gas model, can be interpreted as a coarse-grained equivalent of the conventional DFT [3]. The significant advantage of using lattice DFT is to provide a simple model and computationally efficient approach for studying the behavior of capillary water condensation. To validate the parameters used in our lattice DFT simulations, we compared the isotherm curve obtained from our simulation results with experimental data. Through this comparison, we were able to fine-tune the parameters of the lattice DFT simulation to fit the simulated isotherm curve with that of the experiment. When the parameters are optimized, the resulting water distribution obtained from the lattice DFT simulation, as illustrated in Figure 1, serves as a crucial input to investigate the utilization/activation of Pt nanoparticles within and outside the carbon support particle under varying relative humidity (RH) conditions. Since the resulting water distribution depends on RH, we expect that the utilization/activation of Pt nanoparticles also depend on RH. In this study, we defined utilization/activation of Pt nanoparticle when there is a continuous path of condensed water connecting the Pt nanoparticle to the surface of the carbon support particle. This criterion is similar to the case when we assume that the ionomer is distributed uniformly on the surface of the carbon support particle. Our investigation shows that the utilization/activation behavior of Pt nanoparticles follows closely the isotherm curve of the capillary water condensation.The complex internal structure of CCL particles in PEMFC makes it challenging to visualize and understand their workings through experiments alone. Therefore, our approach of using lattice DFT simulations offers valuable insights to the role of capillary water condensation behavior in the utilization/activation of Pt nanoparticles. This approach may also pave the way for future research in optimization strategies for PEMFC, ultimately contributing to the advancement of clean energy technologies.This work was supported by the New Energy and Industrial Technology Development Organization (NEDO) of Japan (Grant number JPNP20003).[1] Islam, M.N., et al. (2022), Nat. Commun. 13, 6157.[2] Ramaswamy, N., et al. (2020) J. Electrochem. Soc. 167 064515.[3] Monson, P. (2012) Micropor. Mesopor. Mater. 160, 47–66.Figure 1. Reconstructed structural data obtained from TEM images of a PEMFC CCL particle used in Toyota MIRAI Gen 2 model, with visualization of condensed water obtained from a sample lattice DFT simulation. Figure 1

Size effects on atomic collapse in the dice lattice.

We study the role of size effects on atomic collapse of charged impurity in the flat band system. The tight-binding simulations are made for the dice lattice with circular quantum dot shapes. It is shown that the mixing of in-gap edge states with bound states in impurity potential leads to increasing the critical charge value. This effect, together with enhancement of gap due to spatial quantization, makes it more difficult to observe the dive-into-continuum phenomenon in small quantum dots. At the same time, we show that if in-gap states are filled, the resonant tunneling to bound state in the impurity potential might occur at much smaller charge, which demonstrates non-monotonous dependence with the size of sample lattice. In addition, we study the possibility of creating supercritical localized potential well on different sublattices, and show that it is possible only on rim sites, but not on hub site. The predicted effects are expected to naturally occur in artificial flat band lattices.

Preparation of novel Ti–Y/ZrO2 ceramic by two-step of mechanical alloying and microwave-assisted sintering process

Zirconia composite ceramic materials are popular for their many excellent properties. In this study, nTi-3Y–ZrO2 composite ceramics were produced by the mechanical alloying-microwave sintering method with different Ti-doping amounts and microwave sintering temperatures. The sample's phase composition, stability rate, lattice parameters, micromorphology, relative density, and grain size are characterized. The results showed that when the sintering temperature is 1200 °C, the samples with different doping amounts are mainly mixed crystalline structures with tetragonal and cubic phases, and the stability rate remains above 90 %. As TiO2 doping increases, the lattice parameters a(Å) and b(Å)first increase and then decrease, while the lattice parameter c (Å) shows an overall increasing trend. Raman data demonstrated that the increase in Ti content promoted the generation of tetragonal phase zirconia. The average grain size is 61.33 nm, 76.23 nm, 58.77 nm, 63.35 nm, and 68.99 nm, respectively. The increase in doping is also accompanied by a narrowing of the grain size distribution, which increases the sintering activity of the sample. In addition, the relative densities of the samples were 67.85 %, 73.94 %, 84.25 %, 84.87 %, and 77.54 %, respectively, showing a gradual increasing trend overall. When the microwave sintering temperature is 1200 °C, and the doping amount is 5Ti–3Y–92Zr, the performance of the sample is superior to other groups. The preparation of nTi-3Y–ZrO2 composite ceramics can provide certain ideas for preparing ceramic materials with excellent performance in various aspects.

