Materials Science Research Articles

Numerical Optimization of Functionally Graded Ti-HAP Material for Tibial Bone Fixation System

Functionally graded materials (FGMs) are heterogeneous composites characterized by outstanding properties. They are built from two or more components with a gradient distribution of chemical composition along a given direction. A promising graded material for biomedical engineering as an implant could be a FGM made of titanium (Ti) and hydroxyapatite (HAP). It would allow us to counteract the difference between the stiffness modulus of pure titanium and bone tissue. Moreover, it can be a good solution to the problem of stress shielding for bone fixation plates made of conventional titanium or steel. The presented paper aims to perform micromechanical modeling and optimization of a functionally Ti-HAP graded plate, followed by numerical analysis of a fractured tibia stabilization system under specific boundary conditions. Finite element analysis was performed using ANSYS Workbench 2021 software. The models of the FGM plate and tibial fixation system were made using the Space Claim tool. The ANSYS software allowed the optimization of the model considered and the selection of the appropriate structural parameters of the FGM Ti-HAP material. In general, the results proved that the osteosynthesis plate built of graded Ti-HAP material resulted in lower bone stress compared to titanium and steel plates. The results obtained confirmed the validity of the design and the possibility to use functionally graded Ti-HAP bone fixation plates.

Analytical modeling and computational optimization for a 1-DOF compliant mechanism

The first natural frequency directly affects the operational conditions of compliant mechanisms in precision engineering systems. To address this challenge, a computational method based on the surface response method is proposed to optimize the frequency of a new one degree of freedom (DOF) compliant mechanism. Initially, a 1-DOF 3D model of a compliant mechanism is built. The dynamic equation and the frequency response are formulated via equivalent stiffness and the Lagrange method. Subsequently, a series of numerical simulations are conducted to find the fundamental frequency of the mechanism. The initial dimensions of the flexible joints are determined, and the initial frequency is analyzed by using finite element analysis. Next, the flexible joints in the designed mechanism are optimized by a variant of the genetic algorithm. The optimized dimensions of the mechanism are found with the thickness of the circular joint of 1.10 mm, the thickness of the leaf joint of 1.19 mm, and the length of the leaf joint of 54.50 mm. The optimized result showed that there is a significant improvement in the frequency of the mechanism, increasing from an initial design of 53.218 Hz to an optimal design of 75.927 Hz with an improvement of 42.6%. This study provides important reference materials for future research on compliant mechanisms.

Dual‐Modal Sensing Skin Adaptive to Daylight, Darkness, and Ultraviolet Light for Simultaneous Full‐Field Deformation Measurement and Mechanoluminescence Responses

AbstractMechanoluminescence (ML) and digital image correlation (DIC) have emerged as promising optical methods to visualize and measure deformation fields. In this study, a dual‐modal sensing skin, called the ML‐DIC skin is introduced, that is capable of emitting ML and facilitating DIC measurements under various lighting conditions, including daylight, night or darkness, and UV irradiation. Four ML‐DIC skins are fabricated with or without carbon nanotubes (CNTs) using a composite powder consisting of SrAl2O4: Eu,Dy (SAO), and acrylic resin, with CNT milling times of 48, 72, and 96 h for three of four skins, respectively. DIC measurements are performed under multiple lighting conditions for measuring photoluminescence, persistence luminescence, and reflection. Uniaxial tension tests demonstrate the superior performance of ML‐DIC skins with CNTs compared with pristine SAO skins, with the skin subjected to 48 h of CNT dispersion exhibiting optimal performance. Further investigations focus on ML emission and DIC measurements near the crack‐tip vicinity of static and propagating cracks as well as on surfaces above subsurface cracks. The integration of ML and DIC techniques offers a versatile approach for comprehensive deformation analysis applicable to diverse environments, with implications for materials science, engineering, and structural health monitoring.

Antagonistic-contracting high-power photo-oscillators for multifunctional actuations.

