Structure Properties Of Materials Research Articles

RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials

RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials

Effect of laser surface treatment on microstructural evolution and mechanical properties of a Co–Cr–Fe–Ni–Mo medium–entropy alloy

In this study, we explored the influence of laser surface treatment on the microstructural evolution and mechanical properties of a Co17.5Cr12.5Fe55Ni10Mo5 medium-entropy alloy. After laser scanning on the cold-rolled alloy, a heterogeneous microstructure with Mo-rich μ-precipitates formed along the depth from the surface. Notably, laser processing parameters, including scanning speed and the number of scans, affected the macroscopic heterogeneity in the microstructure of the alloy, such as the thickness of the columnar, recrystallized, partially-recrystallized, and non-recrystallized layers. Furthermore, the microstructural features of the laser-treated alloys with a heterogeneous distribution of grains, cellular structures, and precipitates, contributed to the mechanical response of the alloys. As the heat input from the laser heat source increases, the grain coarsening and the absence of non-recrystallized layer have a greater impact on the strength of the laser-treated alloys, even if the precipitates distributed deeper from the surface. These microstructural modifications through laser surface treatment are linked to variations in the mechanical performance of the alloys, indicating that it can be an effective method to tailor the mechanical properties of structural materials.

Microscopic Characteristics and Formation of Various Types of Organic Matter in High-Overmature Marine Shale via SEM

Organic matter exhibits significant heterogeneity and complexity, with varying pore structures across different types influenced by multiple interacting factors. This paper introduces a “two categories, six subcategories” classification scheme based on morphological observations using a combination of argon ion polishing and scanning electron microscopy (SEM). Organic matter is classified into two main categories: depositional organic matter and migrated organic matter, based on whether migration has occurred. Depositional organic matter is further subdivided into three types based on microscopic characteristics: bioclasts, compacted kerogen, and in situ remnants from post-hydrocarbon generation. Migrated organic matter is categorized into three types: organic matter in intragranular pores, organic matter in intergranular pores, and bitumen in microfractures. Bioclasts can be further classified into alginite, zooclasts, acritarchs, and encapsulated organic matter based on maceral type. Zooclasts, acritarchs, encapsulated organic matter, and compacted kerogen—types of depositional organic matter—have few or no pores. This is primarily related to the nature of the hydrocarbon-generating precursor materials, with compacted kerogen being influenced by low thermal maturity and diagenetic compaction. In contrast, pores are more developed in alginite, in situ remnants from post-hydrocarbon generation, and all forms of migrated organic matter, largely due to the expulsion of gaseous hydrocarbons during thermal evolution. The pores in alginite reflect both the original structural properties of the hydrocarbon-generating precursor materials and the thermal evolution process. Depositional organic matter exhibits a stronger oil-generating potential and a higher gas-generating potential, while migrated organic matter primarily possesses a stronger gas-generating capability. Specifically, organic matter enriched in alginite, in situ remnants from post-hydrocarbon generation, as well as migrated organic matter in intragranular pore and intergranular pore, exhibit a higher hydrocarbon-generation potential.

Strategies for enhancing molybdenum sorption from aqueous solutions using aluminum-based sorbents

ABSTRACT The removal of molybdenum from water is essential for mitigating the environmental and health impacts of industrial contamination. This study presents a strategy to enhance the sorption capability of molybdenum by introducing functional groups and optimizing structural properties of aluminum-based materials. AlOHCO₃ and LiAl-LDH exhibited high sorption capacities of 260 mg/g and 320 mg/g, respectively, significantly surpassing the capacity of AlOOH (184 mg/g). The improvements are attributed to the incorporation of CO3 2- in both materials and the interlayer structure in LiAl-LDH, confirming the effectiveness of the proposed strategy. The primary sorption mechanisms for AlOOH and AlOHCO₃ involved electrostatic interactions and ion complexation. Additionally, coordination effects were observed for LiAl-LDH. These aluminum-based materials exhibit significant potential for practical applications in water treatment, particularly for addressing molybdenum contamination.

