Materials Science Research Articles

Influence of perturbative intertube interactions on ballistic and quasi-ballistic phonon transports in double-walled carbon nanotubes

Assembling single-walled carbon nanotubes (SWCNT) into multiwalled carbon nanotubes (MWCNT) reduces the intrinsically high thermal conductivity of individual SWCNTs. Typically, this reduction can be explained by structural imperfections, e.g., defects, and van der Waals (vdW) intertube interactions between the constituent SWCNTs are considered to have negligible impacts on the reduction. However, intertube interactions should alter the transport characteristics of low-frequency phonons responsible for heat conduction, which implies that intertube interactions may also reduce the thermal conductivity of MWCNTs when low-frequency phonons modulated by intertube interactions participate in the overall heat conduction. In this study, by applying a combination of the atomistic Green's function method and nonequilibrium molecular dynamics simulation to double-walled carbon nanotubes (DWCNT) with different chiral configurations of SWCNTs and various lengths, we investigated the length scale and chiral configuration where perturbative intertube interactions can suppress phonon transports. We found that thermal resistance attributed to intertube interactions manifests in the low-temperature ballistic regime and quasi-ballistic regime for DWCNT lengths greater than 1 μm. Revisiting the influence of the intertube interactions helps comprehend the intrinsic origin of the reduced thermal conductivity of MWCNTs. In addition, the reported findings are beneficial for the thermal engineering of SWCNT-assembled materials, including emerging one-dimensional vdW heterostructures.

Real Time Tracking of Nanoconfined Water-Assisted Ion Transfer in Functionalized Graphene Derivatives Supercapacitor Electrodes.

Water molecules confined in nanoscale spaces of 2D graphene layers have fascinated researchers worldwide for the past several years, especially in the context of energy storage applications. The water molecules exchanged along with ions during the electrochemical process can aid in wetting and stabilizing the layered materials resulting in an anomalous enhancement in the performance of supercapacitor electrodes. Engineering of 2D carbon electrode materials with various functionalities (oxygen (─O), fluorine (─F), nitrile (─C≡N), carboxylic (─COOH), carbonyl (─C═O), nitrogen (─N)) can alter the ion/water organization in graphene derivatives, and eventually their inherent ion storage ability. Thus, in the current study, a comparative set of functionalized graphene derivatives-fluorine-doped cyanographene (G-F-CN), cyanographene (G-CN), graphene acid (G-COOH), oxidized graphene acid (G-COOH (O)) and nitrogen superdoped graphene (G-N) is systematically evaluated toward charge storage in various aqueous-based electrolyte systems. Differences in functionalization on graphene derivatives influence the electrochemical properties, and the real-time mass exchange during the electrochemical process is monitored by electrochemical quartz crystal microbalance (EQCM). Electrogravimetric assessment revealed that oxidized 2D acid derivatives (G-COOH (O)) are shown to exhibit high ion storage performance along with maximum water transfer during the electrochemical process. The complex understanding of the processes gained during supercapacitor electrode charging in aqueous electrolytes paves the way toward the rational utilization of graphene derivatives in forefront energy storage applications.

Learners’ Essential Skills and Schools’ Readiness towards Limited Face-to-face Classes

This research assessed the learners’ essential skills and the schools’ readiness towards limited face-to-face classes at Naga Central Elementary School and Greenhills Elementary School in Cebu for the school year 2021-2022. It used a descriptive quantitative design and a universal sampling technique to select the respondents. An adapted questionnaire was administered to kindergarten parents and teachers. Data were gathered using frequency count, percentage, weighted mean, and T-test independent samples. The findings revealed that most parents were between the ages of 21 and 26, the majority were females, attained high school diplomas, had three to four primary school-aged children, and had a combined monthly income of Php 10,000 or less. Moreover, most of the teacher respondents were aged 29-34. Half had a bachelor's degree and had a length of service of less than 10 years. The results further indicate high confidence among parents and teachers regarding school readiness, with parents rating readiness as "very high" and teachers as "high." However, differences in perceptions led to rejecting the null hypothesis. Kindergarten learners' readiness was assessed based on essential skills in literacy, mathematics, and motor skills, with parents rating all skills as "very proficient" and teachers as "proficient." A significant difference was found in literacy skills, leading to the rejection of the null hypothesis, while mathematical and motor skills did not show significant differences. Overall, positive feedback suggests satisfactory readiness levels, with suggestions for improvement, including using interactive digital learning materials and worksheets to enhance the learning experience.

