Class Of Materials Research Articles

Carborane-based BODIPY dyes: synthesis, structural analysis, photophysics and applications

Icosahedral boron clusters-based BODIPY dyes represent a cutting-edge class of compounds that merge the unique properties of boron clusters with the exceptional fluorescence characteristics of BODIPY dyes. These kinds of molecules have garnered substantial interest due to their potential applications across various fields, mainly including optoelectronics, bioimaging, and potential use as boron carriers for Boron Neutron Capture Therapy (BNCT). Carborane clusters are known for their exceptional stability, rigid geometry, and 3D-aromaticity, while BODIPY dyes are renowned for their strong absorption, high fluorescence quantum yields, and photostability. The integration of carborane into BODIPY structures leverages the stability and versatility of carboranes while enhancing the photophysical properties of BODIPY-based fluorophores. This review explores the synthesis and structural diversity of boron clusters-based BODIPY dyes, highlighting how carborane incorporation can lead to significant changes in the electronic and optical properties of the dyes. We discuss the enhanced photophysical characteristics, such as red-shifted absorption and emission poperties, charge and electronic transfer effects, and improved cellular uptake, resulting from carborane substitution. The review also delves into the diverse applications of these compounds. In bioimaging, carborane-BODIPY dyes offer superior fluorescence properties and cellular internalization, making them ideal for cell tracking. In photodynamic therapy, (PDT) these dyes can act as potent photosensitizers capable of generating reactive oxygen species (ROS) for targeted cancer treatment making them excellent candidates for PDT. Additionally, their unique electronic properties make them suitable candidates for optoelectronic applications, including organic light-emitting diodes (OLEDs) and sensors. Overall, carborane-BODIPY dyes represent a versatile and promising class of materials with significant potential for innovation in scientific and technological applications. This review aims to provide a comprehensive overview of the current state of research on carborane-BODIPY dyes, highlighting their synthesis, properties, and broad application spectrum.

Programmable viscosity metamaterials: Designing fluid properties using temporal superposition of shear and acoustics

Metamaterials are composite structures whose extraordinary properties arise from a mesoscale organization of their constituents. Here, we introduce a different material class—viscosity metafluids. Specifically, we demonstrate that we can rapidly drive large viscosity oscillations in shear-thickened fluids using acoustic perturbations with kHz to MHz frequencies. Because the timescale for these oscillations can be orders of magnitude smaller than the timescales associated with the global material flow, we can construct metafluids whose resulting time-averaged viscosity is a composite of the thickened, high-viscosity and dethickened, low-viscosity states. We show that viscosity metafluids can be used to engineer a variety of unique properties including zero, infinite, and negative viscosities. The high degree of control over the resulting viscosity, the ease with which they can be accessed, and the variety of exotic properties achievable make viscosity metafluids attractive for uses in technologies ranging from coatings to cloaking to 3D printing. Published by the American Physical Society 2024

Mechanical Properties Optimization and Microstructure Analysis of Pure Copper Heterostructured Laminates via Rolling

Heterogeneous metallic structures constitute a novel class of materials with excellent mechanical properties. However, the existing process for obtaining heterostructures from a single material does not meet large-scale industrial requirements. In this study, a pure copper heterostructured laminate (HSL) composed of a surface elongated-grain layer and a central equiaxed-grain layer was fabricated by rolling bonding and annealing. To study the effect of the interface on the mechanical properties of gradient-structured materials, both laminate metal composite (LMC) and non-composite laminate (NCL) were fabricated by cold-rolling pretreatment of the center layer (60% reduction) and cold-rolling bonding of the whole blank (67% reduction). Then, the HSL was obtained by controlling the post-annealing regimes, the microstructure of each layer was optimized, and a larger degree of microstructural heterogeneities, such as grain size, misorientation angle, and grain orientation, was obtained, which resulted in obvious mechanical differences. Tensile tests of the HSL, surface layer, center layer, and NCL specimens revealed that the HSL annealed at 300 °C for 1 h had a significantly higher strength than the center layer and a higher elongation than the surface layer. The HSL had a tensile strength and elongation at fracture of 278.08 MPa and 46.2%, respectively, indicating a good balance of strength and plasticity. The improved properties were primarily attributed to the strengthening or strain hardening due to the inhomogeneous deformation of the heterogeneous layers in the laminate and the mutual constraint acquired by the distinct layers with strong mechanical differences. The HSL had an interfacial bonding strength of 178.5 MPa, which played a vital role in the coordinated deformation of the heterogeneous layers. This study proposes an HSL design method that effectively simplifies the process of obtaining heterostructures in homogeneous materials by controlling the cumulative deformation of the surface and center layers.