Quantifying Effective Built-in Temperature Difference for Decades- Old Jointed Plain Concrete Pavements in Eastern Washington State

Fifteen Portland cement concrete (PCC) slabs from four Jointed Plain Concrete Pavement (JPCP) sections in the Long-Term Pavement Program (LTPP) located in eastern Washington State were studied in this paper. Dipstick-measured transverse deflection profile along with temperature measurements across slabs’ depths collected during falling weight deflectometer (FWD) testing were used in the study. The youngest section in the study was 24 years old at the time of testing. The objective was to characterize the total effective linear temperature difference (TELTD) and the effective built-in temperature difference (EBITD) in the slabs. EBITD is a temperature differential representing the combined effects of construction built-in, as well as long-term drying shrinkage, and creep equivalent temperature differences. Using ISLAB2000, several iterations were run for each slab to identify the TELTDs that would produce slab curvatures close to those measured in the field. For validation purposes, the found TELTDs were used in Westergaard’s closed-form solution for deflections in the transverse direction. Transverse profiles predicted by ISLAB2000 and Westergaard equations matched well. EBITD, was then obtained by simply subtracting the in-field measured temperature differential from TELTD. Variations of EBITDs were found among the four sections, ranging from +31 to -120 °C (55 to -215 °F). Multiple factors, such as structural features, material properties, construction conditions, and climatic conditions, were identified as influential for the predicted EBITDs.

Structural Regulation and Performance Enhancement of Carbon-Based Supercapacitors: Insights into Electrode Material Engineering.

The development of carbon-based supercapacitors is pivotal for advancing high energy and power density applications. This review provides a comprehensive analysis of structural regulation and performance enhancement strategies in carbon-based supercapacitors, focusing on electrode material engineering. Key areas explored include pore structure optimization, heteroatom doping, intrinsic defect engineering, and surface/interface modifications. These strategies significantly enhance electrochemical performance through increasing surface area, improving conductivity, facilitating charge transfer, introducing additional pseudocapacitive reactions, and optimizing the density of states at the Fermi level, among other mechanisms. After introducing these fundamental concepts, the review details various preparation methods and their effects on supercapacitor performance, highlighting the interplay between material structure and electrochemical properties. Challenges in scaling advanced fabrication techniques and ensuring the long-term stability of functionalized materials are discussed. Additionally, future research directions are proposed, emphasizing the development of cost-effective, scalable methods and interdisciplinary approaches to design next-generation supercapacitors, thereby meeting the growing demand for efficient and sustainable energy storage solutions.

Impact Damage Localization in Composite Structures Using Data-Driven Machine Learning Methods.

Due to the uncertainty of material properties of plate-like structures, many traditional methods are unable to locate the impact source on their surface in real time. It is important to study the impact source-localization problem for plate structures. In this paper, a data-driven machine learning method is proposed to detect impact sources in plate-like structures and its effectiveness is tested on three plate-like structures with different material properties. In order to collect data on the localization of the impact source, four piezoelectric transducers and an oscilloscope were utilized to construct an experimental platform for impulse response testing. Meanwhile, the position of the impact source on the surface of the test plate is generated by manually releasing the steel ball. The eigenvalue of arrival time in the time domain signal is extracted to build data sets for machine learning. This paper uses the Back Propagation (BP) neural network to learn the difference in the arrival time of each sensor and predict the location of the impact source. The results demonstrate that the machine learning method proposed in this paper can predict the location of the impact source in the plate-like structure without relying on the material properties, with high test accuracy and robustness. The research work in this paper can provide experimental methods and testing techniques for locating impact damage in composite material structures.

Impact of Tunnel Fire and High Ground Temperature on the Durability and Thermal Damage Mechanism of Structural Materials

The goal of this paper is to investigate how tunnel fires and high temperatures interact to reduce the structural and thermal properties of tunnelling materials, namely concrete and steel. The work looks at microstructural modifications in concrete (pore expansion, micro-cracking, and the chemical degradation of calcium silicate hydrate (C-S-H) that reduce compressive strength and make concrete porous). Oxidation, surface scaling and yield strength degradation under high temperature are studied in steels to evaluate their negative impact on the capacity to carry loads. The paper also incorporates simulated data on how the insulation material performs over time as a result of repeated high-temperature exposure. Such results emphasise the double-edged structural hazard of fire and geothermal heat, which hastens material decomposition, weakens robustness and undermines long-term stability of critical infrastructure. The paper ends with suggestions for new, thermophilic materials to make tunnels safer in extreme conditions

Effect of Crystallinity on the Printability of Poly(ethylene Terephthalate)/Poly(butylene Terephthalate) Blends.

