Hasil untuk "Materials of engineering and construction. Mechanics of materials"

Cong Sui, Shengting Zhang, Dachuan Zhang et al.

Tomoaki Sakurada, Woo Seok Lee, Yeongsu Cho et al.

2D materials exhibiting in-plane anisotropy enable novel functionality in electronic, optoelectronic, and photonic devices, yet their availability is generally limited to naturally-occurring low-symmetry van der Waals compounds. Here, we demonstrate an approach to structural engineering in a family of blue-emitting 2D silver phenylchalcogenide semiconductors based on steric interactions among surface-bound organic molecular ligands. By strategically halogenating specific sites of phenyl ligands, we demonstrate dramatic changes to the inorganic AgSe plane in mithrene (silver phenylselenolate, AgSePh). Density functional theory revealed pronounced in-plane electronic anisotropy for direct-gap fluorinated derivatives, while a chlorinated variant exhibited a direct-to-indirect bandgap transition. Furthermore, some fluorinated variants displayed strongly polarized absorption and luminescence, accompanied by a 10x enhancement in photoluminescence quantum yield. This work establishes a versatile approach for tailoring optoelectronic properties in hybrid semiconductors that is difficult or impossible to achieve in all-inorganic materials alone, offering new opportunities in advanced material design.

Akash Ganesan, Renaldo Springer, Andrew Howell et al.

Abstract Aging power plants must cycle more frequently as the sector shifts to renewables, increasing susceptibility to contamination, localized corrosion, and tubing failures. Herein, we examine how high-resolution X-ray computed tomography can provide new insights into the relationship between localized, general corrosion rates and boiler water chemistries. The following study examines how chloride and sulfate contaminants impact carbon steel corrosion at 300 °C and 12.4 MPa, which are typical conditions in utility boilers and evaporators. The localized corrosion rates caused by sulfate and chloride contamination were, on average, 2.69 and 5.55 mm y−1, respectively, an order of magnitude larger than the uniform corrosion rates, 0.16 and 0.40 mm y−1 at the same conditions. Chloride caused a few deep pits, whereas sulfate tended to form more shallow pits during the same timeframe. This study highlights the need to detect and quantify localized corrosion in boiler tubing and the effectiveness of X-ray computed tomography in assessing corrosion rates.

CHANG Xinyu, ZHOU Yan, LEI Honggang

[Purposes] This research is conducted to solve the problems of the low applicable height of ordinary concrete-filled steel tubular special-shaped columns and the easy separation of steel tube and concrete at the internal corner. [Methods] Three concrete-filled square steel tubular columns were welded to form an L-shaped composite special-shaped column, and ultra-high-strength grouting material with standard compressive strength greater than 100 MPa was used in the composite L-shaped columns. The influences of different grouting material strengths and steel tube wall thicknesses on their axial compression performances were studied through experiments. [Findings] The results show that the axial compression bearing capacity of composite L-shaped columns with ultra-high-strength grouting materials is 92%-170% higher than that of pure steel L-shaped columns. With the increase of the strength of high-strength grouting materials, the restraining effect of steel pipe on high-strength grouting material decreases, and the ductility of the specimen increases. The wall thickness of the steel pipe increases from 4 to 6 mm, which can effectively prevent local buckling. The failure mode of the component changes from buckling failure to bending deformation, and the ductility of the specimen increases by more than 50% on average. By comparing the results of the axial compression bearing capacity test with the results obtained from the axial compression bearing capacity calculation formula in 8 current codes at home and abroad, the calculated value obtained by using the specification AISC 360 is the closest to the test result. The research results can improve the axial compression bearing capacity and ductility of the composite special-shaped columns, improve the problem that the steel tube and concrete are easily separated at the internal corners, and help the application and promotion of ultra-high-strength grouting materials in the structure of concrete-filled steel tube special-shaped columns.

Indra Cipta, Indriana Kartini, Akhmad Syoufian et al.

