Metallic Systems Research Articles

Interface Engineering of Platinum–Copper Alloy/Titanium Dioxide for Enhanced Photocatalytic Carbon Dioxide Reduction

To develop an efficient photocatalytic carbon dioxide (CO2) reduction aimed at mitigating CO2 emissions and greenhouse effects, we propose a straightforward strategy involving hydrogen reduction treatment of PtCu/Ti to create the PtCu/Ti-H2 catalyst with a distinctive interface structure. Compared with the fresh PtCu/Ti catalyst and the benchmark anatase TiO2, the CH4 production of the PtCu/Ti-H2 catalyst increased by 2 times and 81.6 times, respectively. Comprehensive characterizations confirmed the formation of Ptδ+-Ov-Ti3+ and Cuδ+-Ov-Ti3+ interface structures on the hydrogen-treated PtCu/Ti-H2 catalyst, enhancing light absorption and the separation of photogenerated charge carriers. Further investigation into the reaction mechanism revealed that the Ptδ+-Ov-Ti3+ and Cuδ+-Ov-Ti3+ species on PtCu/Ti-H2 serve as more favorable sites for CO2 adsorption and activation, promoting an enhanced formaldehyde mechanism. This study not only elucidates the relation between photocatalytic CO2 reduction activity and the PtCu/Ti interface structure but also offers a novel strategy for designing alloy/oxide-based catalysts for CO2 photoreduction, overcoming the limitations of previous studies that focused on metal or vacancy systems.

A Divide-and-Conquer Approach to Nanoparticle Global Optimisation Using Machine Learning.

Global optimization of the structure of atomic nanoparticles is often hampered by the presence of many funnels on the potential energy surface. While broad funnels are readily encountered and easily exploited by the search, narrow funnels are more difficult to locate and explore, presenting a problem if the global minimum is situated in such a funnel. Here, a divide-and-conquer approach is applied to overcome the issue posed by the multifunnel effect using a machine learning approach, without using a priori knowledge of the potential energy surface. This approach begins with a truncated exploration to gather coarse-grained knowledge of the potential energy surface. This is then used to train a machine learning Gaussian mixture model to divide up the potential energy surface into separate regions, with each region then being explored in more detail (or conquered) separately. This scheme was tested on a variety of multifunnel systems and yielded significant improvements to the times taken to locate the global minima of Lennard-Jones (LJ) nanoparticles, LJ75 and LJ104, as well as two metallic systems, Au55 and Pd88. However, difficulties were encountered for LJ98, providing insight into how the scheme could be further improved.

Tailoring Superatomic Stability with Transition Metals in Silicon Cages: Shrinking to M@Si15 (M = Re, Os, Ir).

The design of materials with intriguing electronic properties is crucial for advancing nanoscale technologies, where precise control over atomic structure and electronic behavior is essential. Metal-encapsulating silicon cage superatoms (SAs) provide a new paradigm for molecular-scale material design, allowing fine-tuning of both structure and electronic characteristics. The formation of superatoms mimicking halogens, noble gases, and alkali metals has been well-studied, particularly with M@Si16, where early transition metals from groups 3 to 5 stabilize within a Si16 cage, achieving a 68-electron configuration. For late transition metals with excess electrons, a Si15 cage offers enhanced stability by fulfilling the 68-electron rule with one fewer Si atom. This research synthesizes Si15 cage-SAs with rhenium (Re) from group 7 and iridium (Ir) from group 9 on p-type and n-type organic substrates. The stability of Re@Si15 and Ir@Si15 is evaluated via oxidative reactivity with X-ray photoelectron spectroscopy and theoretical calculations, including osmium (Os) from group 8. Re@Si15-, Os@Si150, and Ir@Si15+ exhibit superatomic behaviors similar to halogens, noble gases, and alkali metals due to the 68-electron shell closure. Among them, Re@Si15- on p-type organic substrates shows superior electronic and geometric properties. These findings advance our understanding of M@Sin systems for transition metals, addressing longstanding questions about their properties at n = 15 and 16.

Basics and Advances of Manganese-Based Cathode Materials for Aqueous Zinc-Ion Batteries.