This study explores the impact of blending polyethylene terephthalate (PET) with polybutylene terephthalate (PBT) on the thermal, structural, and mechanical properties of 3D-printed materials. Comprehensive analyses, including Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and mechanical testing, were conducted to assess the influence of blend composition. FT-IR confirmed that PET and PBT blend physically without transesterification, while TGA showed enhanced thermal stability with increasing PET content. XRD revealed that PET and PBT crystallize separately, with the crystallinity decreasing sharply for blends with more than 50% PET. The DSC results indicated that PET effectively slows down the crystallization kinetics of PBT, promoting cold crystallization. Mechanical tests demonstrated that the elastic modulus remains relatively unchanged, but the strain at break decreases with a higher PET content, indicating increased stiffness and reduced ductility. Overall, incorporating PET into PBT improves 3D-printability and dimensional stability, reducing warpage and enhancing print precision, making these blends advantageous for 3D-printing applications.

Coupled Stacking Faults in Silver Nanorods for CO2 Electroreduction.

The interaction of defects has been proven effective in regulating the mechanical properties of structural materials, while its influence on the physicochemical performance of functional materials has been rarely reported. Herein, we synthesized Ag nanorods with dense stacking faults and investigated how the defect interaction affects the catalytic properties. We found that the stacking faults can couple with each other to form a unique structure of opposite atoms with extortionately high tensile strain. Experimental and theoretical analyses reveal that the opposite-atom structure facilitates the adsorption and activation of CO2 molecules, thus improving the catalytic performance of the carbon dioxide electroreduction reaction (CO2RR). As a result, Ag nanorods achieve high CO partial current density (-11.87 mA cm-2 at -0.8 V vs RHE) and high Faraday efficiency (>95%), superior to most Ag-based catalysts. Our work indicates that the defect interaction is an effective means to boost the performance of functional materials.

Synergistic Effect of Nickel Hydroxide/Hexagonal Boron Nitride Hybrid: An Efficient Electrocatalyst for Detecting 5-Fluorouracil in Human Blood Serum.

5-Fluorouracil (5-Fu) is the third-most often used chemotherapeutic medication and has been scientifically demonstrated to be effective in treating solid tumors, including colorectal, stomach, cutaneous, and breast cancers. When used in excess, it accumulates toxic metabolites, which can have deadly and very harmful effects on people, including neurotoxicity and the induction of morbidity. Therefore, sensitive and rapid analytical techniques for detecting 5-Fu in human blood serum are needed to enhance chemotherapy and forecast the possible adverse effects of 5-Fu residues in the human body. In this report, we developed a simple preparation of three-dimensional/two-dimensional (3D/2D) Nickel hydroxide/hexagonal boron nitride modified with a glassy carbon electrode [Ni(OH)2/h-BN/GCE] for effective electrochemical detection of the 5-fluorouracil with high selectivity. The X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), high-resolution scanning electron microscopy (HR-SEM), and HR-Transmission electron microscopy (HR-TEM) were used to characterize the crystalline, structural, and chemical properties of the as-synthesized materials. Moreover, the cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), differential pulse voltammetry (DPV), square wave voltammetry (SWV), and i-t curves examined the electrode's electrochemical properties and sensor applications. Therefore, under ideal circumstances, Ni(OH)2/h-BN/GCE demonstrated outstanding 5-Fu selectivity, durability, a low LOD (0.001 μM), and a good linear range (0.02-12 μM). Finally, excellent results were obtained while testing this sensor for 5-Fu sensing in human blood serum.

Exploring the diffusion of DNA strands into nanoporous structures for establishing a universal electrochemical biosensor.

The development of universal electrochemical sensing platforms with high sensitivity and specificity is of great significance for advancing practical disease diagnostic methods and devices. Exploring the structural properties of electrode materials and their interaction with biomolecules is essential to developing novel and distinctive analytical approaches. Here, we innovatively investigated the effect of DNA length and configuration on DNA molecule transfer into the nanostructure of a nanoporous gold (NPG) electrode. The NPG electrode can not only distinguish and quantify short DNA strands but can also prevent the diffusion of long DNA, thereby minimizing or eliminating background interference. Leveraging these findings, we developed a universal DNA-based NPG electrochemical biosensing platform for the detection of different types of biomolecules. As a proof-of-concept, this sensing platform was integrated with nuclease-assisted target-recycling recognition and amplification reactions to achieve sensitive and specific detection of single-stranded DNA, microRNA-21, and carcino-embryonic antigen, with detection limits of 4.09, 27.4, and 0.28 fM, respectively. The demonstrated universality, sensitivity, specificity, and capability for analyzing complex samples ensure a comprehensive and robust detection approach for nucleic acid-based molecular diagnosis.