Advancing Sustainable Transportation Education: A Comprehensive Analysis of Electric Vehicle Prototype Design and Fabrication

The global shift towards electric vehicles (EVs) has necessitated a paradigm shift in engineering education, emphasizing hands-on experiences and innovative learning approaches. This review article presents a comprehensive analysis of the design and fabrication process of an educational EV prototype, highlighting its significance in preparing future engineers for the rapidly evolving EV industry. The article delves into the historical development and recent trends in EVs, providing context for the growing importance of practical skills in this field. A detailed examination of the key components and systems in modern EVs, such as battery packs, electric motors, transmission systems, and chassis design, lays the foundation for understanding the complexities involved in EV prototype development. The methodology section explores the research approach, conceptual design, simulations, material selection, and construction techniques employed in the creation of an educational EV prototype. The evaluation and testing phase assesses the prototype’s performance, safety, and reliability, offering valuable insights into the lessons learned and areas for improvement. The impact of such projects on engineering education is discussed, emphasizing the importance of hands-on learning experiences and interdisciplinary collaboration in preparing students for future careers in the EV industry. The article concludes by addressing common challenges faced during EV prototype projects and providing recommendations for future educational initiatives in this field.

Single-Image-Based Deep Learning for Precise Atomic Defect Identification.

Defect engineering is widely used to impart the desired functionalities on materials. Despite the widespread application of atomic-resolution scanning transmission electron microscopy (STEM), traditional methods for defect analysis are highly sensitive to random noise and human bias. While deep learning (DL) presents a viable alternative, it requires extensive amounts of training data with labeled ground truth. Herein, employing cycle generative adversarial networks (CycleGAN) and U-Nets, we propose a method based on a single experimental STEM image to tackle high annotation costs and image noise for defect detection. Not only atomic defects but also oxygen dopants in monolayer MoS2 are visualized. The method can be readily extended to other two-dimensional systems, as the training is based on unit-cell-level images. Therefore, our results outline novel ways to train the model with minimal data sets, offering great opportunities to fully exploit the power of DL in the materials science community.

Ionic Liquid Induced Aggregation and Precipitation Behavior of Pinacyanol

AbstractIn this paper, we demonstrate the unique role of ionic liquids (ILs) as dye aggregation and precipitation promoter. Specifically, we have observed that the presence of small amount of IL such as 1‐butyl‐3‐methylimidazolium hexaflurophosphate ([bmim][PF6]), 1‐butyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide ([bmim][Tf2N]), 1‐butyl‐3‐methylimidazolium trifluoromethanesulfonate ([bmim][OTf]), 1‐butyl‐3‐methylimidazolium tetrafluoroborate ([bmim][BF4]) and 1‐butyl‐1‐methylpyrrolidinium bis(trifluoromethylsulfonyl)imide ([bmpyrr][Tf2N]) in aqueous milieu can help in the conversion of a cyanine dye 1,1’‐Diethyl‐2,2’‐carbocyanine iodide (Pinacyanol iodide) into J‐ and H‐aggregates followed by time dependent precipitation of the dye. The anion of the added IL strongly affects the aggregation process in aqueous solution. Addition of small amount of BF4− anion based IL [bmim][BF4] to aqueous solution of the dye initially induces J‐ and H‐aggregation followed by quick precipitation of the dye in time dependent manner. Presence of small amount of other anion containing ILs such as ([bmim][PF6]), ([bmim][OTf]), ([bmim][Tf2N]) and ([bmpyrr][Tf2N]) strongly supports H‐aggregation of the dye in aqueous solution whereas higher wt % of added ILs also caused precipitation of the dye in a time dependent manner. The nature of the IL anion, wt % of added IL and temperature conditions decides efficiencies of aggregation and precipitation processes. The dual yet unique behavior of ILs as an additive influence the aggregation of cyanine dyes and precipitation has been demonstrated. The observed results can contribute towards various application for dye aggregates and in the removal of dyes from water. The developed process can find potential applications in the field of material science, wastewater treatment, future light harvesting systems, and opto‐electronics related fields.

A comparative analysis of crustacean exoskeletons: structural, microstructural, morphological, and UV absorption studies

Abstract This study aims to investigate the structural, thermal, and spectral characteristics along with ultra-violet (UV) absorption of various marine benthos exoskeletons, such as various species of crabs (Portunus sanguinolentus, Portunus pelagicus, Charybdis feriata) and mantis shrimp (Oratosquilla oratoria). Their unique properties and ability to survive in harsh oceanic environments make them interesting research subjects. This research utilized powder X-ray diffraction (XRD) analysis to determine the crystal structure of the benthic varieties. The sample surface was analysed using high-resolution micrographs obtained from field-emission scanning electron microscopy (FESEM) identified the presence of chitin and calcite in the marine benthos, which was further confirmed by differential scanning calorimetry (DSC), and Fourier transform infrared spectroscopy (FTIR). The optical characteristics were investigated using UV-visible spectroscopy. The proximate analysis revealed high protein content in the mantis shrimp exoskeleton compared to other crab species, revealing its excellent UV-absorption characteristics. Overall, this research has the potential to broaden our understanding of marine organisms, which can have potential applications in biotechnology and materials science to develop nature-inspired innovative materials sustainably.

