Material System Research Articles

Ultrasensitive detection of hazardous gas at room temperature enabled by MOF@MXene 0D-2D heterostructure

Achieving high sensitivity in detecting trace concentrations of toxic gases, particularly under room temperature (RT) conditions, remains a significant challenge. Herein, a 0D-2D heterostructure that can detect ppb-level H2S at RT is proposed by self-assembling cobalt-based metal–organic framework (Co-MOF) on Ti3C2Tx MXene. Co-MOFs with high specific surface areas can capture and concentrate target gas molecules, enhancing host-guest interactions and thereby boosting the selectivity and sensitivity. MXene nanosheets with high conductivity enable rapid electron transport at heterointerface, hence efficiently accelerating the reaction kinetics. Thereby, the as-prepared chemiresistive gas sensor based on Co-MOF@MXene 0D–2D heterostructure possessed excellent sensitivity against interfering gases and delivered an excellent response value of 11.1 to 400 ppb H2S at RT. The judicious design of MOF@MXene heterostructure may spur advanced hybrid material systems for superior sensing applications.

Effect of graphene on absorption spectrum of Si/SiO2 multilayer

In recent decades, photonic crystals have emerged as a key technology in several fields, including light management, photovoltaics, detection, and lasing. This success can be attributed to the ability to regulate electromagnetic waves, which can be achieved by, through a variety of techniques, disruption the periodicity of crystals. In this study, the introduction of graphene as a material defect in a one-dimensional photonic crystal consisting of six Si/SiO2 patterns is subjected to investigation. The calculations are performed using the transfer matrix method, with the experimental data serving as the input, following a protocol that involves exploring the variation of the absorption spectra as a function of the parameters of the material system and the incident electromagnetic wave. The findings illustrate that the absorption peak exhibits a pronounced dependency on the positioning of the material defect, the graphene layer thickness, and the incident angle. This paves the way for a more detailed inquiry into its potential utility in the domain of detection.

Coexistence of anomalous Hall effect and weak magnetization in a nominally collinear antiferromagnet MnTe

In various material systems, an antiferromagnetic phase was found to coexist with a weak ferromagneticlike signal, while symmetry-based theoretical predictions indicate a possibility of a nonzero anomalous Hall effect (AHE) even in the absence of sample magnetization. This is the case of nominally collinear antiferromagnets, in particular, hexagonal MnTe, where the AHE and no detectable magnetization have been recently reported. To clarify the role of magnetization, we present a study of bulk MnTe samples, combining experiment and theory. We demonstrate that the existence of the AHE in the hexagonal MnTe is accompanied by the presence of a weak but detectable ferromagneticlike signal, vanishing at the Néel temperature. In contrast to thin layer samples, we find that the AHE hysteresis loop shows an opposite sign and Barkhausen-like jumps. We introduce a macrospin model involving the Dzyaloshinskii–Moriya type interaction, which explains the existence of a nonzero magnetic moment in the absence of external field and reproduces well hysteretic behavior of the AHE. Using analysis of Néel-vector-dependent Berry curvature, we show that the intrinsic AHE in hexagonal MnTe can be nonzero even when the magnetization vanishes and, also, that it changes sign depending on the Fermi energy position. Published by the American Physical Society 2024

Role of Morphology on Zinc Oxide Nanostructures for Efficient Photoelectrochemical Activity and Hydrogen Production.

Energy generation today heavily relies on the field of photocatalysis, with many conventional energy generation strategies now superseded by the conversion of solar energy into chemical or thermal energy for a variety of energy-related applications. Global warming has pointed to the urgent necessity of moving away from non-renewable energy sources, with a resulting emphasis on creating the best photocatalysts for effective solar conversion by investigating a variety of material systems and material combinations. The present study explores the influence of morphological changes on the photoelectrochemical activity of zinc oxide nanostructures by exploiting electrodeposition and capping agents to control the growth rates of different ZnO facets and obtain well-defined nanostructures and orientations. A zinc nitrate (Zn (NO3)2) bath was used to electrodeposit ZnO nanostructures on an indium tin oxide glass (ITO) substrate at 70 °C with an applied potential of -1.0 V. Ethylenediamine (EDA) or ammonium fluoride (NH4F) were added as capping agents to the zinc nitrate bath. Extensive evaluation and characterization of the photoelectrochemical (PEC) capabilities of the resulting morphology-controlled zinc oxide nanostructures confirmed that altering the ZnO morphology can have positive impacts on PEC properties.