Effects of high-temperature annealing on structural and mechanical properties of amorphous carbon materials investigated by molecular dynamics simulations

Effects of high-temperature annealing on structural and mechanical properties of amorphous carbon materials investigated by molecular dynamics simulations

DFT + U study of structural, electronic, optical and magnetic properties of LiFePO4 Cathode materials for Lithium-Ion batteries

Abstract In this study, we have investigated the structural, electronic, optical, and magnetic properties of LiFePO4 (LFP), which is a prominent cathode material for lithium-ion batteries (LIBs). In order to analyse the properties of LFP, we have carried out the calculations using Density Functional Theory (DFT) combined with the Hubbard (U) correction (i.e., DFT + U), as implemented in the quantum-espresso (QE) code. We performed the structural optimization and found that LFP has a stable olivine structure with equilibrium parameters of a = 4.64 Å, b = 5.98 Å, and c = 10.34 Å. It is shown that LFP has a direct band gap value of 3.82 eV, which is very close to experiment values of 3.6-4.0 eV. The projected density of states (PDOS) of the LFP closely matches with experimental reports of the electronic structure of the material, where the Fe 3d states form tight bands above the O 2p band. The analysis of optical properties shows a significant absorption property in the visible spectrum, reflecting its additional potential for photoactive application. We have also examined the magnetic properties, which reveal that LFP exhibits antiferromagnetic ordering, which plays a critical role in the stability of the material during lithium cycling. The investigated properties of LFP in this work, thus, highlight its viability as an effective cathode material for the next-generation battery technologies with a multifaced applications.

ETL Engineering in Lead-Free New Ca3PBr3 Perovskite Type Structure of Anti- Perovskite Derivative Material for Stable and Effective Photovoltaic Solar Cells

This study explores the structural, electronic, mechanical, optical, and photovoltaic properties of the Ca₃PBr₃ anti-perovskite derivative material using DFT and SCAPS-1D simulations. Results confirm its high stability through tolerance factor...

3D printed three-dimensional elastic metamaterial with surface resonant units for low-frequency vibration isolation

ABSTRACT This study leverages the high manufacturing freedom of 3D printing technology to design a new type of three-dimensional elastic metamaterial with surface resonant units. This metamaterial uses chiral connecting rods and mass blocks on the surface to generate local resonance effects, achieving omnidirectional vibration isolation effects with both low frequency and wide bandwidth, and also has a certain load-bearing capacity. The mechanisms of local resonance bandgap generation are illustrated from the band structure and vibration modes at the edge frequency of the bandgap. The influence of structural geometric parameters and material properties on the bandgap is systematically investigated via finite element method. The transmission characteristics of the metamaterial are obtained through simulation and experiment, and the bandgap areas achieved from two methodologies match each other well. Through static compression tests, the compressive abilities of metamaterials with different frame thicknesses are studied, providing theoretical guidance and data support for engineering applications of balancing vibration isolation and load-bearing.

Graphitic Carbon Nitride for Photocatalytic Hydrogen Production from Water Splitting: Nano-Morphological Control and Electronic Band Tailoring.

Semiconductor polymeric graphitic carbon nitride (g-C3N4) photocatalysts have garnered significant and rapidly increasing interest in the realm of visible light-driven hydrogen evolution reactions. This interest stems from their straightforward synthesis, ease of functionalization, appealing electronic band structure, high physicochemical and thermal stability, and robust photocatalytic activity. This review starts with the basic principle of photocatalysis and the development history, synthetic strategy, and structural properties of g-C3N4 materials, followed by the rational design and engineering of g-C3N4 from the perspectives of nano-morphological control and electronic band tailoring. Some representative results, including experimental and theoretical calculations, are listed to show the advantages of optimizing the above two characteristics for performance improvement in photocatalytic hydrogen evolution from water splitting. The existing opportunities and challenges of g-C3N4 photocatalysts are outlined to illuminate the developmental trajectory of this field. This paper provides guidance for the preparation of g-C3N4 and to better understand the current state of the art for future research directions.