Photoresponsive metal-organic framework materials for advance applications.

The interaction between light and materials produces a range of phenomena within molecular systems, leading to advanced applications in the field of materials science. In this regard, metal-organic framework (MOF) materials have become superior candidates to others because of their easy tailor-made synthetic methods via incorporation of photoactive moieties into their structural assembly. Photoresponsive MOFs exhibit a massive variety of exciting properties, including photochromism, photomagnetism, photoluminescence, photon up or down conversion, photoconductivity, nonlinear optical properties, photosalient effects and photoinduced switching of conformations. These photoresponsive properties of MOFs regulate different potential applications, such as on-demand gas sorption and separation, optical sensing, fabrication of photoactuators and photosensing electronic devices, dye degradation, catalysis, cargo delivery, ink-free erasable printing, bio-imaging and drug delivery in biological systems. Therefore, judicious crystal engineering along with an understanding of their structure-property relationship will lead to the fabrication of desired photosensitive MOFs. Herein, we attempted to incorporate categorical descriptions based on advanced applications of photoresponsive MOFs considering a wide range of recent publications.

Atomic Precision Processing of Two-Dimensional Materials for Next-Generation Microelectronics.

The growth of the information era economy is driving the pursuit of advanced materials for microelectronics, spurred by exploration into "Beyond CMOS" and "More than Moore" paradigms. Atomically thin 2D materials, such as transition metal dichalcogenides (TMDCs), show great potential for next-generation microelectronics due to their properties and defect engineering capabilities. This perspective delves into atomic precision processing (APP) techniques like atomic layer deposition (ALD), epitaxy, atomic layer etching (ALE), and atomic precision advanced manufacturing (APAM) for the fabrication and modification of 2D materials, essential for future semiconductor devices. Additive APP methods like ALD and epitaxy provide precise control over composition, crystallinity, and thickness at the atomic scale, facilitating high-performance device integration. Subtractive APP techniques, such as ALE, focus on atomic-scale etching control for 2D material functionality and manufacturing. In APAM, modification techniques aim at atomic-scale defect control, offering tailored device functions and improved performance. Achieving optimal performance and energy efficiency in 2D material-based microelectronics requires a comprehensive approach encompassing fundamental understanding, process modeling, and high-throughput metrology. The outlook for APP in 2D materials is promising, with ongoing developments poised to impact manufacturing and fundamental materials science. Integration with advanced metrology and codesign frameworks will accelerate the realization of next-generation microelectronics enabled by 2D materials.

Revealing the effects of pressure on periodic descriptors

A number of researchers have proposed different scales for calculating the various atomic descriptors. Atomic descriptors viz. electronegativity and hardness, react differently to varied pressures as demonstrated by a recent study. This work explores the complex interplay in the field of molecular interactions involving pressure, electronegativity, chemical hardness and electrophilicity index. Although it is known that pressure plays a vital role in adjusting the electrical features of molecules, a little is known about how pressure specifically affects basic chemical ideas. After a thorough analysis, we have revealed the complex impact of pressure on the atomic electrophilicity index. The principles of equalisation for hardness, electronegativity and electrophilicity under various pressures (0, 200 and 500 GPa) have been analysed and presented in a novel way. This study advances our understanding of pressure's effect on molecular characteristics. The knowledge gathered from this research has a wide range of usage in scientific fields, which include materials science and chemical reactivity in harsh environments. It also lays the groundwork for future works pertaining to pressure-driven molecular design and application developments.

Comparison of Monte Carlo Tools for Displacement Calculations for Protons and Heavy Ions Irradiation on Iron and EUROFER97

Abstract Ion irradiation of structural materials for the current and future generation nuclear reactors is a widespread technique used to simulate neutron irradiation in the context of material science research. During the designing phase of irradiation experiments Monte Carlo transport codes are often employed to quantify the radiation exposure, by estimating the displacements per atom (dpa) quantity. From the available displacement calculation codes, four popular choices were selected: cern-fluka, mcnp, phits, and srim. These codes will be used to simulate the irradiation effects of proton and Fe ions on pure iron (G379) and EUROFER97 alloy (a common material in fusion applications) targets. Results coming from the different software are presented in the form of damage profiles and of number of displacements as a function of the primary beam energy. This study identifies discrepancies between the codes' outputs and provides optimized simulation setup parameters.

