Showing papers by "Missouri University of Science and Technology published in 2018"
04 Apr 2018
TL;DR: The most recent edition of the dermoscopic image analysis benchmark challenge as discussed by the authors was organized to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer.
Abstract: This article describes the design, implementation, and results of the latest installment of the dermoscopic image analysis benchmark challenge. The goal is to support research and development of algorithms for automated diagnosis of melanoma, the most lethal skin cancer. The challenge was divided into 3 tasks: lesion segmentation, feature detection, and disease classification. Participation involved 593 registrations, 81 pre-submissions, 46 finalized submissions (including a 4-page manuscript), and approximately 50 attendees, making this the largest standardized and comparative study in this field to date. While the official challenge duration and ranking of participants has concluded, the dataset snapshots remain available for further research and development.
1,419 citations
TL;DR: Q-learning and the integral RL algorithm as core algorithms for discrete time (DT) and continuous-time (CT) systems, respectively are discussed, and a new direction of off-policy RL for both CT and DT systems is discussed.
Abstract: This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal $\mathcal {H}_{2}$ and $\mathcal {H}_\infty $ control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.
536 citations
TL;DR: A review of modern trends in theoretical developments, novel designs and modern applications of sandwich structures can be found in this paper, where the most recent literature published at the time of writing this review is considered, older sources are listed only on as-needed basis.
Abstract: The review outlines modern trends in theoretical developments, novel designs and modern applications of sandwich structures. The most recent work published at the time of writing of this review is considered, older sources are listed only on as-needed basis. The review begins with the discussion on the analytical models and methods of analysis of sandwich structures as well as representative problems utilizing or comparing these models. Novel designs of sandwich structures is further elucidated concentrating on miscellaneous cores, introduction of nanotubes and smart materials in the elements of a sandwich structure as well as using functionally graded designs. Examples of problems experienced by developers and designers of sandwich structures, including typical damage, response under miscellaneous loads, environmental effects and fire are considered. Sample applications of sandwich structures included in the review concentrate on aerospace, civil and marine engineering, electronics and biomedical areas. Finally, the authors suggest a list of areas where they envision a pressing need in further research.
412 citations
TL;DR: A comprehensive survey on NFV is presented, which starts from the introduction of NFV motivations, and provides an extensive and in-depth discussion on state-of-the-art VNF algorithms including VNF placement, scheduling, migration, chaining and multicast.
361 citations
TL;DR: A systematic literature review of game-based learning systems, frameworks that integrate game design elements, and various implementations of gamification in higher education to identify how gamified learning systems can be used and categorize its usefulness inHigher education.
346 citations
TL;DR: A Ti3 C2 Tx MXene-based photonic diode that breaks time-reversal symmetry to achieve nonreciprocal transmission of nanosecond laser pulses is demonstrated and is found to show higher threshold for light-induced damage with up to 50% increase in nonlinear transmittance.
Abstract: MXenes comprise a new class of 2D transition metal carbides, nitrides, and carbonitrides that exhibit unique light-matter interactions. Recently, 2D Ti3 CNTx (Tx represents functional groups such as OH and F) was found to exhibit nonlinear saturable absorption (SA) or increased transmittance at higher light fluences, which is useful for mode locking in fiber-based femtosecond lasers. However, the fundamental origin and thickness dependence of SA behavior in MXenes remain to be understood. 2D Ti3 C2 Tx thin films of different thicknesses are fabricated using an interfacial film formation technique to systematically study their nonlinear optical properties. Using the open aperture Z-scan method, it is found that the SA behavior in Ti3 C2 Tx MXene arises from plasmon-induced increase in the ground state absorption at photon energies above the threshold for free carrier oscillations. The saturation fluence and modulation depth of Ti3 C2 Tx MXene is observed to be dependent on the film thickness. Unlike other 2D materials, Ti3 C2 Tx is found to show higher threshold for light-induced damage with up to 50% increase in nonlinear transmittance. Lastly, building on the SA behavior of Ti3 C2 Tx MXenes, a Ti3 C2 Tx MXene-based photonic diode that breaks time-reversal symmetry to achieve nonreciprocal transmission of nanosecond laser pulses is demonstrated.
308 citations
TL;DR: In this paper, an SP-based degradation model is developed by including Solid Electrolyte Interface (SEI) layer formation, coupled with crack propagation due to the stress generated by the volume expansion of the particles in the active materials.