Theoretical study of magnetoresistance oscillations in semi-parabolic plus semi-inverse squared quantum wells in the presence of intense electromagnetic waves

Abstract Magnetoresistance oscillations in semiconductor quantum wells, with the semi-parabolic plus semi-inverse squared potential, under the influence of intense electromagnetic waves (IEMW), is studied theoretically. Analytical expression for the longitudinal magnetoresistance (LMR) is derived from the quantum kinetic equation for electrons, using the Fröhlich Hamiltonian of the electron-acoustic phonon system. Numerical calculation results show the complex dependence of LMR on the parameters of the external field (electric, magnetic field and temperature) as well as the structure parameters of the confinement potential. In the absence of IEMW, Shubnikov-de Haas (SdH) oscillations appear with amplitudes that decrease with temperature in agreement with previous theoretical and experimental results. In the presence of IEMW, the SdH oscillations appear in beats with amplitudes that increase with the intensity of the IEMW. SdH oscillations under the influence of electromagnetic waves are called microwave-induced magnetoresistance oscillations. The maximum and minimum peaks appear at the positions where the IEMW frequencies are integer and half-integer values of the cyclotron frequency, respectively. In addition, the structural parameters of the quantum well such as the confinement frequency and the geometrical parameters have a significant influence on the LMR as well as the SdH oscillations. When the confinement frequency is small, the two-dimensional electronic system in the quantum well behaves as a bulk semiconductor, resulting in the absence of SdH oscillations. In addition, the LMR increases with the geometrical parameter β z of the quantum well. The obtained results provide a solid theoretical foundation for the possibility of controlling SdH oscillations by IEMW as well as the structural properties of materials in future experimental observations.

Advanced Characterization of Solid-State Battery Materials Using Neutron Scattering Techniques.

Advanced batteries require advanced characterization techniques, and neutron scattering is one of the most powerful experimental methods available for studying next-generation battery materials. Neutron scattering offers a non-destructive method to probe the complex structural and chemical processes occurring in batteries during operation in truly in situ/in operando measurements with a high sensitivity to battery-relevant elements such as lithium. Neutrons have energies comparable to the energies of excitations in materials and wavelengths comparable to atomic distances in the solid state, thus giving access to study structural and dynamical properties of materials on an atomic scale. In this review, a broad overview of selected neutron scattering techniques is presented to illustrate how neutron scattering can be used to gain invaluable information of solid-state battery materials, with a focus on in situ/in operando methods. These techniques span multiple decades of length and time scales to uncover the complex processes taking place fundamentally on the atomic scale and to determine how these processes impact the macroscale properties and performance of functional battery systems. This review serves the solid-state battery research community by examining how the unique capabilities of neutron scattering can be applied to answer critical and unresolved questions of materials research in this field. A thorough and broad perspective is provided with numerous practical examples showing these techniques in action for battery research.

Hybrid Materials-Mg3Al-LDH/Ionic Liquids/Chitosan Used in the Recovery Process of Pd Ions from Aqueous Solutions.

The recovery of palladium from aqueous solutions is important due to its critical role in various industrial applications and the growing demand for sustainable resource management. This study investigates the potential of hybrid materials composed of Mg3Al layered double hydroxides (LDHs), chitosan, and ionic liquids (methyl trialchil ammonium chloride) for the efficient adsorption of palladium ions from low-concentration aqueous solutions. Comprehensive characterization techniques, including X-ray diffraction (RX), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), and thermogravimetric analysis (TG), were employed to elucidate the structural and compositional properties of the hybrid materials. The results of the batch adsorption experiments demonstrate that each component contributes synergistically to the adsorption process, significantly enhancing the overall efficacy of palladium recovery. Furthermore, the method of preparing the adsorbent material was found to impact the effectiveness of palladium recovery. Among the materials tested, the chitosan/Mg3Al/IL hybrid exhibited the highest adsorption capacity (qmax = 98 mg/g), suggesting that the ionic liquid functionalization is most beneficial when applied during the hybrid material synthesis, rather than during the LDH synthesis process. This research underscores the viability of hybrid materials as a sustainable approach to palladium recovery, contributing to advancements in environmental remediation technologies.