Optimization of Dynamic Characteristics of Rubber-Based SMA Composite Dampers Using Multi-Body Dynamics and Response Surface Methodology

The suspension system of a commercial vehicle cab plays a crucial role in enhancing ride comfort by mitigating vibrations. However, conventional rubber suspension systems have relatively fixed stiffness and damping properties, rendering them inflexible to load variations and resulting in suboptimal ride comfort under extreme road conditions. Shape memory alloys (SMAs) represent an innovative class of intelligent materials characterized by superelasticity, shape memory effects, and high damping properties. Recent advancements in materials science and engineering technology have focused on rubber-based SMA composite dampers due to their adjustable stiffness and damping through temperature or strain rate. This paper investigates how various structural parameters affect the stiffness and damping characteristics of sleeve-type rubber-based SMA composite vibration dampers. We developed a six-degree-of-freedom vibration differential equation and an Adams multi-body dynamics model for the rubber-based SMA suspension system in commercial vehicle cabins. We validated the model’s reliability through theoretical analysis and simulation comparisons. To achieve a 45% increase in stiffness and a 64.5% increase in damping, we optimized the suspension system’s z-axis stiffness and damping parameters under different operating conditions. This optimization aimed to minimize the z-axis vibration acceleration at the driver’s seat. We employed response surface methodology to design the composite shock absorber structure and then conducted a comparative analysis of the vibration reduction performance of the optimized front and rear suspension systems. This study provides significant theoretical foundations and practical guidelines for enhancing the performance of commercial vehicle cab suspension systems.

A hybrid GRA-PCA-TOPSIS Technique Optimization of EDD Process Parameter on Drilling of AL8011/B4C/aloevera composites

A class of cutting-edge materials called hybrid aluminum metal matrix composites has been produced for applications such as the automobile, aerospace, and electronics industry and where weight and strengths are crucial factors. In the present research work, AA8011 composite reinforced with boron carbide particles and green aloevera has been fabricated using an economical stir casting process. In this 1% to 3% of boron carbide and 1% to 2% aloevera were used to fabricate the three different combinations of composites. The electrical discharge drilling process variables such as discharge current, pulse-on time, pulse-off time, and dielectric fluid pressure are investigated using the tubular copper electrode on drilling of hybrid composites. Performance aspects including drilling rate, roundness error, taper angle, and electrode wear rate have been analyzed, and the effect of process variables with the response surface methodology–central composite experimental design. The process parameters during the drilling of composites were optimized using a novel multi-criteria decision-making technique called the hybrid grey relational analysis–pulse component analysis–technique for order of preference by similarity to ideal solution method in order to maximize the drilling rate while concurrently minimizing other aspects. The optimum conditions were reached using the hybrid optimization method and a 1.5 mm tubular copper electrode with an input current of 9 Ampere , pulse on time 25 [Formula: see text]s, pulse off time 12 [Formula: see text]s, and pressure 60 kg/cm2. In comparison to the initial settings, the optimal condition shows a 25% faster drilling rate, with a 23% better roundness value, 14% lesser taper angle, and 7% lesser electrode wear rate.

Stable Long-Persistent Luminescence from Self-Activated CaSb2O6 Induced by Intrinsic Defects.

Long-persistent luminescence (LPL) materials have attracted intensive attention due to their fascinating emission after excitation. However, current LPL materials typically depend on external doping to introduce traps or emitting centers, resulting in a complex synthesis and controllability. For the first time, we develop another category of undoped LPL materials based on antimonate CaSb2O6, which exhibits blue LPL for over 8000 s. Both experimental and theoretical evidence indicate that excitons are trapped by intrinsic oxygen vacancies. Then, they are detrapped and recombine through singlet and triplet emission of Sb3+ to form LPL. Moreover, CaSb2O6 maintains approximately 100% of its initial LPL performance and structural integrity even after being treated under 1000 °C, UV irradiation, and extreme conditions (pH = 1 or 13). This study highlights the significant potential of antimonates as robust and versatile luminescent materials.