Transport in a Two-Channel Nanotransistor Device with Lateral Resonant Tunneling.

We study field effect nanotransistor devices in the Si/SiO2 material system which are based on lateral resonant tunneling between two parallel conduction channels. After introducing a simple piecewise linear potential model, we calculate the quantum transport properties in the R-matrix approach. In the transfer characteristics, we find a narrow resonant tunneling peak around zero control voltage. Such a narrow resonant tunneling peak allows one to switch the drain current with small control voltages, thus opening the way to low-energy applications. In contrast to similar double electron layer tunneling transistors that have been studied previously in III-V material systems with much larger channel lengths, the resonant tunneling peak in the drain current is found to persist at room temperature. We employ the R-matrix method in an effective approximation for planar systems and compare the analytical results with full numerical calculations. This provides a basic understanding of the inner processes pertaining to lateral tunneling transport.

Mutant amplitude modulation behavior of MIS-like structure of few-layer graphene/SiO2/p-Si in 500–750 GHz band

Graphene has great application potential in the field of electromagnetic modulation field because of its excellent physical and electronic properties. Studies have demonstrated that the properties of graphene films with different layers are also different due to the difference in energy band structure. Nowadays, the modulation mechanism of monolayer graphene (MLG) and bilayer graphene (BLG) has been gradually discovered, but for graphene with more than three layers, the mechanism of whether it is tunable remains to be explored, especially on the proving from an experimental perspective. In this study, the CVD-prepared highly homogeneous few-layer graphene (FLG) film was combined with SiO2 nanolayers and P-doped Si substrate to form an MIS-like capacitor structure, a unique electromagnetic behavior of mutant amplitude modulation exhibited by FLG film was found, which was different from that of mono- and bi-layers of graphene. The results show that the structure exhibits obvious modulation behavior in the ultra-wideband frequency of 500–750 GHz and the bias of 0.9 V, up to 3.1 dB. This study makes a new supplement to a gap in the EM modulation system of graphene series material.

Active learning accelerated exploration of single-atom local environments in multimetallic systems for oxygen electrocatalysis

Single-atom catalysts (SACs) with multiple active sites exhibit high activity for a wide range of sluggish reactions, but identifying optimal multimetallic SAC is challenging due to the vast design space. Here, we present a self-driving computational strategy that combines first-principles calculations and equivariant graph neural network (GNN) to explore over 30,000 binary metallic sites with varying combinations of 3d transition metals and different ligand environments for oxygen reduction and evolution reactions (ORR/OER). Active learning facilitates the investigation of the search space by balancing the exploration of unseen atomic structures with the exploitation of the active ones. The GNN learns the chemical environments to capture composition-structure-property relationships for ORR/OER activity and selectivity. The computational predictions of promising Co-Fe, Co-Co, and Co-Zn metal pairs are consistent with the state-of-the-art results of experimental measurements reported in the literature. This approach can be extended to a broader class of multi-element high entropic materials systems.

The development and impact of tin selenide on thermoelectrics.

Thermoelectric technology experienced rapid development over the past 20 years, with the most promising applications being in both power generation and active cooling. Among existing thermoelectrics, tin selenide (SnSe) has had particularly rapid development owing to the unexpectedly high thermoelectric efficiency that has been continuously established over the past decade. Several transport mechanisms and strategies used to interpret and improve the thermoelectric performance of SnSe have been important for understanding and developing other material systems with SnSe-like characteristics. Similar to other thermoelectrics, building commercially viable SnSe-based devices requires advances in device efficiency and service stability. Further optimization across all material systems should enable thermoelectric technology to play a critical role in the future global energy landscape.

Design and performance of a foamed ceramic prepared by sintering using boron carbide as a foaming agent

To meet the requirements of microwave penetration in military applications, the technical potential of preparing foamed ceramics (FCs) with low permittivity and reduced preparation costs by using desalted sea sands as the main raw material and boron carbide (B4C) as a foaming agent was investigated. The results of the orthogonal experiment demonstrate that the FCs prepared from a material system containing 3 wt% B4C, 2 wt% Fe2O3 and 4 wt% Na2CO3 exhibit the optimal overall performance. The performance of the FCs is strongly influenced by the sintering temperature, but less so by the sintering time. The FCs sintered at 1000 °C for 10 min have a high total porosity of 72 %, a high compressive strength of 9.7 MPa due to their homogeneous internal pore structure with small pore diameter, a high closed porosity of 71 % due to their dense smooth surface and intact pore walls, and a low permittivity of (2.09–2.25)+j(0.014–0.019) in the X–band due to their high porosity and simple composition, indicating that they are a promising multifunctional material for microwave penetration.

