Search Results (214)

We studied the changes of martensite average temperature T_M in a wide range of Heusler alloys derived from a Ni-Mn-Ga multifunctional compound prepared by arc melting. Based on prepared alloys and supplemented by the literature data, we demonstrated that criteria based on valence electron or non-bonding electron concentration per atom often failed in many different cases, in particular for isoelectronic compounds and Heusler alloys with Sb and Sn. Thus, we suggest an empirical criterion for estimating the temperature of martensitic transformation T_M in Ni-Mn-based Heusler alloys. It is built on valence electron concentration per atomic volume. Suggested criterion well-describes the experiment and data available in literature. Although it can be used for predicting T_M in complexly alloyed Ni-Mn-based Heusler alloys. Full article

Mixed amine/sulfolane (TMS) biphasic solutions have gained attention for their adjustable structure–activity relationships and lower regeneration energy. In this study, monoethanolamine (MEA) is employed as the main absorbent and polyamine as the co-absorbent, which are subsequently mixed with the phase separation promoter sulfolane (TMS) to form ternary biphasic solvent systems. Polyamine co-absorbents include 3-Dimethylaminopropylamine (DMAPA), 3-Diethylaminopropylamine (DEAPA), and Diethylenetriamine (DETA). Phase separation, absorption, and desorption performances were systematically studied. Reaction and phase separation mechanisms were elucidated through ¹³C nuclear magnetic resonance (NMR) spectroscopy. The overall mass transfer coefficients (K_G) were measured using a wetted wall column (WWC). Variations in the amine-to-sulfolane concentration ratio showed minimal impact on phase volume, while temperature and solvent composition significantly influenced phase separation behavior. All three solvents exhibited superior CO₂ capture performance, with CO₂ loadings in the rich phases ranging from 4.09 to 4.71 mol/L and over 96.82% of CO₂ concentrated in them, cyclic capacities reached or exceeded 3 mol/L, and regeneration energy consumption was 29.63–55.51% lower than 5 M MEA. ¹³C NMR analysis indicated that multiple N atoms in polyamines promoted the formation of additional ionic species during CO₂ absorption, thereby enhancing phase separation completeness. Furthermore, K_G values for the ternary systems exceeded that of conventional MEA, with the MEA/DEAPA/TMS system exhibiting a 1.7-fold increase. These findings demonstrated the industrial potential of MEA/polyamine/TMS biphasic solvents for efficient CO₂ capture. Full article

Defect engineering can effectively regulate the catalytic activity of single-atom catalysts anchored on the graphene substrate. Based on graphene with topological defects consisting of 5,7-membered carbon rings, we designed and investigated twenty transition metal single-atom catalysts TM-N₄-C57 (TM = Sc~Cu, Zr~Mo, Ru, Rh, Hf~Ir) for electrocatalytic nitrogen reduction reaction (NRR) using density functional theory (DFT) calculations. Employing a screening strategy that considers binding energy, N₂ adsorption, catalytic activity, selectivity, and thermal stability, we ultimately screened out two electrocatalysts (Mo-N₄-C57 and W-N₄-C57) with excellent catalytic activity and selectivity. The NRR pathways on these two catalysts proceed through distal and consecutive pathways, with limiting potentials of −0.19 and −0.53 V for Mo-N₄-C57 and W-N₄-C57, respectively. The activity origin was elucidated through the analysis of partial density of states (PDOS) and crystal orbital Hamilton populations (COHP), suggesting that the interaction between Mo and NH₂ in the *NH₂ intermediate is relatively weak. An excellent linear relationship between U_L and ICOHP has been identified, suggesting it as a descriptor. This work provides a theoretical basis for designing efficient NRR catalysts with modified second coordination spheres. Full article

Alpha helical transmembrane proteins are a specific type of membrane proteins that consist of helices spanning the entire cell membrane. They make up almost a third of all transmembrane (TM) proteins and play a significant role in various cellular activities. The structural prediction of these proteins is crucial in understanding how they behave inside the cell and thus in identifying their functions. Despite their importance, only a small portion of TM proteins have had their structure determined experimentally. Inter-helical residue contact is one of the most successful computational approaches for reducing the TM protein fold search space and generating an acceptable 3D structure. Most current TM protein residue contact predictors use features extracted only from protein sequences to predict residue contacts. However, these features alone deliver a low-accuracy contact map and, as a result, a poor 3D structure. Although there are models that explore leveraging features extracted from protein 3D structures in order to produce a better representative contact model, such an approach remains theoretical, assuming the structure features are available, whereas in reality they are only available in the training data, but not in the test data, whose structure is what needs to be predicted. This presents a brand new transfer learning paradigm: training examples contain two sets of features, but test examples contain only one set of the less informative features. In this work, we propose a novel approach that can train a model with training examples that contain both sequence features and atomic features and apply the model on the test data that contain only sequence features but not atomic features, while still improving contact prediction rather than using sequence features alone. Specifically, our method, AT-TSVM, employs Active Transfer for Transductive Support Vector Machines, which is augmented with transfer, active learning and conventional transductive learning to enhance contact prediction accuracy. Results from a benchmark dataset show that our method can boost contact prediction accuracy by an average of 5 to 6% over the inductive classifier and 2.5 to 4% over the transductive classifier. Full article