The study investigated the impact of three alcoholic solvents—ethanol (Et), ethylene glycol (EG), and glycerol (GLY)—on the solvothermal synthesis of the supported photocatalyst BiOI/natural halloysite. Characterization using FTIR, X-ray diffraction, SEM, TEM, DR-UV-Vis, and fluorescence spectroscopy provided insights into the structure, phase, morphology, and optical properties. Natural halloysite (HAL) was sourced from Gamalama volcanic soil. Consequently, varied BiOI and Bi5O7I phases, sizes, and morphologies were observed with different solvents. Ethylene glycol and ethanol produced spherical BiOI particles (1–5 μm in diameter), while glycerol yielded tube-shaped Bi5O7I particles (1 μm). The incorporation of halloysite hindered BiOI agglomeration, leading to an increase in the bandgap energy. The bandgap energy for BiOI (Et) was 1.98 eV, whereas for BiOI/HAL (Gly), it was 2.79 eV. Natural halloysite effectively reduced electron-hole recombination, as confirmed by fluorescence spectroscopy. This study elucidates how the selection of solvent and the addition of halloysite modulate the properties of the resulting photocatalyst. This study is the first to report the use of natural halloysite from Gamalama as a supporting material for Bismuth Oxyiodide (BiOI). Our findings reveal that natural halloysite can prevent BiOI agglomeration, increase bandgap energy, and reduce electron-hole recombination.

Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon et al.

Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partially replaced by ground granulated blast furnace slag (GGBFS) with various amounts to make the concrete eco-friendly. The concrete was reinforced with several quantities of PP fiber. Specific cases of beams and cylinders made from PFRC were examined to learn more about their performance. The research contributes valuable insights to eco-friendly concrete design by integrating industrial byproducts (GGBFS) and non-metallic fibers, aligning with sustainable construction trends. The study demonstrates that adding sustainable fibers to concrete improves its structural integrity while lessening its environmental impact. Experimental testing validates the proposed model, showing a significant connection between the expected and actual stress-strain behavior. In terms of absolute relative error (ARE), the dataset proves that the suggested model has both the greatest (ARE 5 %) and worst (ARE > 15 %) frequencies. The proposed model demonstrates promising accuracy (R-value = 0.9975) and highlights the effectiveness of PSO in parameter optimization. Additionally, the usage of GGBFS instead of OPC resulted in CO2 reduction up to 42 %. Comparative analysis of the proposed model against existing models registered an excellent forecasted accuracy.

Ehsan Samiei, Teodor Veres, Axel Günther

ABSTRACT To expand the use of collagen‐based biomaterials beyond their current applications in three‐dimensional (3D) cell culture, tissue engineering, and biofabrication, limitations such as poor shear‐thinning behavior and poor control over porosity during gelation need to be overcome. Granular biomaterials promise to address these constraints, however their uniform and scalable preparation from extracellular matrix materials is challenging. To address this need, we employed a droplet microfluidic approach and prepared irregularly shaped microgels of fibrillar collagen and collagen‐glycosaminoglycan (GAG) copolymer in a continuous oil phase, at rates of up to 5500 s−1. The approach allowed us to tune the average microgel size from 40 to 170 µm. Microgels obtained after removal of the oil phase were found to promote the attachment and proliferation of human fibroblasts and mesenchymal stromal/stem cells. Granular materials prepared with packing densities exceeding 65 vol% exhibited shear‐thinning rheological behavior, a requirement for use as injectable biomaterials and bioinks. Cell‐containing granular biomaterials contracted 2.8 times less than thermally gelled matrices of comparable collagen and cell concentration. In a case study, a skin tissue model prepared from a fibroblast containing collagen‐GAG (CG) microgels layer covered with an epithelium revealed immunohistochemical markers associated with intact human skin after month‐long air–liquid interface (ALI) culture.

Po-Hao Chou, Chung-Yu Mou, Chung-Hou Chung et al.

We develop a gauge-invariant renormalized mean-field theory (RMFT) to reliably find the quantum spin liquid (QSL) states and their field response for realistic Kitaev materials under strong magnetic fields and described by the generalized Kitaev $J$-$K$-$Γ$-$Γ'$ model. Remarkably, while our RMFT reproduces previous results based on using more complicated numerical methods, it also predicts several new stable QSL states. In particular, since Kitaev spin liquid (KSL) is no longer a saddle point solution, a new exotic 2-cone state distinct from the KSL, is found to describe experimental observations well, and hence should be the candidate state realized in the Kitaev material, $α$-RuCl$_3$. We further explore the mechanism for the suppression of the observed thermal Hall conductivity at low temperatures within the fermionic framework, and show that the polar-angle dependence of the fermionic gap can distinguish the found 2-cone state from the KSL state in further experiments.