Rapid Synthesis of Self‐Healing, pH‐Responsive IA‐Based Hydrogels via Frontal Polymerization

ABSTRACTSelf‐healing polymeric gels have emerged as a promising class of materials due to their ability to repair damage autonomously, offering significant advantages for various applications. Nevertheless, a major hurdle to their widespread practical use lies in their often‐compromised mechanical strength and long reaction time. Herein, we present the synthesis of a new type of self‐healing hydrogels using poly(itaconic acid‐co‐hydroxypropyl alcohol‐co‐acrylic acid), also known as poly(IA‐co‐HPA‐co‐AAc), by a frontal polymerization (FP) method. The rapid reaction rate of FP facilitates the swift and energy‐efficient synthesis of the hydrogels within 10 min, eliminating the need for prolonged reaction times. Additionally, the results revealed that the synthesized hydrogels exhibited pH‐dependent responsiveness, robust mechanical integrity, and autonomous self‐healing capabilities, obviating the requirement for external stimuli. The exceptional self‐healing properties can be attributed to the extensive hydrogen bonding network between the polymer chains, enabling them to recover up to 80% of their original mechanical strength. Rheological analysis confirmed the presence of a robust and stable gel network, evidenced by high storage modulus (G′) values across the entire frequency and strain sweep tests. This research addresses a significant knowledge gap in IA‐based hydrogels by introducing a rapid, optimized method for constructing self‐healing materials through hydrogen bonding interactions.

Time domain spectral LiDAR enabled by cascaded Raman in a hydrogen-filled fiber transmitter

We introduce what we believe to be novel spectral light detection and ranging (LiDAR) architectures that enable ultra-compact systems by a transition from spectral signal processing in space (gratings) to processing in time. The architectures leverage temporal dispersion and the unique spectro-temporal waveforms produced from the cascaded Raman scattering generated in the (H2) filled hollow core fiber. The characterized Raman source yields as many as six Raman orders from 1.06-1.70 μm; their unique spectro-temporal waveforms are measured. System performance simulations based on measured Raman waveforms show that high accuracy measurement of range and reflectivity are possible with proper selection of signal-to-noise ratio and detector bandwidth. Materials classification analysis based on the system performance analysis shows that near-optimal classification is feasible with time domain processing.

Poly(arylene ether)s via Cu(II)-Catalysis.

Poly(arylene ether)s (PAEs) are a versatile class of thermoplastic materials with commercial importance. Currently their synthesis relies predominantly on either nucleophilic or electrophilic aromatic substitution reactions, severely limiting the scope of available PAEs. Herein, we report the copper(II)-catalyzed polycondensation of electronically unactivated aryl bromides with bisphenols to afford a wide range of new PAEs. These PAEs are characterized by their thermal and mechanical properties. Functional PAEs were produced that have reversible acid- and redox-triggered chromophores incorporated into the backbone, which illustrates the utility of these methods.

On-Off Switching of Singlet Self-Trapped Exciton Emission Endows Antimony-Doped Indium Halides with Excitation-Wavelength-Dependent Luminescence.

Excitation-wavelength-dependent (Ex-De) emitters are a fascinating category of luminescent materials whose emission properties vary with the wavelength of the light used for excitation. Antimony (Sb3+)-doped indium (In)-based metal halides are efficient light emitters; however, the peak fluorescence emission of most Sb3+-activated In-halide remains independent of the excitation wavelength. Here, the study introduces a new Sb3+-doped In-halide cluster, (BDPA)2InCl5:Sb (BDPA+ = C15H18N+, benzyldimethylphenylammonium), which demonstrates efficient Ex-De emission originating from the on-off switchable fluorescence behavior of singlet self-trapped exciton (STE) in 5-coordinate Sb3+ dopant. Interestingly, when excited within the range of 240-370nm, photoluminescence (PL) spectra of (BDPA)2InCl5:Sb show both singlet and triplet STE emission. However, under excitation wavelengths of 370 to 420nm, the singlet STE emission is absent, resulting in a noticeable correlated color temperature change from 1700 to 3800 K. The study provides a new approach to designing color-tunable Sb3+-based luminophores, and also presents a novel application scenario for the widely recognized Sb3+ doping strategy.