This study aims to optimize the variables of the gas metal arc welding (GMAW)-based wire arc additive manufacturing (WAAM) process namely, wire feed speed (WFS), voltage (V), and travel speed (TS), to achieve the desired bead geometries, specifically bead width (BW), and bead height (BH) on a mild steel substrate. The selection of WAAM parameters significantly influences the characteristics of multi-layer structures in terms of bead geometry. By optimizing these variables, the research seeks to enhance bead geometry properties, thereby improving the overall performance of the WAAM process. Single-layer depositions were performed using TM-B6 metallic wire using Box–Behnken design methodology. Multivariable regression equations were formulated to establish relationships between design variables and their corresponding responses, with their validity assessed through ANOVA. For both BW and BH responses, the R² and adjusted R² values were found to be close to unity, indicating excellent model fitness. The results demonstrate the high accuracy of the models, enabling effective analysis of the influence of process parameters on weld bead geometry and accurate prediction of bead dimensions across the design space. The main effects plot illustrates how WFS, V, and TS affect bead width and bead height. Atomic Search Optimization (ASO) was employed to determine optimal parameter combinations. An objective function with equal weightage (0.5) for BH and BW was formulated, resulting in optimized values of BW and BH (4.01 mm and 5.86 mm, respectively) at WFS: 13 m/min, TS: 10 mm/s, and V: 20 V. The obtained findings confirm the high accuracy of the models and their effectiveness in analyzing and optimizing WAAM process parameters. Full article

This research seeks to investigate extremely efficient catalysts for the nitrogen reduction process (NRR), utilizing machine learning (ML)-aided density functional theory (DFT) computations. Specifically, we investigate dual transition metal atoms anchored on hexagonal nitrogen-doped graphene (TM₁-TM₂@N₆G) as prospective high-activity catalysts for the NRR. The findings indicate that the synergistic effect of dual transition metal atoms in the TM₁-TM₂@N₆G catalyst overcomes the intrinsic constraints of the linear relationship among intermediates, facilitating the activation and adsorption of N₂, thereby exhibiting significant potential for ammonia synthesis through N₂ reduction. Particularly, four catalysts screened by ML and DFT exhibit good stability and excellent selectivity and activation towards N₂. Among them, the catalysts Ti-Cr@N₆G, Ti-Mo@N₆G, and Ti-Pd@N₆G possess two reaction pathways with minimum reaction energies of 0.55 eV, 0.50 eV, and 0.40 eV, respectively. Remarkably, Ti-Co@N₆G, which features a single reaction pathway, exhibits a reaction energy lower than 0.05 eV, allowing the NRR to proceed spontaneously. It is noteworthy that incorporating ML into DFT calculations facilitates the rapid screening of all transition metal combinations, significantly accelerating the research on catalytic performance and optimizing the selection of catalysts. Full article