Arthur Pilone, Paulo Meirelles, Fabio Kon et al.

A central challenge for ensuring the success of software projects is to assure the convergence of developers' and users' views. While the availability of large amounts of user data from social media, app store reviews, and support channels bears many benefits, it still remains unclear how software development teams can effectively use this data. We present an LLM-powered approach called DeeperMatcher that helps agile teams use crowd-based requirements engineering (CrowdRE) in their issue and task management. We are currently implementing a command-line tool that enables developers to match issues with relevant user reviews. We validated our approach on an existing English dataset from a well-known open-source project. Additionally, to check how well DeeperMatcher works for other languages, we conducted a single-case mechanism experiment alongside developers of a local project that has issues and user feedback in Brazilian Portuguese. Our preliminary analysis indicates that the accuracy of our approach is highly dependent on the text embedding method used. We discuss further refinements needed for reliable crowd-based requirements engineering with multilingual support.

Suman Itani, Yibo Zhang, Jiadong Zang

The discovery of magnetic materials with high operating temperature ranges and optimized performance is essential for advanced applications. Current data-driven approaches are limited by the lack of accurate, comprehensive, and feature-rich databases. This study aims to address this challenge by using Large Language Models (LLMs) to create a comprehensive, experiment-based, magnetic materials database named the Northeast Materials Database (NEMAD), which consists of 67,573 magnetic materials entries(www.nemad.org). The database incorporates chemical composition, magnetic phase transition temperatures, structural details, and magnetic properties. Enabled by NEMAD, we trained machine learning models to classify materials and predict transition temperatures. Our classification model achieved an accuracy of 90% in categorizing materials as ferromagnetic (FM), antiferromagnetic (AFM), and non-magnetic (NM). The regression models predict Curie (Néel) temperature with a coefficient of determination (R2) of 0.87 (0.83) and a mean absolute error (MAE) of 56K (38K). These models identified 25 (13) FM (AFM) candidates with a predicted Curie (Néel) temperature above 500K (100K) from the Materials Project. This work shows the feasibility of combining LLMs for automated data extraction and machine learning models to accelerate the discovery of magnetic materials.

G.M.A.M. El-Fallah

High silicon bainitic steels have gained significant recognition in various applications due to their exceptional properties, such as high strength, favourable corrosion resistance, and excellent high-temperature stability. This study investigates an alloy capable of generating a finer bainitic structure through a transformation at 260 °C, leading to the desired microstructure. Interestingly, other phenomena were discovered while pursuing optimal heat treatment conditions. At temperatures exceeding 850 °C, the alloy exhibits a tendency for graphite formation, which has intriguing implications for its mechanical properties. The high silicon concentration in the alloy significantly retards cementite growth, resulting in a microstructure composed solely of bainitic ferrite and residual austenite through the transformation of austenite below the bainite start temperature. Furthermore, it is observed that pearlite formed during rapid transformation at 650 °C does not exhibit the predicted equilibrium chemical composition. This discrepancy challenges the existing models of pearlite growth, which assume local equilibrium at the shared interface with austenite. This research aims to investigate the influence of silicon content on solid-state transformations in high-silicon steels using dilatometry, optical microscopy, scanning electron microscopy, and X–ray diffraction techniques. These analytical methods will provide insights into the intricate processes occurring during isothermal transformation temperatures, contributing to a deeper understanding of the material's behaviour and its potential applications.

E. G. S. Zanni, C.C.A. Ferreira, A.T. Harada et al.

The following work analyzed the changes in the properties of Fatigue in a 300M aeronautical steel after the application of thermochemical treatments of plasma nitriding and laser carburizing. The microstructural characterization of the formed layers and the hardness obtained after the surface treatments were conducted. Thus, a comparison was made between the two treatments to verify which one has better efficacy. It has been observed that the treatment of plasma nitriding improves significantly the fatigue properties of 300 M steel. It was also noted that laser carburizing was not efficient to improve fatigue life.