Why active Willis metamaterials? A controllability and observability perspective

Recently, active Willis metamaterials (AWM) have been the focus of extensive investigations because of their unique electro-elastic coupling characteristics. However, the treatments of this class of materials have been carried out exclusively, in all the available literature, by approaches that do not rely on solid control theory basis. In this paper, the emphasis is placed on revealing very important control features that are inherent to this class of materials because of their Willis coupling characteristics. These features lie in the enhanced controllability and observability properties of the AWM as compared to non-Willis active materials. Such control properties enable the AWM to possess broad sensing and actuation capabilities that can lend this material to be an effective means for monitoring and controlling the behavior of numerous critical applications, such as acoustic cloaking, particularly when integrated with appropriate robust control strategies. A simple example of a piezoelectric-based AWM is presented to demonstrate its effective control capabilities and distinguish this class of materials from conventional materials. In the selected example, the AWM is structured from two dissimilar masses connected by a piezoelectric spring. Lagrange dynamics formulation is utilized to generate the equations governing the Willis coupling, the piezoelectric coupling, and reveal the inherent control features. With this developed controlled-based structure of the AWM, it is shown that the AWM can simultaneously monitor and control both the strain and velocity whereas the conventional active material, which is formed from two similar masses connected by a piezoelectric spring, can only measure and control the strain alone. It is envisioned that the revealed control metrics for the simple one-dimensional AMW example can serve as means for investigating the potential of AMW's of higher dimensionality.

Classification of Gem Materials Using Machine Learning

Classification of Gem Materials Using Machine Learning

Cohesive Living Bacterial Films with Tunable Mechanical Properties from Cell Surface Protein Display.

Engineered living materials (ELMs) constitute a novel class of functional materials that contain living organisms. The mechanical properties of many such systems are dominated by the polymeric matrices used to encapsulate the cellular components of the material, making it hard to tune the mechanical behavior through genetic manipulation. To address this issue, we have developed living materials in which mechanical properties are controlled by the cell-surface display of engineered proteins. Here, we show that engineered Esherichia coli cells outfitted with surface-displayed elastin-like proteins (ELPs, designated E6) grow into soft, cohesive bacterial films with biaxial moduli around 14 kPa. When subjected to bulge-testing, such films yielded at strains of approximately 10%. Introduction of a single cysteine residue near the exposed N-terminus of the ELP (to afford a protein designated CE6) increases the film modulus 3-fold to 44 kPa and eliminates the yielding behavior. When subjected to oscillatory stress, films prepared from E. coli strains bearing CE6 exhibit modest hysteresis and full strain recovery; in E6 films much more significant hysteresis and substantial plastic deformation are observed. CE6 films heal autonomously after damage, with the biaxial modulus fully restored after a few hours. This work establishes an approach to living materials with genetically programmable mechanical properties and a capacity for self-healing. Such materials may find application in biomanufacturing, biosensing, and bioremediation.

Nonlinear incompressible shear wave models in hyperelasticity and viscoelasticity frameworks, with applications to Love waves

General equations describing shear displacements in incompressible hyperelastic materials, holding for an arbitrary form of strain energy density function, are presented and applied to the description of nonlinear Love-type waves propagating on an interface between materials with different mechanical properties. The model is valid for a broad class of hyper-viscoelastic materials. For the Murnaghan constitutive model, shear wave equations contain cubic and quintic differential polynomial terms, including viscoelasticity contributions in terms of dispersion terms that include mixed derivatives uxxt of the material displacement. Full (2+1)-dimensional numerical simulations of waves propagating in the bulk of a two-layered solid are undertaken and analysed with respect to the source position and mechanical properties of the layers. Interfacial nonlinear Love waves and free upper surface shear waves are tracked; it is demonstrated that in the fully nonlinear case, the variable wave speed of interface and surface waves generally satisfies the linear Love wave existence condition c1<v<c2, while tending to the larger material wave speed c1 or c2 for large times.