289 citations
TL;DR: In this article, the authors demonstrate that two-dimensional MXenes (e.g., titanium carbide Ti3C2Tx) are a family of electrically conducting materials that are triboelectrically more negative than polytetrafluorethylene, or Teflon.
243 citations
TL;DR: In this paper, the dynamics of powder spattering in the laser powder bed fusion (LPBF) additive manufacturing (AM) process were investigated with in-situ high-speed high-energy x-ray imaging.
238 citations
TL;DR: The attainment of full charge delocalization within the parent framework and charge mobilities comparable to technologically relevant polymers and ceramics in a KxFe2(BDP)3 field-effect transistor represents the realization of a general synthetic strategy for the creation of new porous conductor-based devices.
Abstract: Conductive metal–organic frameworks are an emerging class of three-dimensional architectures with degrees of modularity, synthetic flexibility and structural predictability that are unprecedented in other porous materials. However, engendering long-range charge delocalization and establishing synthetic strategies that are broadly applicable to the diverse range of structures encountered for this class of materials remain challenging. Here, we report the synthesis of K
x
Fe2(BDP)3 (0 ≤ x ≤ 2; BDP2− = 1,4-benzenedipyrazolate), which exhibits full charge delocalization within the parent framework and charge mobilities comparable to technologically relevant polymers and ceramics. Through a battery of spectroscopic methods, computational techniques and single-microcrystal field-effect transistor measurements, we demonstrate that fractional reduction of Fe2(BDP)3 results in a metal–organic framework that displays a nearly 10,000-fold enhancement in conductivity along a single crystallographic axis. The attainment of such properties in a K
x
Fe2(BDP)3 field-effect transistor represents the realization of a general synthetic strategy for the creation of new porous conductor-based devices. A conducting metal–organic framework with charge delocalization by reductive potassium insertion is demonstrated. Integration into a field-effect transistor shows similar mobilities to semiconductors, with a mobility estimated to be at least 0.84 cm2 V–1 s–1.
228 citations
TL;DR: The results show that precipitation strengthening, as one of the main strengthening mechanisms, contributes to a tensile yield strength of ~1.52 GPa at room temperature, which heretofore represents the highest strength reported for an HEA with an appreciable failure strain of ~5.2%.
Abstract: High-entropy alloys (HEAs) are a class of metallic materials that have revolutionized alloy design. They are known for their high compressive strengths, often greater than 1 GPa; however, the tensile strengths of most reported HEAs are limited. Here, we report a strategy for the design and fabrication of HEAs that can achieve ultrahigh tensile strengths. The proposed strategy involves the introduction of a high density of hierarchical intragranular nanoprecipitates. To establish the validity of this strategy, we designed and fabricated a bulk Fe25Co25Ni25Al10Ti15 HEA to consist of a principal face-centered cubic (fcc) phase containing hierarchical intragranular nanoprecipitates. Our results show that precipitation strengthening, as one of the main strengthening mechanisms, contributes to a tensile yield strength (σ0.2) of ~1.86 GPa and an ultimate tensile strength of ~2.52 GPa at room temperature, which heretofore represents the highest strength reported for an HEA with an appreciable failure strain of ~5.2%.
TL;DR: In this paper, the authors evaluated the effects of two types of graphite nanoplatelet (GNP-C and GNP-M) and one type of carbon nanofiber (CNF) on rheological properties, hydration kinetics, autogenous shrinkage, and pore structure of ultra-highperformance concrete (UHPC).
TL;DR: In this article, the authors investigated the catalytic performance of Ni3Te2 and showed that increasing the covalency around the transition metal center enhances catalytic activity, which is the first instance where this hypothesis has been validated in the chalcogenide series.