It is greatly crucial to develop low-cost energy storage candidates with high safety and stability to replace alkali metal systems for a sustainable future. Recently, aqueous zinc-ion batteries (ZIBs) have received tremendous interest owing to their low cost, high safety, wide oxidation states, and sophisticated fabrication process. Nanostructured manganese (Mn)-based oxides in different polymorphs are the potential cathode materials for the widespread application of ZIBs. However, Mn-based oxide materials suffer from several drawbacks, such as low electronic/ionic conductivity and poor cycling performance. To overcome these issues, various structural modification strategies have been adopted to enhance their electrochemical activity, including phase/defect engineering, doping with foreign atoms (e.g., metal and/or nonmetal atoms), and coupling with carbon materials or conducting polymers. Herein, this review targets to summarize the advantages and disadvantages of the above-mentioned strategies to improve the electrochemical performance of the cathodic part of ZIBs. The challenges and suggestions for the development of manganese oxides for ZIBs are put forward.

Solid–Liquid Diffusion Stresses Leading to Voiding

AbstractThis paper discusses cavitation within a two-phase solid–liquid enclosed system due to interdiffusion. This mechanism is discussed within the context of solid–liquid interdiffusion bonding for metal systems and the voids which are caused by this mechanism. A case study composed of liquid (Sn), Ni3Sn4, and (Ni) phases was used. The mechanical tension and bubble volume resulting from the mechanically enclosed system during isothermal solidification at 250 °C were calculated using a fitted 1D growth model coupled with thermodynamics. Thermodynamic energy calculations showed that it becomes favorable for cavitation after 6 seconds for a starting liquid pocket of 5 µm3. The critical pressure for this cavitation was − 0.029 GPa. The volumetric change for the reaction was determined to be − 12.3 vol pct by a partial molar volume balance. While the volumetric change determined by the thermodynamics found − 7.2 vol pct. The likely presence of unwettable inclusions in non-pure liquids would circumvent this cavitation mechanism, even though cavitation conditions are present. Meaning cavitation for these systems can only be expected when the liquid metal purity is sufficient. Lastly, the bubble growth is attributed to a combination of thermodynamic bubble growth and Kirkendall vacancies.

Antimicrobial Peptide Delivery Systems as Promising Tools Against Resistant Bacterial Infections

The extensive use of antibiotics during recent years has led to antimicrobial resistance development, a significant threat to global public health. It is estimated that around 1.27 million people died worldwide in 2019 due to infectious diseases caused by antibiotic-resistant microorganisms, according to the WHO. It is estimated that 700,000 people die each year worldwide, which is expected to rise to 10 million by 2050. Therefore, new and efficient antimicrobials against resistant pathogenic bacteria are urgently needed. Antimicrobial peptides (AMPs) present a broad spectrum of antibacterial effects and are considered potential tools for developing novel therapies to combat resistant infections. However, their clinical application is currently limited due to instability, low selectivity, toxicity, and limited bioavailability, resulting in a narrow therapeutic window. Here we describe an overview of the clinical application of AMPs against resistant bacterial infections through nanoformulation. It evaluates metal, polymeric, and lipid AMP delivery systems as promising for the treatment of resistant bacterial infections, offering a potential solution to the aforementioned limitations.

A multifunctional coconut shell biochar modified by titanium dioxide for heavy metal removal in water/soil and tetracycline degradation

Heavy metals and tetracycline pollute the environment and endanger human health. This work prepared a multifunctional coconut shell biochar (Ti-XBC) through NaHCO3 activation and TiO2 modification. The modified coconut shell biochar was characterized by various methods. Ti-4BC exhibited excellent removal performance for heavy metals. The maximum adsorption capacity of Ti-4BC on Cd2+, Pb2+, Cr3+, and Cr6+ reached 104.2, 136.8, 101.2, 112.4 mg/g in water. The adsorption of Ti-4BC for four metal ions had a competitive effect in the binary metal system. It also reduced the mobility of four heavy metal ions in soil. Density functional theory (DFT) calculations were employed to explain the mechanism of heavy metal removal. Additionally, the degradation performance and mechanism of Ti-4BC towards tetracycline were investigated. The results indicated that the maximum degradation rate was 99.4%. Overall, this work developed a multifunctional material capable of both removing heavy metals and degrading antibiotics, addressing the issue of single-function in biochar. This provided a novel approach for tackling complex and diverse environmental pollution scenarios.