The crystal structure of kuliokite-(Y), Y₄Al(SiO₄)₂(OH)₂F₅, has been re-investigated using the material from the type locality the Ploskaya Mt, Kola peninsula, Russian Arctic. It has been shown that in contrast to previous studies, the mineral is monoclinic, Im, with a = 4.3213(1), b = 14.8123(6), c = 8.6857(3) Å, β = 102.872(4)°, and V = 541.99(3) ų. The crystal structure was solved and refined to R₁ = 0.030 on the basis of 3202 unique observed reflections. The average chemical composition determined by electron microprobe analysis is (Y_2.96Yb_0.49Er_0.27Dy_0.13Tm_0.07Lu_0.05Ho_0.05Gd_0.01Ca_0.01)_Σ4.04Al_0.92Si_2.04O₈-[(OH)_2.61F_4.42]_Σ7.03; the idealized formula is (Y,Yb,Er)₄Al[SiO₄]₂(OH)_2.5F_4.5. The crystal structure of kuliokite-(Y) contains two symmetrically independent Y sites, Y1 and Y2, coordinated by eight and seven X anions, respectively (X = O, F). The coordination polyhedra can be described as a distorted square antiprism and a distorted pentagonal bipyramid, respectively. The refinement of site occupancies indicated that the mineral represents a rare case of HREE fractionation among two cation sites driven by their coordination numbers and geometry. In agreement with the lanthanide contraction, HREEs are selectively incorporated into the Y2 site with a smaller coordination number and tighter coordination environment. The strongest building unit of the structure is the [AlX₂(SiO₄)₂] chain of corner-sharing AlX₆ octahedra and SiO₄ tetrahedra running along the a axis. The chains have their planes oriented parallel to (001). The Y atoms are located in between the chains, along with the F⁻ and (OH)⁻ anions, providing the three-dimensional integrity of the crystal structure. Each F⁻ anion is coordinated by three Y³⁺ cations to form planar (FY₃)⁸⁺ triangles parallel to the (010) plane. The triangles share common edges to form [F₂Y₂]⁴⁺ chains parallel to the a axis. The analysis of second-neighbor coordination of Y sites allowed us to identify the structural topology of kuliokite-(Y) as the only case of the skd network in inorganic compounds, previously known in molecular structures only. The variety of anionic content in the mineral allows us to identify the potential existence of two other mineral species that can tentatively be named ‘fluorokuliokite-(Y)’ and ‘hydroxykuliokite-(Y)’. Full article

The ideal crystal symmetry of the 1T-TiS₂ lattice results in a non-magnetic structure. However, recent studies have demonstrated that it may become magnetic upon substitution with transition-metal (TM) atoms. In this study, we examine the mechanisms and interactions that allow magnetic exchange through the TiS₂ matrix. Using density functional theory, we model the substitutional TM-doped TiS₂ (TM = V, Cr, or Mn) system with varying spatial distances to examine the effects on the magnetic exchange. Since pristine 1T-TiS₂ is weakly semiconducting, there is a possibility that the introduction of metallic atoms may induce an RKKY-like interaction. We find that the substitution of vanadium produces a standard exchange through the orbital interactions. However, the introduction of chromium and manganese may generate RKKY interactions with the conduction electrons. Overall, a more comprehensive understanding of how different dopants affect magnetic behavior and communicate through the lattice can enable the design of spintronic devices, which offer the potential for more energy-efficient technologies and a deeper understanding of low-dimensional systems. Full article

Room-temperature sodium–sulfur (RT Na-S) batteries hold great potential in the field of large-scale energy storage due to their high theoretical energy density and low cost of raw materials. However, the inherent low conductivity, notorious shuttling, and sluggish kinetics of cathode materials cause the loss of active substances and capacity delay, hindering the practical application of RT Na-S batteries. Owing to their low cost, variable oxidation states, and unsaturated d orbitals, transition metal (TM)-based catalysts have been extensively studied in circumventing the above shortcomings. Herein, the review first elaborates on the reaction mechanisms and current challenges of RT Na-S batteries. Subsequently, the role and function mechanism of TM-based catalysts (including single/dual atoms, nanoparticles, compounds, and heterostructures) in RT Na-S batteries are described. Specifically, based on the theories of electronic transfer and atomic orbital hybridization, the interaction mechanism between TM-based catalysts and polysulfides, as well as the catalytic performance, are systematically discussed and summarized. Finally, a discussion on the challenges and future research perspectives associated with TM-based catalysts for RT Na-S batteries is provided. Full article

Hollow coaxial double-shell submicron fibers were fabricated by combining electrospinning and atomic layer deposition (ALD). Polyvinyl alcohol (PVA) fibers were electrospun to serve as templates for the subsequent atomic layer deposition (ALD) of ZnO doped with transition metals (TM: Ni, Co, and Fe). An inner shell of amorphous Al₂O₃ was first deposited at low-temperature ALD to protect the polymer template. The PVA core was then removed through high-temperature annealing in air. Finally, a top shell of TM-doped ZnO was deposited at an elevated temperature within the ALD window for ZnO. The morphology, microstructure, elemental composition, and crystallinity of these submicron hollow double-shell fibers were thoroughly investigated using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Full article

Trace metal (TM) concentrations and carcinogenic risk were determined in ninety-two edible samples of the triggerfish Balistes spp. from the RAMSAR site 1826 San Ignacio-Navachiste-Macapule Lagoon Complex (NAV). The acid digestion method and an atomic absorption spectrophotometer were used to determine TM concentrations. Calibration curves were carried out using TORT-3 reference materials. The blank and certified reference materials were treated using the same procedure as a sample. TM sequence was Zn > Fe > Mn > Cu = Pb > Ni > Cd, and a correlation (p = 0.0169) between size and concentrations was found. No correlation (p = 0.079) was found between weight and concentrations, or sampling sites and the concentrations. The highest concentrations were found during the summer, followed by the spring and winter of 2017, while the lowest was found in the winter of 2018. The Zn was significantly higher in summer-17. The Target Hazard Quotient (THQ) was <1 for Pb, Ni, Cd, Fe, Zn, and Cu, and 1.39 for Mn. Cd and Pb resulted in carcinogenic potential (CsFo < 1) with a very low probability. The TM concentrations and bioaccumulation in triggerfish showed no consumption risk, due to its omnivorous diet, and trophic transfer rates were described for aquatic food webs. Full article