Influence of Different Filler Systems on the Thermal Conductivity and Mechanical Properties of Thermosets.

The changing demands in terms of the compactness and performance of electronic devices increase the role of thermal management within this application field. Because polymers and especially thermosets have a low thermal conductivity, filler systems have to be used to improve their performance and make thermosets suitable for applications. So far, several factors influencing thermal conductivity have been defined; however, the combined investigation of mechanical properties as another important value in terms of applications has not been realized. Therefore, this paper analyzes thermal conductivity based on the orientation of fillers and a contact path as well as mechanical properties in different material systems. In addition to the matrix material, the filler type and grade and the geometry and size were varied. It was shown that boron nitride provides the best values in terms of thermal conductivity after orientation along the flow path is realized. An aluminum silicate was defined as the best filler system in terms of mechanical properties. However, the boron nitride was found to reveal the greatest potential in terms of applications, since the mechanical properties are likely to be increased by the usage of finishing additives such as silane.

Mechano-adaptive meta-gels through synergistic chemical and physical information-processing

Global functional adaptation after local mechanical stimulation, as in mechanobiology and the mimosa plant, is fascinating and ubiquitous in nature. This is achieved by locally sensing mechanical deformation with precise thresholds, processing this information via biochemical circuits, followed by downstream actuation. The integration of such embodied intelligence allowing for mechano-to-chemo-to-function information-processing remains elusive in man-made systems. By merging the fields of chemical circuits and metamaterials, we introduce adaptive metamaterial hydrogels (meta-gels) that can accurately sense mechanical stimuli (local touch and global strain), transmit this information over long distances via reaction-diffusion signaling, and induce downstream mechanical strengthening by growing nanofibril networks, or soft robotic actuation through competitive swelling. All elements of the sensor-processor-actuator system are embedded in the device, functioning autonomously without external feeding reservoirs. Our concept enables designing advanced life-like materials systems that synergistically combine two worlds – chemical circuits for chemical information-processing and metamaterial unit cells for physical information-processing.

Novel 2D/3D Heterojunction for UV Light‐Emitting Diodes Using Hexagonal Boron Nitride as Hole Injection Layer

The AlGaN materials system has been extensively studied in order to improve the efficiency of UV‐B and UV‐C light‐emitting diodes (LEDs). While progress has been made, significant challenges remain at shorter wavelengths. Most notably, increased Al composition for shorter‐wavelength operation results in increased activation energy of Mg dopants, resulting in low p‐doping. Although p‐doped h‐BN, with a bandgap of 5.9 eV, has been proposed as a potential replacement of p‐doped AlGaN, there have not been demonstrations of LEDs fabricated from p‐doped h‐BN/AlGaN heterostructures. Such unique heterostructures combine 2D p‐doped h‐BN materials with 3D AlGaN materials. Herein, fabrication and characterization of p‐doped h‐BN/AlGaN multiple quantum wells (MQWs)/n‐AlGaN LEDs, demonstrating emission of light at 290 nm corresponding to the AlGaN MQWs, with weaker emission at 262 nm corresponding to the AlGaN barrier, are reported. These results conclusively show hole injection through p‐doped h‐BN into AlGaN and provide a proof of concept that p‐doped h‐BN can be an alternative hole injection layer for UV LEDs.

The Molecular Design and Electroluminescent Performance of Near-Infrared (NIR) Iridium(III) Complexes Bearing Isoquinoline-, Phthalazine- and Phenazine-Based Ligands.

Near-infrared (NIR) light has characteristics of invisibility to human eyes, less background interference, low light scattering, and strong cell penetration. Therefore, NIR luminescent materials have significant applications in imaging, sensing, energy, information storage and display. The development of NIR luminescent materials thus has emerged as a highly dynamic area of research in the realm of contemporary materials. To date, NIR luminescent materials are roughly divided into inorganic materials and organic materials. Compared with inorganic materials, organic NIR luminescent materials have become a hot research topic in recent years due to their rich sources, easy control of structure, simple preparation process, low cost, and good film-forming properties. Among them, iridium(III) [Ir(III)] complexes exhibit excellent properties such as thermal stability, simple synthesis, easy color modulation, short excited state lifetimes, and high brightness, thus becoming one of the ideal luminescent material systems for preparing high-quality organic light-emitting diodes. Therefore, how to obtain Ir(III) complexes with NIR emission and high efficiency through molecular design is a necessary and promising research topic. This work reviews the research progress of representative NIR Ir(III) complexes bearing isoquinoline-, phenazine-, and phthalazine-based ligands reported in recent years and introduces the design strategies and electroluminescent performances of NIR Ir(III) complexes.