High-power autonomous soft actuators are in high demand yet face challenges related to tethered power and dedicated control. Light-driven oscillation by stimuli-responsive polymers allows for remote energy input and control autonomy, but generating high output power density is a daunting challenge requiring an advanced material design principle. Here, inspired by the flight muscle structure of insects, we develop a self-oscillator based on two antagonistically contracting photo-active layers sandwiching an inactive layer. The actuator produces an output power density of 33 W kg-1, 275-fold higher than other configurations and comparable to that of insects. Such oscillators allow for broad-wavelength operation and multifunction integration, including proprioceptive actuation and energy harvesting. We demonstrate high-performance flapping motion enabling various locomotion modes, including a wing with a thrust-to-weight ratio of 0.32. This work advances autonomous, sustained and untethered actuators for powerful robotics.

Green Synthesis and Enhanced Photocatalytic Performance of rGO/ZnO/Fe3O4 Nanocomposites: A Sustainable Approach to Environmental Remediation.

The fast industrialization and mounting pollution have necessitated the need for advanced materials in order to degrade pollutants efficiently. Metal oxide-based and graphene-derivative photocatalytic nanocomposites are excellent for harnessing light energy in environmental remediation. Among them, ZnO-based nanocomposites have drawn considerable attention because of their high photocatalytic activity and stability. However, improving the performance of these nanocomposites is still necessary for their wide applications. This study explores the green synthesis, detailed characterization, and enhanced photocatalytic efficiency of reduced graphene oxide rGO/ZnO/Fe3O4 nanocomposites. The nanocomposites were synthesized via a hydrothermal method, utilizing milk thistle extract as a natural reducing agent, representing a novel and sustainable approach to fabricating magnetic rGO/Fe3O4 nanocomposites. These composites were further integrated with zinc oxide to produce a multifunctional material, exhibiting high surface area, superior electrical and thermal conductivity, and robust mechanical strength. The photocatalytic performance was significantly enhanced due to the synergistic interaction between graphene and metal oxide nanoparticles, leading to efficient degradation of environmental pollutants. Electrochemical analysis via cyclic voltammetry revealed distinctive redox peaks, demonstrating efficient electron transfer processes essential for applications in energy conversion and storage. This green synthesis not only provides a sustainable pathway for the development of advanced nanocomposites but also underscores their potential in a wide range of applications, including environmental remediation, sensing, energy storage, and optoelectronics.

Integrating an antimicrobial nanocomposite to bioactive electrospun fibers for improved wound dressing materials

This study investigates the fabrication and characterization of electrospun poly (ε-caprolactone)/poly (vinyl pyrrolidone) (PCL/PVP) fibers integrated with a nanocomposite of chitosan, silver nanocrystals, and graphene oxide (ChAgG), aimed at developing advanced wound dressing materials. The ChAgG nanocomposite, recognized for its antimicrobial and biocompatible properties, was incorporated into PCL/PVP fibers through electrospinning techniques. We assessed the resultant fibers’ morphological, physicochemical, and mechanical properties, which exhibited significant enhancements in mechanical strength and demonstrated effective antimicrobial activity against common bacterial pathogens. The findings suggest that the PCL/PVP-ChAgG fibers maintain biocompatibility and facilitate controlled therapeutic delivery, positioning them as a promising solution for managing chronic and burn-related wounds. This study underscores the potential of these advanced materials to improve healing outcomes cost-effectively, particularly in settings plagued by high incidences of burn injuries. Further clinical investigations are recommended to explore these innovative fibers’ full potential and real-world applicability.

Photothermally‐Induced Reversible Rigidity of Nacre‐Mimetic Composites Toward Semi‐Active Personal Safeguard