High thermoelectric performance of aluminum-doped cuprous selenide thin films with exceptional flexibility for wearable applications

Flexible thin-film generators are a great promising energy source for wearable device applications. In this work, Al-doped Cu2Se thin film with highly (0l0) preferred orientation was achieved by magnetron co-sputtering deposition. It possessed a high ZT value of 0.76 at 275 °C, and further surface organic component coating treatment resulted in its exceptional flexibility. The Al dopant was proven to be successfully introduced into the lattice of Cu2Se samples, which can decrease carrier concentration and result in the enhancement of Seebeck coefficient. Meanwhile, a significant decline in lattice thermal conductivity was achieved after Al doping. The organic component coating can prevent the fracture of inorganic thin films after bending. The resistance difference (∆R/R0) after 1000 cycles of bending was lower than 10%, which is a great improvement compared with that in pristine thin film (over 15%). The thermoelectric device prepared by the Al-doped Cu2Se obtained a stable power density of ∼5.7 W m−2 at a temperature difference of 20 °C.

Determining weathering-induced heterogeneous oxidation profiles of polyethylene, polypropylene and polystyrene using laser-induced breakdown spectroscopy

Weathering-induced polymer degradation is typically heterogeneous which plays an integral part in fragmentation. Despite that, the current selection of techniques to investigate such heterogeneities, especially beneath the sample surface, is sparse. We introduce Laser-induced Breakdown Spectroscopy (LIBS) as an analytical tool and evaluate its performance for depth profiling. Three types of polymers were selected (polyethylene, polypropylene, and polystyrene) that were aged under controlled conditions. We demonstrate that LIBS can detect heterogeneous oxidation on the surface and inside the samples. The results reveal that different oxidation behaviors are linked to the sample's lattice structure and the subsequent formation of microcracks. This implies that LIBS is beneficial to give additional insights into the weathering and degradation behavior of environmentally relevant plastics.

Multiscale topology optimization of cellular structures using Nitsche-type isogeometric analysis

This paper proposes a multiscale topology optimization method using Nitsche-type isogeometric analysis (IGA) for design of structures described by multiple non-uniform rational B-spline (NURBS) patches. In this method, at macroscale, unknown structural responses are calculated by Nitsche-type IGA, which not only ensures the consistency between geometric and analytical models, but also offers an effective way to enforce kinematic compatibility and mechanical equilibrium on interfaces between adjacent NURBS patches. At microscale, mechanical properties of microstructures are predicted by a Kriging metamodel at a low computational cost, which is constructed via some sample lattice unit cells (LUCs). In addition, analytical computation of sensitivities for coupled elements is developed. Finally, the structures are infilled by graded LUCs according to the density distribution within the design space. Some 2D and 3D numerical examples with conforming and non-conforming NURBS patches are presented to test the proposed method. Results indicate that the proposed method is effective for design of structures described by multiple NURBS patches.

Sol–gel combustion derived novel ternary transition metal boride-anisotropic magnetic powders and their magnetic property

We investigated the auto-ignition based sol–gel approach for the synthesis of ternary transition metal boride (TTMB) powders and studied their magnetic property. The obtained TTMB powders were found to have different crystallinity and magnetic behavior, based on the boron to metal ratio and further introduction of dysprosium into one of the sample lattice. The magnetic results obtained by vibrating sample magnetometer shows that TTMB is a soft magnet which demonstrates high ferromagnetic behavior with increased magnetic saturation based on the boron content, while the dysprosium based TTMB on contrary was found to exhibit an antiferromagnetic behavior. The TTMB powder showed no impurities as observed in Raman spectroscopy. The morphology of the powders obtained microscopically displays distinctive facets in the crystalline samples. The TTMB powders can be prospectively used in different polymer matrix to fabricate novel devices for sensors, environmental catalysts, radiation shielding and contrasting agents etc., to name a few.

Tailoring the structural, optical, photoluminescence, dielectric and electrical properties of Zn0·6Ni0·2Mg0·2Fe2-xLaxO4 (x = 0.00, 0.0125, 0.0250, 0.0375)

The green synthesis approach was used to manufacture the lanthanum modified spinel ferrites, which had the formula Zn0·6Ni0·2Mg0·2Fe2-xLaxO4 and were heated at 100 °C for 2 h. Through the use of XRD, FTIR, UV–visible, RLC study, four probe I–V, and PL spectroscopy the structural, optical, dielectric, electrical, and photoluminescence features were examined. XRD results confirmed that spinel ferrite have a cubic network. The substitution of La ions causes an overall increase in sample's lattice constants, which was credited to the disparity in ionic radii between Fe3+ (0.63 Aͦ) and La3+ (1.061 Aͦ) ions. From the XRD data, it was possible to compute the cationic distributions, oxygen positional parameters, tolerance factor, interatomic distances, bond lengths, bond length angles, and positional parameters. The computed Eg from the UV–Visible spectroscopy was decreased from 2.5 to 1.8eV. FTIR results revealed octahedral absorption band having 557.32–550.57 cm−1 range. The value of force constant from FTIR was revealed in the range of 2.27–2.21 dyne cm−1. The dielectric losses and constant are decreasing, whereas ac conductivity exhibited expanding behavior with high frequency. PL test result shows that La doping improves the material's light response, so the result showed that La-doped materials are suitable for magneto-optic devices. Electrical properties show that DC electrical resistivity decreases in the range of 1.65 × 10°5–5.01 × 10°3 Ω-cm. So, they are suitable for high-frequency circuits.