Yihao Chen, Simon A. Rogers, Suresh Narayanan et al.

An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their mechanical history. Here, we employ x-ray photon correlation spectroscopy (XPCS) with \textit{in situ} rheometry to characterize memory formation in a nanocolloidal soft glass due to cyclic shear. During a cycle, particles undergo irreversible displacements composed of a combination of shear-induced diffusion and strain fields. The magnitudes of these displacements decrease with each cycle before reaching a steady state where the microstructure has become trained to achieve enhanced reversibility. The displacements resemble a random walk in which the directions in each cycle are independent of those in preceding cycles. Accompanying the training is a steady decrease in the dissipation during each cycle towards a steady state value. Memory of this training is revealed by measurements in which the amplitude of the shear is changed after steady state is reached. The magnitude of the particle displacements as well as the dissipation and the change in residual stress vary non-monotonically with the new strain amplitude, having minima near the training amplitude, thereby revealing both microscopic and macroscopic signatures of memory.

Francesco Pietro Campo, Mario Grosso

Lime is used in a variety of industrial sectors (e.g. construction materials, iron and steel industry, flue gas cleaning, etc.) By the thermal decomposition of limestone (CaCO3), known as calcination, two products are obtained: CO2 and quicklime, i.e. calcium oxide (CaO). There is a growing interest in quantifying and improving the potential of CO2 absorption of lime containing products during their operational life. The carbonation occurs during the lifetime of the lime application and it consists in the absorption of atmospheric CO2 that closes the loop by forming calcium carbonate back. Thus, a portion of the CO2 emitted during calcination is reabsorbed and stored in a permanent stable form. A literature review was carried out on the Carbonation Rate (CR) of lime used in three different construction materials: air-lime mortars, mixed air-lime mortars and hemplime. Out of 205 scientific publications reviewed, only 57 provide information about CR, specifically 21 for air-lime mortars, 27 for mixed air-lime mortars and 9 for hemplime. CR is 80-92% for pure air-lime mortars, 20-23% for mixed ones and 55% for hemplime. For all the materials, the CR trend over time was also assessed, according to the Fick’s law.

Hisashi Hirukawa, Yoshiyuki Furuya, Hideaki Nishikawa et al.

The new fatigue data sheet, No. 132, discloses gigacycle fatigue properties of the A6061-T6 aluminium alloys at high stress ratios. The fatigue tests were conducted mainly by the ultrasonic fatigue testing at 20 kHz, while conventional fatigue tests at 100 Hz were also conducted for comparison. The fatigue test results indicated that fatigue limits were obscure in the A6061-T6 alloys. Many specimens failed at over 107 cycles, developing internal fractures as well as surface fractures. On the other hand, fatigue failures at over 109 cycles were very rare, suggesting the presence of new fatigue limits in the gigacycle region. The differences in fatigue test results were negligible between the 20 kHz and 100 Hz tests, demonstrating that the 20 kHz tests were comparable to the conventional fatigue tests on this material. The fatigue strengths evaluated by the stress amplitude were decreased according to increase in the stress ratios, while the degradation of the fatigue strengths was not so serious. The fatigue strengths were higher than the modified Goodman lines, meaning that the stress ratio effects could be estimated by conventional ways.

Brendan Deibert, Travis Wiens

Low-cost small-scale (<100 W) electrohydrostatic actuators (EHAs) are not available on the market, largely due to a lack of suitable components. Utilizing plastic 3D printing, a novel inverse shuttle valve has been produced which, when assembled with emerging small-scale hydraulic pumps and cylinders from the radio-controlled hobby industry, forms a low-cost and high-performance miniature EHA. This paper presents experimental test results that characterize such a system and highlight its steady, dynamic, and thermal performance capabilities. The results indicate that the constructed EHA has good hydraulic efficiency downstream of the pump and good dynamic response but is limited by the efficiency of the pump and the associated heat generated from the pump’s losses. The findings presented in this paper validate the use of a 3D printed plastic inverse shuttle valve in the construction of a low-cost miniature EHA system.