AbstractThe capacity to withstand challenges posed by complex environments is crucial for developing advanced high‐performance protective materials with mechanically adjustable nature. By constructing long‐range hierarchical network of shear‐stiffening gel‐carbon nanotube‐cellulose nanofiber (SCC) embedded within epoxy resin (ER), this work engineers a nacre‐inspired variable‐stiffness SCC‐ER composite (SCCE). Lightweight SCC scaffold attenuates falling impact force from 2.23 to 0.46 kN, and reaches 60 °C within 20 s under 1 sun exposure. Additionally, owing to the rigid ER matrix, SCCE exhibits 4.03 GPa elastic modulus, outperforming numerous conventional engineering materials in puncture resistance. Specific energy absorption of nacre‐mimetic SCCE presents 1.91 MJ m−3 while that of random structural SCCE is only 0.50 MJ m−3. More importantly, SCCE features representative photothermal‐induced reversible rigidity whose storage modulus varies from 9.85 MPa at 30 °C to 11.61 kPa at 116 °C under light stimulation. It also presents shape‐programmability, capable of adhering complex structural surfaces for protection. Eventually, SCCE‐based semi‐active adjustable protectors are constructed that leverage contactless photothermal effect to modulate rigidity. 5 mm‐thick smart SCCE‐protectors resist 163.93 m s−1 ballistic impact while 15‐mm commercial kneepads are penetrated at lower speed of 136.98 m s−1. This bio‐inspired semi‐active strategy proposes a promising avenue for enhancing personal protective equipment.

Exploring European Parents’ Attitudes Towards the Age Appropriateness of Digital Sexuality Education for Adolescents

We conducted a multinational cross-sectional survey in Europe to explore parental attitudes toward the appropriate age for adolescents to receive sexuality education through an app interface. This was delivered via an online survey across Belgium (n = 479), the United Kingdom (n = 445), and Italy (n = 454). Parents from Belgium consistently accepted their children accessing digital material at the youngest ages, whereas Italian participants selected the oldest age groups. Most parents, however,endorsed a spiral curriculum, whereby topics are introduced sequentially throughout adolescents’ school careers. Thus, whilst on average participants were comfortable with adolescents having access to content on body anatomy younger ages (from 9–12 years to 12–15 years), they approved virtual content on relationships and sex at older school ages (from 12–15 years to 15–18 years). European ethnicity, liberal sociosexual attitudes, lower religiosity, and higher educational attainment were associated with parents approving adolescent exposure to digital sex education at younger ages. To our knowledge, this exploratory study is the first to quantitatively examine parental attitudes toward digital sex education curricula, as well as explore the parental characteristics that relate to these attitudes. This work should inform educators internationally on their future efforts to deploy virtual sexuality learning.

Cytotoxicity of Orthodontic Archwires Used in Clinical Practice: In Vitro Study

This study investigates the cytotoxicity of various orthodontic archwires, which are essential in directing tooth movement through biomechanical forces. With advancements in material science, different archwire materials have been developed to balance mechanical performance with aesthetic and biological considerations. The study focuses on evaluating the biocompatibility and mechanical properties of stainless steel, nickel–titanium, and chromium–cobalt archwires, particularly their cytotoxic effects on oral cavity cells. In vitro cell culture experiments with fibroblasts, combined with scanning electron microscopy (SEM) analysis, were conducted to assess cell viability and morphology. The results revealed significant differences in cytotoxicity, with copper wires showing high toxicity and causing extensive cell death, while nickel–titanium and chromium–cobalt wires supported better cell viability and healthier cell morphology. These findings highlight the importance of selecting archwire materials that ensure mechanical efficiency without compromising cellular health, emphasizing the need for ongoing assessment of material biocompatibility in the oral environment.

Pinwheel-like Curved Aromatics from the Cyclotrimerization of Strained Alkyne Cycloparaphenylenes.

Carbon nanomaterials composed of curved aromatics, such as carbon nanotubes, are difficult to selectively synthesize and modify precisely. Smaller molecular fragments of curved nanomaterials, such as cycloparaphenylenes, benefit from the precision of bottom-up synthesis, however, efforts to expand the curved molecular framework into even larger structures often rely on restrictive early stage synthetic strategies or difficult to control polymerizations. In this work we report a high yielding, strain-promoted, late-stage modification of a series of [n + 1]CPPs. We show that the conversion of these [n + 1]CPPs into soluble, pinwheel-like multipore carbon nanostructures is achievable via a straightforward and efficient metal-mediated alkyne cyclotrimerization reaction. We provide insight into suitable metals for this transformation, the photophysics of these trimeric molecules, as well as their strain profiles and crystal packing. We also demonstrate the strain-enhanced nature of the reaction under the optimized conditions, showing that strained internal-alkyne [n + 1]CPPs efficiently undergo complete conversion whereas unstrained diphenylacetylene remains completely unreacted. We anticipate that this work will have broader impacts on the study of reactivity in strained-alkyne-containing hydrocarbons, and that access to this new molecular architecture will inspire new research and applications in materials science and related fields.