The use of nanotechnology in cosmetics

The nanoscience present in cosmetics, corresponds to a new segment that is showing results meaningful in comparison to traditional methods. In this sense, this article aimed to carry out an investigation of the main published studies on the techniques, advantages and disadvantages regarding the use of nanotechnology in cosmetology. The methodology used consists of reviewing the literature through research using keywords related to the proposed theme, in the SCIELO, PubMED and MEDLINE databases. The literature points to greater and more prolonged cutaneous penetration in the use of nanoparticles in detriment to traditional methods, as well as the targeting of actives to specific cell groups. In addition, the present nanostructures are presented, being the lipid, polymeric and metallic systems, as well as highlighting their main techniques and their benefits, such as biocompatibility and high delivery of actives, in addition to highlighting concerns about toxicological risks to the human body and the environment.

“Chacco” clay from the Peruvian highlands as a potential adsorbent of heavy metals in water

This research aimed to remove Cd (II), Cr (VI), Ni (II), Pb (II), and V (V) from aqueous solutions prepared in distilled water using “Chacco” clay from the Peruvian highlands as adsorbent. The adsorption process was carried out in Batch type systems for 120 min using solutions of each metal at a concentration of 5 mg/L in aqueous systems of a single metal or monometallic (MAS) and solutions of the five metals simultaneously or multimetallic (MMAS). For this purpose, the “Chacco” clay was first characterized by SEM-EDS analysis, finding a laminated clay structure with an elemental composition of C, Al, Fe, Na, Mg, Ca, K, As, Cu, Pd, O, and Ta. The results using 10 g/L of “Chacco” clay showed that the best adsorption efficiency in both MAS and MMAS aqueous systems is achieved at pH = 4 achieving in MAS aqueous systems the removal of 64.16 ± 0.98 % of Cd (II), 95.70 ± 0.81 % of Cr (VI), 97.20 ± 0.89 % of Ni (II), 92. 78 ± 0.79 % of Pb (II), and 95.80 ± 0.67 % of V (V), on the other hand, in aqueous MMAS systems a decrease in adsorption efficiency was observed, managing to remove 6.88 ± 0.53 % of Cd (II), 63.04 ± 0.94 of Cr (VI), 7.81 ± 0.43 % of Ni (II), 62.34 ± 0.77 % Pb (II), and 14.33 ± 0.56 % of V (V). The kinetic study showed that the adsorption mechanism would correspond to chemisorption since the process fitted best to the pseudo-second order model and Elovich. SEM-EDS analysis after adsorption confirmed the presence of the heavy metals under study in the “Chacco” clay. Metal adsorption is evidenced at 1418 cm−1 by -CH2-metal deformation vibrations according to FTIR analysis. In conclusion, the “Chacco” clay would be a promising adsorbent of heavy metals in polluted waters so that scaling up to real environments could be feasible. On the other hand, the “Chacco” clay is consumed by the population of Puno, Peru, therefore its potential impact on health should be evaluated due to its capacity to accumulate metals and the presence of Al in this clay.

Homogeneous Catalysis in N-Formylation/N-Methylation Utilizing Carbon Dioxide as the C1 Source.

The growing emphasis on sustainable chemistry has driven research into utilizing carbon dioxide (CO2) as a nontoxic, abundant, and cost-effective C1 building block. CO2 offers a promising avenue for direct conversion into valuable chemicals ranging from fuels to pharmaceuticals. This review focuses on the utilization of CO2 for reductive N-formylation/N-methylation reactions of various amines, providing advantages over conventional methods involving toxic CO and other methylating reagents. The approach employs readily available reductants such as silane, borane reagents, and hydrogen (H2). The discussion encompasses recent developments in transition metal and organocatalyst systems for these reactions, highlighting mechanistic interpretations and factors influencing product selectivity.

Efficient and Robust Ab Initio Self-Consistent Field Acceleration Algorithm Based on a Semiempirical Model Hamiltonian.