Lewis Base-Catalyzed Dynamic Kinetic Asymmetric Transformation of Racemic Chlorosilanes en Route to Si-Stereogenic Silylethers.

Enantiopure Si-stereogenic organosilanes are highly valued in the fields of organic synthesis, development of advanced materials, and drug discovery. However, they are not naturally occurring, and their synthesis has been largely confined to resolution of racemic silanes or desymmetrization of symmetric silanes. In contrast, the dynamic kinetic asymmetric transformation (DYKAT) of racemic organosilanes offers a mechanistically distinct approach and would broaden the accessibility of Si-stereogenic silanes in an enantioconvergent manner. In this study, we report a Lewis base-catalyzed DYKAT of racemic chlorosilanes. The chiral isothiourea catalyst, (S)-benzotetramisole, facilitates silyletherification with phenols, yielding (R)-silylethers in good yields with high enantioselectivity (27 examples, up to 86% yield, up to 98:2 er). Kinetic analysis, control experiments, and DFT calculations suggest that a two-catalyst-bound pentacoordinate silicate is responsible for the Si-configurational epimerization of the ion-paired tetracoordinated silicon intermediates.

Fabrication of Azacrown Ether‐Embedded Covalent Organic Frameworks for Enhanced Cathode Performance in Aqueous Ni−Zn Batteries

AbstractCrown ethers (CEs), known for their exceptional host–guest complexation, offer potential as linkers in covalent organic frameworks (COFs) for enhanced performance in catalysis and host–guest binding. However, their highly flexible conformation and low symmetry limit the diversity of CE‐derived COFs. Here, we introduce a novel C3‐symmetrical azacrown ether (ACE) building block, tris(pyrido)[18]crown‐6 (TPy18C6), for COF fabrication (ACE‐COF‐1 and ACE‐COF‐2) via reticular synthesis. This approach enables precise integration of CEs into COFs, enhancing Ni2+ ion immobilization while maintaining crystallinity. The resulting Ni2+‐doped COFs (Ni@ACE‐COF‐1 and Ni@ACE‐COF‐2) exhibit high discharge capacity (up to 1.27 mAh ⋅ cm−2 at 8 mA ⋅ cm−2) and exceptional cycling stability (>1000 cycles) as cathode materials in aqueous alkaline nickel‐zinc batteries. This study serves as an exemplar of the seamless integration of macrocyclic chemistry and reticular chemistry, laying the groundwork for extending the macrocyclic‐synthon driven strategy to a diverse array of COF building blocks, ultimately yielding advanced materials tailored for specific applications.

Absence of causality between seismic activity and global warming

Abstract. There is no more consequential scientific matter today than global warming. The societal and policy implications, however, hinge upon the attribution of that warming to human activity and, specifically, continued societal reliance on the burning of fossil fuels. It was recently suggested that this warming could be explained by the non-anthropogenic factor of seismic activity. If that is the case, it would have profound implications. We have assessed the validity of the claim using a statistical technique (the method of conditional dispersion) that evaluates the existence of causal connections between variables, finding no evidence for any causal relationship between seismic activity and global warming.

Spanish Doctoral Dissertations on the Properties of Materials in Engineering

We present a bibliometric study of engineering doctoral dissertations focusing on the properties of materials. The study exhaustively examines the production of doctoral theses on material properties in the field of engineering at Spanish universities from 1977 to 2022. The main objective is to analyse the volume and temporal distribution of these theses, explore their production by authors and directors considering gender, and identify the most common descriptors in the research. Technological innovation and progress in engineering materials are essential for social welfare, economic competitiveness, and international cooperation, highlighting the significance of these studies. The results reveal a total of 508 valid theses after a meticulous filtering process, with a notable increase in production post-1998, particularly during 2011–2020. The study highlights the limited presence of women in both authorship and direction of these, indicating male dominance in the field. However, there is an increasing trend of female participation in these academic areas. This study offers detailed insights into the trends and composition of doctoral research in materials engineering in Spain, pointing to important gender dynamics and research themes.