Lorentz-covariant sampling theory for fields

Sampling theory is a discipline in communications engineering involved with the exact reconstruction of continuous signals from discrete sets of sample points. From a physics perspective, this is interesting in relation to the question of whether spacetime is continuous or discrete at the Planck scale, since in sampling theory we have functions which can be viewed as equivalently residing on a continuous or discrete space. Further, it is possible to formulate analogues of sampling which yield discreteness without disturbing underlying spacetime symmetries. In particular, there is a proposal for how this can be adapted for Minkowski spacetime. Here we will provide a detailed examination of the extension of sampling theory to this context. We will also discuss generally how spacetime symmetries manifest themselves in sampling theory, which at the surface seems in conflict with the fact that the discreteness of the sampling is not manifestly covariant. Specifically, we will show how the symmetry of a function space with a sampling property is equivalent to the existence of a family of possible sampling lattices related by the symmetry transformations.

Generative learning for the problem of critical slowing down in lattice Gross-Neveu model

In lattice field theory, Monte Carlo simulation algorithms get highly affected by critical slowing down in the critical region, where autocorrelation time increases rapidly. Hence the cost of generation of lattice configurations near the critical region increases sharply. In this paper, we use a Conditional Generative Adversarial Network (C-GAN) for sampling lattice configurations. We train the C-GAN on the dataset consisting of Hybrid Monte Carlo (HMC) samples in regions away from the critical region, i.e., in the regions where the HMC simulation cost is not so high. Then we use the trained C-GAN model to generate independent samples in the critical region. We perform both interpolation and extrapolation to the critical region. Thus, the overall computational cost is reduced. We test our approach for Gross-Neveu model in 1+1 dimension. We find that the observable distributions obtained from the proposed C-GAN model match with those obtained from HMC simulations, while circumventing the problem of critical slowing down.

Femtosecond Laser Induced Lattice Deformation in KTN Crystal.

In recent years, many novel optical phenomena have been discovered based on perovskite materials, but the practical applications are limited because of the difficulties of device fabrication. Here, we propose a method to directly induce localized lattice modification inside the potassium tantalate niobate crystal by using the femtosecond laser. This selective modification at the processed regions and the surrounding areas is characterized by two-dimensional Raman spectrum mapping. The spectrum variations corresponding to specific lattice vibration modes demonstrate the lattice structure deformation. In this way, the lattice expansion at the femtosecond laser irradiated regions and the lattice compression at the surrounding areas are revealed. Furthermore, surface morphology measurement confirms this lattice expansion and suggests the extension of lattice structure along the space diagonal direction. Moreover, the existence of an amorphization core is revealed. These modifications on the sample lattice can induce localized changes in physicochemical properties; therefore, this method can realize the fabrication of both linear diffraction and nonlinear frequency conversion devices by utilizing the novel optical responses of perovskite materials.

Enhanced Flux Pinning Performance of Bulk MgB2 via Immersion of Synthetic Motor Oil

The present investigation focuses on the incorporation of synthetic motor oil as an inexpensive, rich carbon source in bulk MgB2 superconductor and its effect on superconducting and flux pinning properties. A set of three MgB2 bulk samples were prepared from commercial high-purity powders of Mg metal and amorphous B powder utilizing a conventional in situ solid-state reaction process. Before sintering, the MgB2 samples were immersed in used and new synthetic motor oil for a standby time of 30 min and sintered in pure Ar atmosphere at 775 °C for 3 h. X-ray powder diffractometer (XRD) analysis confirmed that single-phase formation of MgB2 with a small shift in X-ray diffraction peaks especially at (110) towards the peak position due to the effect of carbon substitution into the boron sites in lattice for samples immersed in new and used synthetic oil. The magnetization measurements indicated the Tc (onset) value to somewhat decrease to 37.5 K as a result of carbon doping. Microstructural observations with scanning electron microscopy (SEM) suggested that fine nano-sized MgB2 grains improved self-field critical current density around 3.8 × 105 A/cm2 at 20 K for all samples studied. Further, the high-field critical current density (Jc) was improved especially for the sample immersed in used synthetic motor oil with the value of 2.7 × 104 A/cm2, 6 × 103 A/cm2 at 20 K, and at 3 T and 4 T, which is higher as compared to pure-MgB2 sample. In essence, the results signify that the bulk MgB2 samples immersed with used synthetic motor oil would improve the bulk performance at high magnetic fields indicating to be a viable option for industrial applications.