Viktoriya Pakharenko, Otavio Augusto Titton Dias, Sankha Mukherjee et al.

Abstract The structural changes of the glucopyranose chain and the chemical compositional response of cellulose nanofibers (CNFs) under thermal exposure (at 190 °C for 5 h) have remained a significant gap in the understanding of the long-term performance of nanocellulose. Herein, CNF films with different chemical compositions were investigated to confirm the structural transformation of glucopyranose (coupling constant of OH groups changed up to 50%) by nuclear magnetic resonance (NMR) analysis. Remarkably, the glucopyranose rings underwent partial dehydration during the thermal exposure resulting in enol formation. This study confirms the chain mobility that could lead to the conformational and dimensional changes of the CNFs during thermal exposure. The broad range of conformations was defined by the dihedral angles that varied from ±27° to ±139° after thermal exposure. Investigation into the mechanism involving chemical transformation of the substrates during heating is important for the fabrication of the next generation of flexible electrical materials.

Alberto Castro, Umberto de Giovannini, Shusuke A. Sato et al.

We demonstrate that the electronic structure of a material can be deformed into Floquet pseudo-bands with arbitrarily tailored shapes. We achieve this goal with a novel combination of quantum optimal control theory and Floquet engineering. The power and versatility of this framework is demonstrated here by utilizing the independent-electron tight-binding description of the $π$ electronic system of graphene. We show several prototype examples focusing on the region around the K (Dirac) point of the Brillouin zone: creation of a gap with opposing flat valence and conduction bands, creation of a gap with opposing concave symmetric valence and conduction bands -- which would correspond to a material with an effective negative electron-hole mass --, or closure of the gap when departing from a modified graphene model with a non-zero field-free gap. We employ time periodic drives with several frequency components and polarizations, in contrast to the usual monochromatic fields, and use control theory to find the amplitudes of each component that optimize the shape of the bands as desired. In addition, we use quantum control methods to find realistic switch-on pulses that bring the material into the predefined stationary Floquet band structure, i.e. into a state in which the desired Floquet modes of the target bands are fully occupied, so that they should remain stroboscopically stationary, with long lifetimes, when the weak periodic drives are started. Finally, we note that although we have focused on solid state materials, the technique that we propose could be equally used for the Floquet engineering of ultracold atoms in optical lattices, and to other non-equilibrium dynamical and correlated systems.

Benedikt Hoock, Santiago Rigamonti, Claudia Draxl

A main goal of data-driven materials research is to find optimal low-dimensional descriptors, allowing us to predict a physical property, and to interpret them in a human-understandable way. In this work, we advance methods to identify descriptors out of a large pool of candidate features by means of compressed sensing. To this extent, we develop schemes for engineering appropriate candidate features that are based on simple basic properties of building blocks that constitute the materials and that are able to represent a multi-component system by scalar numbers. Cross-validation based feature-selection methods are developed for identifying the most relevant features, thereby focusing on high generalizability. We apply our approaches to an \textit{ab initio} dataset of ternary group-IV compounds to obtain a set of descriptors for predicting lattice constants and energies of mixing. In particular, we introduce simple complexity measures in terms of involved algebraic operations as well as the amount of utilized basic properties.

Rama K. Vasudevan, Erick Orozco, Sergei V. Kalinin

The design of materials structure for optimizing functional properties and potentially, the discovery of novel behaviors is a keystone problem in materials science. In many cases microstructural models underpinning materials functionality are available and well understood. However, optimization of average properties via microstructural engineering often leads to combinatorically intractable problems. Here, we explore the use of the reinforcement learning (RL) for microstructure optimization targeting the discovery of the physical mechanisms behind enhanced functionalities. We illustrate that RL can provide insights into the mechanisms driving properties of interest in a 2D discrete Landau ferroelectrics simulator. Intriguingly, we find that non-trivial phenomena emerge if the rewards are assigned to favor physically impossible tasks, which we illustrate through rewarding RL agents to rotate polarization vectors to energetically unfavorable positions. We further find that strategies to induce polarization curl can be non-intuitive, based on analysis of learned agent policies. This study suggests that RL is a promising machine learning method for material design optimization tasks, and for better understanding the dynamics of microstructural simulations.