Al-based intermetallic compounds possess excellent mechanical and thermal properties, making them promising candidates for high-temperature structural applications. In this study, the structural stability, mechanical properties, and electronic characteristics of Al₅TM (TM = Mo, Nb, Os, Re, Ru, Ta, Tc, Ti) intermetallic compounds were systematically investigated using first-principles calculations based on density functional theory. All alloys exhibit negative formation energy, indicating favorable thermodynamic stability. Elastic constant analysis shows that all compounds satisfy the Born stability criteria, confirming their mechanical stability. Among them, Al₅Mo (205.9 GPa), Al₅Nb (201.1 GPa), and Al₅Ta (204.1 GPa) exhibit relatively high Young’s moduli, while Al₅Os, Al₅Re, and Al₅Ru demonstrate large bulk moduli and good ductility. The high Debye temperatures of Al₅Mo (600.5 K) and Al₅Nb (606.7 K) suggest excellent thermal stability at elevated temperatures. Electronic structure analysis reveals that all alloys exhibit metallic behavior with no band gap near the Fermi level. The hybridization between TM-d and Al-3p orbitals enhances the covalent bonding between Al and TM atoms. This study provides theoretical guidance for the design and application of high-performance Al-based intermetallic compounds. Full article

Electromigration (EM), current-driven atomic diffusion in interconnect metals, critically threatens integrated circuit (IC) reliability via void-induced open circuits and hillock-induced short circuits. This review examines EM’s physical mechanisms, influencing factors, and advanced models, synthesizing seven primary determinants: current density, temperature, material properties, microstructure, geometry, pulsed current, and mechanical stress. It dissects the coupled contributions of electron wind force (dominant EM driver), thermomigration (TM), and stress migration (SM). The review assesses four foundational modeling frameworks: Black’s model, Blech’s criterion, atomic flux divergence (AFD), and Korhonen’s theory. Despite advances in multi-physics simulation and statistical EM analysis, achieving predictive full-chip assessment remains computationally challenging. Emerging research prioritizes the following: (i) model order reduction methods and machine-learning solvers for verification of EM in billion-scale interconnect networks; and (ii) physics-informed routing optimization to inherently eliminate EM violations during physical design. Both are crucial for addressing reliability barriers in IC technologies and 3D heterogeneous integration. Full article

A simple and efficient dispersive micro solid-phase extraction (DMSPE) method using nano-TiO₂ as a sorbent was developed for the separation and preconcentration of (ultra) trace levels of lead in water samples prior to quantification by electrothermal atomic absorption spectrometry (ETAAS). Key experimental parameters affecting the DMSPE process, including pH, ionic strength, sorbent dosage, and preconcentration factor, were optimized. The optimized method demonstrated a preconcentration factor of 20, a relative standard deviation below 4.5%, and a detection limit of 0.11 µg/L. The procedure was validated using certified reference material (CRM TM-25.5) and applied to real water samples from a lake, a residential well, and industrial wastewater. Satisfactory recoveries (89–103%) confirmed the reliability of the method for the determination of low lead concentrations in complex matrices. Full article

The electrochemical reduction of carbon monoxide (COER) offers a promising route for generating value-added multi-carbon (C₂₊) products, such as ethanol, but achieving high catalytic performance remains a significant challenge. Herein, we performed comprehensive density functional theory (DFT) computations to evaluate CO-to-ethanol conversion on single metal atoms anchored on graphitic carbon nitride (TM/g–CN). We showed that these metal atoms stably coordinate with edge N sites of g–CN to form active catalytic centers. Screening 20 TM/g–CN candidates, we identified V/g–CN and Zn/g–CN as optimal catalysts: both exhibit low free-energy barriers (<0.50 eV) for the key ^*CO hydrogenation steps and facilitate C–C coupling via an Eley–Rideal mechanism with a negligible kinetic barrier (~0.10 eV) to yield ethanol at low limiting potentials, which explains their superior COER performance. An analysis of d-band centers, charge transfer, and bonding–antibonding orbital distributions revealed the origin of their activity. This work provides theoretical insights and useful guidelines for designing high-performance single-atom COER catalysts. Full article