Unlocking the potential of copper-reinforced fibre metal laminates: The influence of stacking sequences

Fibre-Metal Laminates (FMLs) are a class of advanced hybrid materials consisting of a metal layer and fibre-reinforced polymers that give an excellent combination of mechanical properties. The present study deals with the development and characterization of copper-based FMLs developed through the hand layup method by considering multiple stacking sequences for improved mechanical properties and by incorporating carbon nanotubes. Extensive tensile, flexural, fatigue, and wear tests were carried out on the FMLs. SEM analysis was also done to investigate the fracture. According to the test results, in the Type III stacking sequence where optimum 0.5% CNT content is used, the best overall tensile strength together with good flexibility, fatigue resistance, and wear resistance could be obtained. The Type III stacking sequence exhibited a maximum tensile strength of 117.85 MPa, flexural strength of 168.0 MPa, and fatigue life of 22,00,000 cycles at 50 MPa stress amplitude. Further SEM analysis has shown that enhancement in microstructural integrity actually occurred with the inclusion of CNT, especially in fiber-matrix bonding improvement and reduction of voids. The results obtained in this work indicate the suitable possibility for application in high-performance aerospace and automotive industries of copper-based FMLs. This study highlights optimization issues related to both material composition and stacking sequence toward the attainment of superior mechanical properties in FMLs.

Exploring the Synergistic Potential: A Comprehensive Review of MXene-Based Composite Electrocatalysts

MXenes, a prominent category of 2D materials consisting of transition metal carbides, nitrides, and carbonitrides, have garnered significant interest since the introduction of Ti3C2Tx. This fascination arises from their exceptional attributes like their high special surface area, superb electrical conductivity, and remarkable mechanical strength. These qualities have established MXenes as top materials for electrocatalysis, a critical component of clean energy conversion technologies. Crucially, MXenes serve as the foundation for the next generation of electrocatalysts, aiming at high activity, selectivity, and sustainability.In electrocatalysis, MXene composites enhance the performance of various reactions, such as water splitting and fuel cell operations. When combined with metals, metal oxides, or other conductive materials, MXenes exhibit improved electrical conductivity and catalytic activity. These composites can achieve higher efficiency and selectivity in electrochemical reactions, making them suitable for sustainable energy applications. MXene composites also play an significant role in the development of supercapacitors, which are energy storage devices characterized by rapid charge and discharge capabilities. The high special surface area and excellent conductivity of MXenes increase charge storage and improve energy and power density. When MXene composites are mixed with materials such as polymers or other nanomaterials, they can further optimize these properties, leading to increased performance and longevity. Also in battery technology, MXene composites are used to improve the performance of anodes and cathodes. Their high capacity for ion storage and conduction contributes to higher energy density and faster charge/discharge rates. By combining MXenes with other materials, researchers are able to create advanced battery systems that overcome traditional limitations, resulting in batteries that are more efficient, durable, and capable of delivering higher performance. In this study MXene–Carbon composites, MXene-LDH composites, MXene-Polymer composites, MXene-MOF composites are reviewed and discussed. The versatility of MXenes is further enhanced when they are composited with various other materials. Such compositions allow for tailoring their innate properties, enabling a widespread range of applications. In terms of environmental implications, MXenes and their composites boast excellent reducibility, conductivity, and biocompatibility, making them very appropriate for use in environmental clean-up and protection applications.

Honeycomb Molding - Forming Thermoplastic Sandwich Structures for Interior Applications