Electrostatics in Materials Revisited: The Case of Free Charges Combined with Linear, Homogeneous, and Isotropic Dielectrics

Here we revisit the electrostatics of material systems comprising of free charges and linear, homogeneous, and isotropic (LHI) dielectrics. We focus on D(r) suggesting that this is the primary vector field of electrostatics. We show that D(r) is sufficient to conceptually describe all underlying physics and to mathematically accomplish all necessary calculations, beforehand, independently of the secondary vector fields P(r) and E(r) that, if needed, can be easily calculated from D(r). To this effect, we introduce a P-D electric susceptibility, χε, with , that couples linearly P(r) with D(r) (instead of the standard P-E electric susceptibility, χe, with , that couples linearly P(r) with E(r)). This concept restores the somehow misleading causality/feedback between P(r) and E(r) of the standard formulation, captures efficiently the underlying physics, enables electrostatics to obtain a form analogous to that of magnetostatics, and facilitates analytical/computational calculations in relevant systems. To document these claims, we provide technical means, among others, the free scalar potential, , and clarify the conditions that enable the calculation of D(r) on a standalone basis, directly from the free charge density, , and the electric susceptibility, χε, of the LHI dielectrics. Our concept sets interesting perspectives for the treatment of all dielectrics.

Fuel-Driven Dynamic Combinatorial Peptide Libraries.

Dynamic combinatorial chemistry (DCC) creates libraries of molecules that are constantly interchanging in a dynamic combinatorial library. When a library member self-assembles, it can displace the equilibria, leading to emergent phenomena like its selection or even its replication. However, such dynamic combinatorial libraries typically operate in or close to equilibrium. This work introduces a new dynamic combinatorial chemistry fueled by a catalytic reaction cycle that forms transient, out-of-equilibrium peptide-based macrocycles. The products in this library exist out of equilibrium at the expense of fuel and are thus regulated by kinetics and thermodynamics. By creating a chemically fueled dynamic combinatorial library with the vast structural space of amino acids, we explored the liquid-liquid phase separation behavior of the library members. The study advances DCCs by showing that peptide structures can be engineered to control the dynamic library's behavior. The work paves the way for creating novel, tunable material systems that exhibit emergent behavior reminiscent of biological systems. These findings have implications for the development of new materials and for understanding life's chemistry.

Synthesis and electrochemical performance of novel high-entropy spinel oxide (FeCoMgCrLi)3O4

High-entropy oxides (HEOs) are attractive options for anode materials in lithium-ion batteries (LIBs) because of their impressive specific capacity and structural stability. The multi-element composition of HEOs endows them with diverse physicochemical properties. However, the role of different elements in the energy storage mechanism remains unclear, and the limited number of successfully synthesized high-entropy oxide systems currently hinders further development. Therefore, developing HEOs with different compositions and studying their electrochemical properties is of great significance. Using the glycine-nitrate solution combustion synthesis (SCS) method, we produced two new High Entropy Oxides (HEOs), namely (FeCoMgCr)3O4 and (FeCoMgCrLi)3O4, and assessed their electrochemical performance as LIBs anode materials. The studies indicate that the inclusion of lithium significantly enhances the lithium storing capabilities of the material system. Specifically, after undergoing two hundred cycles at a current density of 200 mA/g, (FeCoMgCrLi)3O4 exhibited a specific capacity of 658 mAh/g, which was considerably greater than the specific capacity of (FeCoMgCr)3O4, which was 306.9 mAh/g. This work enriches the spinel-type high-entropy oxide systems and proposes a new design strategy for HEOs as LIBs anode materials.