Transforming science labs into automated factories of discovery.

Laboratories in chemistry, biochemistry, and materials science are at the leading edge of technology, discovering molecules and materials to unlock capabilities in energy, catalysis, biotechnology, sustainability, electronics, and more. Yet, most modern laboratories resemble factories from generations past, with a large reliance on humans manually performing synthesis and characterization tasks. Robotics and automation can enable scientific experiments to be conducted faster, more safely, more accurately, and with greater reproducibility, allowing scientists to tackle large societal problems in domains such as health and energy on a shorter timescale. We define five levels of laboratory automation, from laboratory assistance to full automation. We also introduce robotics research challenges that arise when increasing levels of automation and when increasing the generality of tasks within the laboratory. Robots are poised to transform science labs into automated factories of discovery that accelerate scientific progress.

Direct observation of deformation and resistance to damage accumulation during shock loading of stabilized nanocrystalline Cu-Ta alloys

Energy absorption by matter is fundamental to natural and man-made processes. However, despite this ubiquity, developing materials capable of withstanding severe energy fluxes without degradation is a significant challenge in materials science and engineering. Despite recent advances in creating alloys resistant to energy fluxes, mitigating the damage caused by the absorption and transfer of mechanical energy remains a critical obstacle in both fundamental science and technological applications. This challenge is especially prominent when the mechanical energy is transferred to the material by shock loading. This study demonstrates a phenomenon in which microstructurally stabilized nanocrystalline Cu-Ta alloys can undergo reversal or nearly complete recovery of the dislocation structure after multiple shock-loading impacts, unlike any other known metallic material. The microstructure of these alloys can withstand repeated shock-wave interactions at pressures up to 12 GPa without any significant microstructural damage or deterioration, demonstrating an extraordinary capacity to be virtually immune to the detrimental effects of shock loading.

Comparing SMILES and SELFIES tokenization for enhanced chemical language modeling

Life sciences research and experimentation are resource-intensive, requiring extensive trials and considerable time. Often, experiments do not achieve their intended objectives, but progress is made through trial and error, eventually leading to breakthroughs. Machine learning is transforming this traditional approach, providing methods to expedite processes and accelerate discoveries. Deep Learning is becoming increasingly prominent in chemistry, with Convolutional Graph Networks (CGN) being a key focus, though other approaches also show significant potential. This research explores the application of Natural Language Processing (NLP) to evaluate the effectiveness of chemical language representations, specifically SMILES and SELFIES, using tokenization methods such as Byte Pair Encoding (BPE) and a novel approach developed in this study, Atom Pair Encoding (APE), in BERT-based models. The primary objective is to assess how these tokenization techniques influence the performance of chemical language models in biophysics and physiology classification tasks. The findings reveal that APE, particularly when used with SMILES representations, significantly outperforms BPE by preserving the integrity and contextual relationships among chemical elements, thereby enhancing classification accuracy. Performance was evaluated in downstream classification tasks using three distinct datasets for HIV, toxicology, and blood–brain barrier penetration, with ROC-AUC serving as the evaluation metric. This study highlights the critical role of tokenization in processing chemical language and suggests that refining these techniques could lead to significant advancements in drug discovery and material science.