A novel doubly iterative self-consistent field (SCF) approach using a semiempirical model Hamiltonian (denoted as the SMH algorithm) is proposed to accelerate the Hartree-Fock (HF) and density functional theory (DFT) calculations. This method first constructs the Fock matrix exactly in each SCF macroiteration, followed by a few SCF microiterations, where the Fock matrix is incrementally updated using an inexpensive semiempirical approximation. This leads to an improved wave function in each SCF macroiteration with minimal additional cost, and therefore a reduced number of exact Fock builds is required for SCF convergence. The SMH algorithm can be combined with conventional SCF convergence techniques such as level shifting, direct inversion in the iterative subspace (DIIS), and energy-DIIS (EDIIS). When integrated with DIIS, SMH enhances the convergence of simple organic molecules by approximately 10% compared to plain DIIS, with speedups of up to 60% for the more challenging transition metal systems compared to EDIIS + DIIS. Our results show that SMH is a reliable SCF accelerator that seldom deteriorates convergence and is highly robust.

Self-Adaptive Layering Structure of Nanoconfined Fe-Ni Liquids: Origin of the Liquid-Liquid Phase Transition.

Metallic liquids under confinement exhibit different properties compared to those of their corresponding bulk phases, such as miscibility, diffusion, and phase transitions. Unfortunately, the challenges in experimentally characterizing Fe-Ni liquids at the nanoscale and the high cost of first-principles simulations hindered the atom-level understanding that is necessary for controlling Fe-Ni liquids. Here, we report a comprehensive molecular dynamics study of the liquid Fe-Ni alloy confined within nanoslits. Driven by the slit size, the confined Fe-Ni liquid experiences the liquid-liquid phase transition (LLPT) that is characterized by layering transitions. Interestingly, during the LLPT, a transition liquid phase appears, separating two layering phases, which is accompanied by abnormal variations in density, potential energy, and pressure perpendicular to the wall. The Voronoi cluster analysis reveals a self-adaptive local structural evolution in confined Fe-Ni liquids during the LLPT. The effect of temperature, pressure, and composition on the LLPT is investigated. Based on the pressure-confinement phase diagram, the LLPT is mainly induced by confinement under high pressure, while under low pressure, the LLPT is mainly pressure-driven. Our research will stimulate more interest in the phase transition under confinement in a metallic system.

Atomic cluster expansion interatomic potential for defects and thermodynamics of Cu–W system

The unique properties exhibited in immiscible metals, such as excellent strength, hardness, and radiation-damage tolerance, have stimulated the interest of many researchers. As a typical immiscible metal system, the Cu–W nano-multilayers combine the plasticity of copper and the strength of tungsten, making it a suitable candidate for applications in aerospace, nuclear fusion engineering, and electronic packaging, etc. To understand the atomistic origin of the defects (e.g., vacancies, free surfaces, grain boundaries, and stacking faults and thermodynamical properties), we developed an accurate machine learning interatomic potential for Cu–W based on the atomic cluster expansion (ACE) method. The Cu–W ACE potential can faithfully reproduce the fundamental properties of Cu and W predicted by density functional theory (DFT) calculations. Moreover, the thermodynamical properties, such as the melting point, coefficient of thermal expansion, diffusion coefficient, and equation of the state curve of the Cu–W solid solution, are calculated and compared against DFT and experiments. Monte Carlo molecular dynamics simulations performed with the Cu–W ACE potential predict the experimentally observed phase separation and uphill diffusion phenomena. Our findings not only provide an accurate ACE potential for describing the Cu–W immiscible system but also shed light on understanding the atomistic mechanism during the Cu–W nano-multilayers formation process.

Photohole-induced strong σ−π scattering driven by out-of-plane phonons in graphene

A theoretical study of the phonon-induced linewidths of the occupied electronic bands and the electron-phonon coupling (EPC) constant in graphene is presented. We propose an approximation in the spirit of the rigid ion approximation which considerably simplifies calculations of the EPC in metallic systems. We apply a tight-binding approach for the electrons and a force-constant model for the phonons with parameters obtained from . A simple procedure is presented in order to estimate the influence of the graphene-substrate interaction on the phonon dispersion and thereby also on, e.g., the linewidths. The EPC is the strongest in the energy region where π and σ bands overlap. We find that the electron scattering is predominantly driven by the out-of-plane acoustic ZA and optical ZO phonon modes, while in general the high-energy optical phonon modes LO and TO are of secondary importance. Published by the American Physical Society 2024

Study of the surface features of palladium-based alloys using atomic force microscopy and magnetic force microscopy