Trains play an important role in the sustainable mobility of the future. The changes in the market are reflected in the number of newly approved series by the German Federal Railway Authority (EBA); 226 new designs and redesigns of train cars were approved for use on German rails in 2019. Phenol-formaldehyde resins are used extensively specifically for railcar interiors. However, phenol-formaldehyde resins release carcinogenic vapors during and even after production if not completely sealed. As a result, European production standards and requirements have been increased, making the material less economical and increasingly difficult to enter the market. Further bans aimed at lower formaldehyde release limits are currently being considered by the European Union's Committee for Risk Assessment (RAC) and Committee for Socioeconomic Analysis (SEAC). In order to develop and design alternative materials, it is important to meet the requirements for stiffness, light weight, insulation and sustainability simultaneously. This research aim is therefore to develop a new class of material for interior components with improved stiffness, lower weight, lower CO2 footprint and no health hazards. The approach is to develop advanced composite sandwich panels that retain the ability to be molded into complex structures for interior applications. This is done through a thermoplastic honeycomb core structure that is manufactured directly from sheet material and fiber reinforced organo-sheets as the outer layers. The base matrix for all layers is kept uniform for better recyclability and consists of polycarbonate (PC) with sufficient flame retardant properties to provide an environmentally friendly alternative to existing phenolic resin and aramid epoxy honeycomb solutions while still complying with the security norms.

Novel hybrid coating material with triple distinct healing bond for fat oil and grease deposition control in the sewer system

Hybrid materials with distinct self-healing bonds are a prominent category of materials, demanding in various modern applications. Developing self-healable hybrid materials with desired self-healing properties at ambient conditions is highly desirable and challenging. Herein, we developed a novel zinc (II)–dimethylglyoxime–urethane-complex-based polyurethane elastomer (Zn-polyurethane hybrid material) with synergetic triple dynamic bonds, which exhibits spontaneous self-healing properties at 30 °C. Moreover, this material shows excellent thermal stability up to approximately 850 °C and is highly stable in water systems. This hybrid material has potential applications in water systems; in this study, we characterized it for fat, oil and grease (FOG) deposition management in sewer systems by applying it as a coating on concrete blocks. The findings indicate that following a 30-day leaching test conducted under controlled pH conditions on uncoated and Zn-polyurethane-coated concrete blocks, a reduction of over 80 % in calcium release was observed in the coated block compared to the uncoated concrete block. Additionally, in FOG deposit formation tests conducted on uncoated and coated concrete blocks for 30 days, a reduction of over 30 % in FOG deposit formation was noted in the coated sample.

D5 digital circular workflow: five digital steps towards matchmaking for material reuse in construction

The intersection of digital transformation and circular construction practices presents significant potential to mitigate environmental impacts through optimised material reuse. We propose a five-step (D5) digital circular workflow that integrates these digital innovations towards reuse, validated through real-world case studies. We assessed a variety of digital tools for enhancing the reuse of construction materials, including digital product passports, material classification assisted by artificial intelligence (AI), reality capture, computational design, design inspired by generative AI, digital fabrication techniques, extended reality, and blockchain technology. Using action research through a multiple case study approach, we disassembled several buildings that were set for demolition and subsequently designed and executed construction projects using the salvaged materials. Our findings indicate that digital transformation for detection, disassembly, distribution, design, and finally deployment significantly support the application of circular economy principles. We demonstrate the potential of the proposed workflow for industry implementation and scalability.

Deep Learning Accelerated Phase Prediction of Refractory Multi-Principal Element Alloys

The tunability of the mechanical properties of refractory multi-principal-element alloys (RMPEAs) make them attractive for numerous high-temperature applications. It is well-established that the phase stability of RMPEAs control their mechanical properties. In this study, we develop a deep learning framework that is trained on a CALPHAD-derived database that is predictive of RMPEAs phases with high accuracy up to eight phases within the elemental space of Ti, Fe, Al, V, Ni, Nb, and Zr with an accuracy of approximately 90%. We further investigate the causes for the low out of domain performance of the deep learning models in predicting phases of RMPEA with new elemental sets and propose a strategy to mitigate this performance shortfall. While our proposed approach shows marginal improvement in prediction accuracy of RMPEAs with new elemental sets, we should emphasize that overcoming the out-of-domain problem remains largely challenging, particularly in materials science where missing elements or absent material classes in training data hinder predictions, thus slowing the discovery of new potential materials. Predicting phase competition is inherently difficult due to the very small differences in free energies (on the order of meV/atom) that govern competing phases. Current deep learning models, including ours, face significant limitations in capturing these subtle energy differences. Accordingly, more substantial future work is needed to fully address this challenge and achieve robust out-of-domain predictions in complex alloy systems.