Structural, vibrational and magnetic properties of monoclinic La2FeMnO6 double perovskite

We report the synthesis of the double perovskite La2FeMnO6 and a complete characterization of this system by using X-ray diffraction, Raman and Fourier transform infrared (FT-IR) spectroscopy, scanning electron microscopy (SEM), vibrating sample magnetometer, Mossbauer spectroscopy and lattice dynamic calculations. The ambient structure of the La2FeMnO6 was well refined using monoclinic system and P21/n-space group, with two formulas per unit cell (Z = 2). SEM reveals that the sample is formed by particles with quasi-spherical morphology, randomly distributed in clusters. The investigation by Mössbauer spectroscopy identified that the incorporation of iron atoms occurred successfully in the analyzed structure since two paramagnetic phases were identified. The magnetization versus applied field (MxH) curve of La2FeMnO6 at room temperature is discussed. The LFMO double perovskite EPR spectrum indicates the coexistence of paramagnetic resonance (PM) and antiferromagnetic resonance (AFM), being a strong indication of the coexistence of PM and AFM clusters. Moreover, vibrational properties were calculated using a rigid ion model in order to assign the experimental Raman and infrared bands. All these results making the La2FeMnO6 an interesting material with practical applications and for the scientific investigations.

Structure Determination, Mechanical Properties, Thermal Stability of Co2MoB4 and Fe2MoB4.

The precise determination of atomic position of materials is critical for understanding the relationship between structure and properties, especially for compounds with light elements of boron and single or multiple transition metals. In this work, the single crystal X-ray diffraction is employed to analyze the atomic positions of Co2MoB4 and Fe2MoB4 with a Ta3B4-type structure, and it is found that the lengths of B-B bonds connecting the two zig-zag boron chains are 1.86 Å and 1.87 Å, but previously unreported 1.4 Å. Co and Fe atoms occupy the same crystallographic position in lattice for the doped samples and the valence is close to the metal itself, and Co/Fe K-edge X-ray Absorption Fine Structure(XAFS) spectra of borides with different ratios of Co to Fe are collected to detect the local environment and chemical valence of Co and Fe. Vickers hardness and nano indentation measurements are performed, together with the Density Functional Theory (DFT) calculations. Finally, Co2MoB4 possess better thermal stability than Fe2MoB4 evaluated by Thermogravimetric Differential Thermal Analysis (TG-DTA) results.

Sampling lattices in semi-grand canonical ensemble with autoregressive machine learning

Calculating thermodynamic potentials and observables efficiently and accurately is key for the application of statistical mechanics simulations to materials science. However, naive Monte Carlo approaches, on which such calculations are often dependent, struggle to scale to complex materials in many state-of-the-art disciplines such as the design of high entropy alloys or multi-component catalysts. To address this issue, we adapt sampling tools built upon machine learning-based generative modeling to the materials space by transforming them into the semi-grand canonical ensemble. Furthermore, we show that the resulting models are transferable across wide ranges of thermodynamic conditions and can be implemented with any internal energy model U, allowing integration into many existing materials workflows. We demonstrate the applicability of this approach to the simulation of benchmark systems (AgPd, CuAu) that exhibit diverse thermodynamic behavior in their phase diagrams. Finally, we discuss remaining challenges in model development and promising research directions for future improvements.

Extreme Learning Machine Approach to Modeling the Superconducting Critical Temperature of Doped MgB2 Superconductor

Magnesium diboride (MgB2) superconductor combines many unique features such as transparency of its grain boundaries to super-current flow, large coherence length, absence of weak links and small anisotropy. Doping is one of the mechanisms for enhancing these features, as well as the superconducting critical temperature, of the compound. During the process of doping, the MgB2 superconductor structural lattice is often distorted while the room temperature resistivity, as well as residual resistivity ratio, contributes to the impurity scattering in the lattice of doped samples. This work develops three extreme learning machine (ELM)-based empirical models for determining MgB2 superconducting critical temperature (TC) using structural distortion as contained in lattice parameters (LP) of doped superconductor, room temperature resistivity (RTR) and residual resistivity ratio (RRR) as descriptors. The developed models are compared with nine different existing models in the literature using different performance metrics and show superior performance over the existing models. The developed SINE-ELM-RTR model performs better than Intikhab et al. (2021)_linear model, Intikhab et al. (2021)_Exponential model, Intikhab et al. (2021)_Quadratic model, HGA-SVR-RRR(2021) model and HGA-SVR-CLD(2021) model with a performance improvement of 32.67%, 29.56%, 20.04%, 8.82% and 13.51%, respectively, on the basis of the coefficient of correlation. The established empirical relationships in this contribution will be of immense significance for quick estimation of the influence of dopants on superconducting transition temperature of MgB2 superconductor without the need for sophisticated equipment while preserving the experimental precision.