High Mechanical Performance of Lattice Structures Fabricated by Additive Manufacturing

Lattice structures show advantages in mechanical properties and energy absorption efficiency owing to their lightweight, high strength and adjustable geometry. This article reviews lattice structure classification, design and applications, especially those based on additive manufacturing (AM) technology. This article first introduces the basic concepts and classification of lattice structures, including the classification based on topological shapes, such as strut, surface, shell, hollow-strut, and so on, and the classification based on the deformation mechanism. Then, the design methods of lattice structure are analyzed in detail, including the design based on basic unit, mathematical algorithm and gradient structure. Next, the effects of different lattice elements, relative density, material system, load direction and fabrication methods on the mechanical performance of AM-produced lattice structures are discussed. Finally, the advantages of lattice structures in energy absorption performance are summarized, aiming at providing theoretical guidance for further optimizing and expanding the engineering application potential of lattices.

Development of Peptide Identification System for ToF-SIMS Spectra Using Supervised Machine Learning.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) data interpretation for organic materials is complicated because of various fragment ions produced from each molecule and the overlapping of certain mass peaks from different molecules. Fragmentation mechanisms in SIMS are complex because different sputtering and ionization processes can simultaneously occur. Therefore, a prediction system that can identify materials in a sample is required. A novel prediction system for peptides based on ToF-SIMS and amino-acid-based teaching information (labels) for supervised machine learning was developed. To develop the prediction system for general organic materials, the annotation of materials is crucial to creating effective labels for supervised learning. Peptides are composed of 20 amino acid residues, which can be used as labels. We previously developed a peptide prediction system using Random Forest, a supervised machine-learning method. However, only the amino acids contained in the target peptide were predicted, and the amino acid sequence was unable to be assumed. In this study, the amino acid sequence of the test peptide was determined by adding the information on two adjacent amino acids to the labels. Once the prediction system learned the target peptide spectra, the peptides in the newly obtained ToF-SIMS spectra could be identified. The new prediction system also provides useful information for the identification of unknown peptides. The prediction results indicate that two adjacent permutations of amino acids are effective pieces of teaching information for expressing the amino acid sequence of a peptide.

Root causes analysis for improved containment integrity in LPG storage: A case study

AbstractA liquefied petroleum gas (LPG) storage system is a critical component designed for the storage of liquefied petroleum gas. LPG storage systems for hazardous materials require rigorous safety protocols to prevent catastrophic containment losses. However, complex interactions between equipment failure, human factors, and external events make prevention a persistent challenge. This study demonstrates the application of structured methods to systematically analyze, correct, and prevent loss of containment in LPG systems. In order to realize this, 8D methodology was used to analyze and solve the problem which included fault tree analysis (FTA) to identify the root causes. Additionally, the bow tie analysis (BTA) will be integrated into the analysis process to implement permanent mitigative actions and prevent the recurrence of similar issues in the future. As a result of this work, it was determined that by applying the proposed approach, the risk of undesired consequences was reduced compared to baseline levels. This study demonstrated the value of a structured suggested approach to improve containment integrity in high‐risk storage systems.

Comparative analysis of thermoelectric properties in bulk 2H and monolayer MoS2: a first-principles study at high temperatures

The pursuit of high-efficiency heat-to-electricity conversion is one of the indispensable driving forces toward future renewable energy production. The two-dimensional (2D) transition metal dichalcogenide, such as molybdenum disulfide (MoS2), is at the forefront of research due to its outstanding heat propagation features and potential applications as a thermoelectric material. Using the first-principles density functional theory coupled with the semi-classical Boltzmann transport equation within the constant relaxation time approximation, we present the thermoelectric and energy transport in the bulk 2H and monolayer MoS2 material system. In order to advance the underlying physics, we calculate several crucial transport parameters such as electrical conductivity, electronic thermal conductivity, Seebeck coefficient, and power factor as a function of the reduced chemical potential for different doping types and temperatures, in addition to the electron energy dispersion relation of the material system. Our comprehensive study employs the Shankland interpolation algorithm and the rigid band approximation to attain a high degree of accuracy. This thorough investigation reveals the high Seebeck coefficient of 1534 and 1550 μ V/K at 500 K for the bulk 2H and monolayer MoS2, respectively. Furthermore, the ultrahigh power factor values of 9.21 × 1011 and 3.69 × 1011 Wm −1 K −2 s −1 are shown at 800 K in the bulk 2H and monolayer MoS2, respectively. Based on the power factor results, our in-depth analysis demonstrates that the bulk 2H MoS2, when compared to monolayer MoS2, exhibits great potential as a promising semiconducting thermoelectric material for advanced high-performance energy device applications.