Normal Approximation of Random Gaussian Neural Networks

In this paper, we provide explicit upper bounds on some distances between the (law of the) output of a random Gaussian neural network and (the law of) a random Gaussian vector. Our main results concern deep random Gaussian neural networks with a rather general activation function. The upper bounds show how the widths of the layers, the activation function, and other architecture parameters affect the Gaussian approximation of the output. Our techniques, relying on Stein’s method and integration by parts formulas for the Gaussian law, yield estimates on distances that are indeed integral probability metrics and include the convex distance. This latter metric is defined by testing against indicator functions of measurable convex sets and so allows for accurate estimates of the probability that the output is localized in some region of the space, which is an aspect of a significant interest both from a practitioner’s and a theorist’s perspective. We illustrated our results by some numerical examples. Funding: This research was supported by the European Union’s Horizon 2020 research project WARIFA under grant agreement no. 101017385, by the PRIN project 2022 “Variational Analysis of Complex Systems in Materials Science, Physics and Biology” (CUP B53D23009290006), and by the INdAM project “Modelli ed Algoritmi per dati ad elevata dimensionalità” (CUP E53C23001670001).

Enhanced stimulated Raman and fluorescence imaging by single-frame trained BDN

Hyperspectral and multispectral imaging capture an expanded dimension of information that facilitates discoveries. However, image features are frequently obscured by noise generated from the limited photodamage threshold of the specimen. Although machine learning approaches demonstrate considerable promise in addressing this challenge, they typically require extensive datasets, which can be difficult to obtain. Here, we introduce BiFormer denoising network (BDN), designed to effectively and efficiently extract image features by utilizing both local and global level connections, sparse architectures, and fine-tuning. Experimental results indicate that BDN enhances the quality of stimulated Raman scattering (SRS) images by up to 16-fold in signal-to-noise ratio (SNR), particularly improving subtle features at higher spatial frequencies. Furthermore, BDN is successfully adapted to fluorescence imaging, achieving significant improvements in SNR and order-of-magnitude reduction in exposure time, thereby showcasing its versatility across various imaging modalities. Collectively, BDN exhibits substantial potential for spectroscopic imaging applications in the fields of biomedicine and materials science.

Progress on Carbon Dots with Intrinsic Bioactivities for Multimodal Theranostics.

Carbon dots (CDs) with intrinsic bioactivities are candidates for bioimaging and disease therapy due to their diverse bioactivities, high biocompatibility, and multiple functionalities in multimodal theranostics. It is a multidisciplinary research hotspot that includes biology, physics, materials science, and chemistry. This progress report discusses the CDs with intrinsic bioactivities and their applications in multimodal theranostics. The relationship between the synthesis and structure of CDs is summarized and analyzed from a material and chemical perspective. The bioactivities of CDs including anti-tumor, antibacterial, anti-inflammatory etc. are discussed from biological points of view. Subsequently, the optical and electronic properties of CDs that can be applied in the biomedical field are summarized from a physical perspective. Based on the functional review of CDs, their applications in the biomedical field are reviewed, including optical diagnosis and treatment, biological activity, etc. Unlike previous reviews, this review combines multiple disciplines to gain a more comprehensive understanding of the mechanisms, functions, and applications of CDs with intrinsic bioactivities.

Facilitating Ion Storage and Transport Pathways by In Situ Constructing 1D Carbon Nanotube Electric Bridges between 2D MXene Interlayers.

Multiple van der Waals (vdW) gaps invoke abundant opportunities for contriving artificial architectures and tailoring desired properties via the intercalation route beyond the reach of conventional concepts. Intriguingly, the electrochemical intercalation strategy can precisely and reversibly tune the intercalation stage of charged functional species. This study presents a valid structural editing protocol facilitated by electrochemical intercalation to engineer MXene interlayers, ultimately incorporating in situ constructed carbon nanotube (CNT) electric bridges for enhanced ion storage and transport pathways. The method allows for the precise modulation of electrochemical forces to tailor materials for specific applications. Deep intercalation and in situ growth processes establish robust anchoring sites and connectivity hubs between MXenes and CNTs, ensuring structural homogeneity and stability in advanced electrode materials. The results demonstrate the effectiveness of electrochemistry-mediated interlayer nanoengineering in MXenes, offering a versatile approach to design vdW heterostructures with tailored functionalities for energy storage and conversion applications. This work highlights the potential of electrochemical modulation in advancing materials engineering strategies for next-generation energy storage technologies.