Applications of machine learning in materials science: From a methodological point of view

Discovering new functional materials with certain properties using high-throughout methods is of vital importance for materials science. The advancement of the machine learning method has provided a new, more efficient pathway for this procedure. Traditional trial-and-error methods have been supplanted by in-silico simulations, which facilitate rapid material discovery. Machine learning (ML) has further accelerated this process by uncovering patterns and relationships within complex computational data sets, thus enhancing predictive abilities for material properties and performance. This integration of computational methods and machine learning holds great potential, promising a future where material limitations are overcome, catalyzing technological breakthroughs. Furthermore, ML also inspired advancements in fields like crystallography and metallurgy, and enhancing energy storage materials. Despite challenges in model interpretability, overfitting, and data quality, ML presents an exciting evolution toward a data-driven discipline. Ultimately, ML promises to reduce the time from materials discovery to deployment, turning material limitations into catalysts for innovation.

Sustainable polyurethane coatings derived from alkyds of Camelina oil monoglycerides

AbstractThis study presents the synthesis of sustainable urethane coatings derived from alkyds of Camelina oil (CO) monoglycerides, offering a sustainable alternative to petrochemical resources. Utilizing immobilized lipase for a low‐temperature glycerolysis reaction, high‐yield monoglycerides were obtained from CO. These were then reacted with dibasic acids (phthalic, succinic, and maleic anhydride) to produce alkyd diols, confirmed by both nuclear magnetic resonance (NMR) and Fourier transform infrared (FTIR) spectroscopy. The hydroxyl functionality of the alkyd diols showed a significant enhancement (up to 2200%) over crude CO produced Camelina‐based alkyd diols were incorporated into polyurethane formulations and applied to metal substrates. Comprehensive performance evaluations revealed their superior mechanical, thermal, and chemical properties in comparison with previously reported plant‐based alkyd‐urethane coatings, especially for the phthalic anhydride‐derived alkyd diol. The present research underscores the potential of Camelina‐derived alkyds in creating high‐performance, plant‐based coatings, aligning with recent sustainability trends in material science.

Recent Progress of Induced Spermatogenesis In Vitro

Sperm, a crucial gamete for reproduction in sexual reproduction, is generated through the proliferation, differentiation, and morphological transformations of spermatogonial stem cells within the specialized microenvironment of the testes. Replicating this environment artificially presents challenges. However, interdisciplinary advancements in physics, materials science, and cell engineering have facilitated the utilization of innovative materials, technologies, and structures for inducing in vitro sperm production. This article offers a comprehensive overview of research progress on inducing in vitro sperm production by categorizing techniques into two major systems based on matrix-based and non-matrix-based approaches, respectively. Detailed discussions are provided for both types of technology systems through comparisons of their similarities and differences, as well as research advancements. The aim is to provide researchers in this field with a comprehensive panoramic view while presenting our own perspectives and prospects.

Standardization of Chemically Selective Atomic Force Microscopy for Metal Oxide Surfaces.

The structures of metal oxide surfaces and inherent defects are vital for a variety of applications in materials science and chemistry. While scanning probe microscopy can reveal atomic-scale details, elemental discrimination usually requires indirect assumptions and extensive theoretical modeling. Here, atomic force microscopy with O-terminated copper tips on a variety of sample systems demonstrates not only a clear and universal chemical contrast but also immediate access to the atomic configuration of defects. The chemically selective contrast is explained by purely electrostatic interactions between the negatively charged tip-apex and the strongly varying electrostatic potential of metal and oxygen sites. These results offer a standardized methodology for the direct characterization of even the most complex metal oxide surfaces, providing fundamental insight into atomic-scale processes in these material systems.

Pore Chemistry and Architecture Control in Anionic Functional Ultramicroporous Materials for Record Dense Packing of Xenon.

Adsorptive separation of Xe and Kr is an industrially promising but challenging process because of their identical shape and similar physicochemical properties. Herein, we demonstrate a strategy through rationally designing the linkers of anionic functional ultramicroporous materials (FUMs) to finely regulate the pore chemistry and architecture, which creates unique stepped channels incorporating dense polar nanotraps to generate a larger effective pore space and enables dense packing of Xe. A new hydrolytically stable FUM (ZUL-530) was prepared, which for the first time achieves a Xe packing density exceeding the liquid Xe density at atmospheric conditions in metal-organic frameworks (MOFs) (based on experimental data), resulting in both excellent Xe uptake (2.55 mmol g-1 at 0.2 bar) and high IAST selectivity (20.5). GCMC and DFT-D calculations reveal the essential role of the stepped traps in the dense packing of Xe. Breakthrough experiments demonstrate remarkable productivities of both high-purity Kr (6.70 mmol g-1) and Xe (1.78 mmol g-1) for the Xe/Kr (20:80) mixture. In a model nuclear industry exhaust gas, ZUL-530 exhibits a top-class Xe dynamic capacity (28.8 mmol kg-1) for trace Xe, which proves it is one of the best candidates for Xe/Kr separation.