The surface state of palladium-based alloys, specifically Pd–6.0In–0.5Ru and Pd–7.0Y (the element content is given in wt.%) has been studied using magnetic force microscopy (MFM) and atomic force microscopy (AFM). The study was conducted within the framework of the current trend to enhance the safety of hydrogen separation and storage. The samples for the study were made of high-purity metals through arc alloying. They underwent reversible hydrogen alloying to investigate the impact of internal deformation of metal systems on their structure-sensitive properties. The study demonstrates the characteristics of the sample surface morphology and domain structure before and after hydrogenation. The local magnetic properties of alloy surfaces have been clarified, and their changes as a result of hydrogen exposure have been identified.

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

Modeling analysis framework for metallic currency system

Small coins, large coins, and ingots circulated in parallel in the metallic currency system, and they were sorted by different mechanisms based on the transaction value of each form. This is the first attempt to model their boundaries. We construct a model of the market mechanism of the mint which derives two models to achieve our goal. The first model derived is a supply-demand model of small coins that determines the demarcation between small coins and large coins, and the second is a game model whose equilibrium solution determines the dividing line between large coins and ingots.

Tunable rejuvenation behavior of Zr55Cu35Al10 metallic glass at the atomic scale during recovery annealing and pressure treatment

In this study, molecular dynamics (MD) simulations were employed to investigate atomic structure characteristics of Zr55Cu35Al10 metallic glasses under various annealing temperature and pressure. Following the initial formation of amorphous, the samples annealed at temperatures ranging from 800 K to 1100 K exhibited a transition from an aged state to a rejuvenated state during the subsequent heat treatment stage. In the third stage of heat treatment, increasing the pressure in samples from 0 to 50 GPa significantly enhanced the degree of rejuvenation compared to raising the temperature. Additionally, applying pressure dramatically enhanced the short-range order in the metallic glass system, altered the proportion of icosahedral cluster types, and contributed to a transformation of Voronoi polyhedrons (VPs) from low local five-fold symmetry to high local five-fold symmetry. Notably, the <0,0,12,0> VP, which represents high local five-fold symmetry, reached a peak proportion of 12.5 %, thereby strengthening the amorphous forming ability.

Spin-orbit entanglement driven by the Jahn-Teller effect

Spin-orbit entanglement in 4d and 5d transition metal systems can enhance electronic correlations, leading to nontrivial ground states and the emergence of exotic excitations. There is also an interest to investigate spin-orbit entanglement in 3d compounds, though this is challenging due to their smaller spin-orbit coupling. Here we demonstrate that the Jahn-Teller effect in Mn3+ reduces the energy gap between high- and low- spin-orbital states that lead to enhanced spin-orbit entanglement. Our results show a rare example of synergistic effects of Jahn-Teller and spin-orbit interactions and provide a way to entangle different degrees of freedom in d-metal oxides, which may allow paths to explore the interplay of orbital, lattice and spins in 3d correlated systems.

Ultrafast antiferromagnetic switching of Mn2Au with laser-induced optical torques

Ultrafast manipulation of the Néel vector in metallic antiferromagnets most commonly occurs by generation of spin-orbit (SOT) or spin-transfer (STT) torques. Here, we predict another possibility for antiferromagnetic domain switching by using novel laser optical torques (LOTs). We present results of atomistic spin dynamics simulations from the application of LOTs for all-optical switching of the Néel vector in the antiferromagnet Mn2Au. The driving mechanism takes advantage of the sizeable exchange enhancement, characteristic of antiferromagnetic dynamics, allowing for picosecond 90 and 180-degree precessional toggle switching of the Néel vector with laser fluences on the order of mJ/cm2. A special symmetry of these novel torques greatly minimises the over-shooting effect common to precessional spin switching by SOT and STT methods. We demonstrate the opportunity for LOTs to produce deterministic, non-toggle switching of single antiferromagnetic domains. Lastly, we show that even with sizeable ultrafast heating by laser in metallic systems, there exist a large interval of laser parameters where the LOT-assisted toggle and preferential switchings in magnetic grains have probabilities close to one. The proposed protocol could be used on its own for all-optical control of antiferromagnets for computing or memory storage, or in combination with other switching methods to lower energy barriers and/or to prevent over-shooting of the Néel vector.