Роль китайских пушкинистов в популяризации русской литературы в культурном континууме КНР

The aim of the study is to assess the scale of research and educational activities of Chinese scientists, whose focus is Russian literature, namely the work of Alexander Sergeevich Pushkin. To do this, the authors of the article identify and systematize the scientific works of Chinese scientists using the information capabilities of the scientific platform CNKI (China National Knowledge Infrastructure, “Zhongguo Zhiwan” – hereinafter Zhiwan). Various scientific materials are posted here, including those that provide an opportunity to get acquainted with the most popular works of Chinese Pushkin scholars. An analysis of the entire volume of publications on this site made it possible to highlight the names of outstanding Chinese scientists who devoted their lives to the study and popularization of Russian culture and literature among their com-patriots. The characteristic features of the activities of Chinese Russian scholars are highlighted and described. The authors identified and systematized, according to the degree of publication activity, Chinese printed publications that posted materials on the Zhiwan website that, to one degree or another, related to the study of the works of the great Russian poet and prose writer. Particular attention is paid to the systematization of monographs and articles not only by philologists, but also by representatives of other scientific fields. The authors presented a brief description of public events (conferences, competitions, etc.) held in China by scientific and educational institutions to popularize Russian spiritual culture. The research results reflected in the reports of Chinese Pushkin scholars can be found on the Zhiwan website. The methodological basis is the dialectical method of scientific knowledge, which made it possible to trace the continuity of the scientific research of Chinese Pushkinists. The systematic method revealed the wide capabilities of the CNKI scientific platform. The statistical method for identifying and processing textual information provided a quantitative description of the scale and depth of the study of Russian literature abroad. Thanks to the analytical-synthetic method, not only was a database of scientific works created by Chinese researchers of the life and work of A.S. Pushkin, but also their role in the popularization of Russian culture in China was revealed. The conducted research is interdisciplinary in nature and may be in demand by domestic and Chinese Pushkin scholars (philologists, historians, cultural experts, specialists in the field of art history).

Entropy Engineering of 2D Materials.

Entropy, a measure of disorder or uncertainty in the thermodynamics system, has been widely used to confer desirable functions to alloys and ceramics. The incorporation of three or more principal elements into a single sublattice increases the entropy to medium and high levels, imparting these materials a mélange of advanced mechanical and catalytic properties. In particular, when scaling down the dimensionality of crystals from bulk to the 2D space, the interplay between entropy stabilization and quantum confinement offers enticing opportunities for exploring new fundamental science and applications, since the structural ordering, phase stability, and local electronic states of these distorted 2D materials get significantly reshaped. During the last few years, the large family of high-entropy 2D materials is rapidly expanding to host MXenes, hydrotalcites, chalcogenides, metal-organic frameworks (MOFs), and many other uncharted members. Here, the recent advances in this dynamic field are reviewed, elucidating the influence of entropy on the fundamental properties and underlying elementary mechanisms of 2D materials. In particular, their structure-property relationships resulting from theoretical predictions and experimental findings are discussed. Furthermore, an outlook on the key challenges and opportunities of such an emerging field of 2D materials is also provided.

Research on the characteristics of the Helium plasma beam in HIT-PSI

As a high heat flux linear plasma device designed for studying divertor materials in future fusion reactors, HIT-PSI(Plasma Surface Interaction device at Harbin Institute of Technology) has been successfully constructed and has maintained stable operation since its completion. The characteristics of He plasma beams in HIT-PSI are investigated by emission spectroscopy and an infrared camera, with preliminary irradiation experiments conducted by bombarding tungsten with the beam. For relatively conservative discharge parameters, HIT-PSI achieved a steady-state heat flux capacity of ∼40 MW/m2 using infrared measurements, with the full width at half maximum (FWHM) of the heat flux beam reaching 4 mm. These characteristics make HIT-PSI an advanced platform for testing divertor materials and plasma-facing components, providing essential experimental supports for research and development of high-performance divertor materials.