Abstract: Designing efficient electrocatalysts has been one of the primary goals for water electrolysis, which is one of the most promising routes towards sustainable energy generation from renewable sources. In this article, we have tried to expand the family of transition metal chalcogenide based highly efficient OER electrocatalysts by investigating nickel telluride, Ni3Te2 as a catalyst for the first time. Interestingly Ni3Te2 electrodeposited on a GC electrode showed very low onset potential and overpotential at 10 mA cm−2 (180 mV), which is the lowest in the series of chalcogenides with similar stoichiometry, Ni3E2 (E = S, Se, Te) as well as Ni-oxides. This observation falls in line with the hypothesis that increasing the covalency around the transition metal center enhances catalytic activity. Such a hypothesis has been previously validated in oxide-based electrocatalysts by creating anion vacancies. However, this is the first instance where this hypothesis has been convincingly validated in the chalcogenide series. The operational stability of the Ni3Te2 electrocatalyst surface during the OER for an extended period of time in alkaline medium was confirmed through surface-sensitive analytical techniques such as XPS, as well as electrochemical methods which showed that the telluride surface did not undergo any corrosion, degradation, or compositional change. More importantly we have compared the catalyst activation step (Ni2+ → Ni3+ oxidation) in the chalcogenide series, through electrochemical cyclic voltammetry studies, and have shown that catalyst activation occurs at lower applied potential as the electronegativity of the anion decreases. From DFT calculations we have also shown that the hydroxyl attachment energy is more favorable on the Ni3Te2 surface compared to the Ni-oxide, confirming the enhanced catalytic activity of the telluride. Ni3Te2 also exhibited efficient HER catalytic activity in alkaline medium making it a very effective bifunctional catalyst for full water splitting with a cell voltage of 1.66 V at 10 mA cm−2. It should be noted here that this is the first report of OER and HER activity in the family of Ni-tellurides.
TL;DR: In this article, the authors provide a critical review on the current mechanistic understanding of three different catalyst types used in the ODPC reaction based on experimental studies; (i) zeolites with different frameworks, (ii) porous materials-supported metal oxides, and (iii) transition metal oxide and other metal catalysts.
Abstract: Oxidative dehydrogenation of propane in the presence of carbon dioxide (ODPC) is a sustainable approach and an attractive catalytic route for propylene production with less environmental footprint than the conventional oxidative dehydrogenation path with oxygen. Researchers have considered CO2 as a mild oxidant that can overcome the problems of over-oxidation and low propylene selectivity, that are typically associated with the current synthesis routes. This article provides a critical review on the current mechanistic understanding of three different catalyst types used in the ODPC reaction based on experimental studies; (i) zeolites with different frameworks, (ii) porous materials-supported metal oxides, and (iii) transition metal oxides and other metal catalysts. A detailed review of the literature compares the framework, pore structure, nature of active sites, reducibility, and the role of promoters and supports for each type of catalytic materials in the absence and presence of CO2, and is followed by a thorough discussion on the promotional effects of CO2 as a soft oxidant on C H bond scission. Future directions with respect to materials design, synthesis and reaction conditions are also discussed.
TL;DR: Both the image content sensitiveness and the user trustworthiness are integrated to train a tree classifier to recommend fine-grained privacy settings for social image sharing.
Abstract: To configure successful privacy settings for social image sharing, two issues are inseparable: 1) content sensitiveness of the images being shared; and 2) trustworthiness of the users being granted to see the images. This paper aims to consider these two inseparable issues simultaneously to recommend fine-grained privacy settings for social image sharing. For achieving more compact representation of image content sensitiveness (privacy), two approaches are developed: 1) a deep network is adapted to extract 1024-D discriminative deep features; and 2) a deep multiple instance learning algorithm is adopted to identify 280 privacy-sensitive object classes and events. Second, users on the social network are clustered into a set of representative social groups to generate a discriminative dictionary for user trustworthiness characterization. Finally, both the image content sensitiveness and the user trustworthiness are integrated to train a tree classifier to recommend fine-grained privacy settings for social image sharing. Our experimental studies have demonstrated both the efficiency and the effectiveness of our proposed algorithms.
TL;DR: It is indicated that sustainable control of membrane fouling requires employing more than one single approach, and large scale application of fouling mitigation strategies should be the focus of future studies.
TL;DR: This paper proposes a hierarchical decentralized SoS architecture for the energy management of a MMG system and formulates it as a bilevel optimization problem and addresses the problem of spatially unbalanced demand and generation in the area.
Abstract: The rapid development of microgrid (MG) has made it ready to connect multiple MGs for providing regional power supply. The energy management of a multi-MG (MMG) system is the key to the reliable, economic operation of the interconnected power system. The MMG system is rich in distributed generation sources. The intermittence and volatility of renewable energy sources (RESs), such as wind and solar, cannot be ignored in a large-scale hybrid power system. Therefore, the energy management of a MMG system is a complex problem that coordinates distributed generation units within individual MGs, the power exchange among MGs, and the power trading between the grid and MGs. System of systems (SoS) has been identified as an effective way of forming a MMG system and coordinating the participating MGs for energy management. This paper proposes a hierarchical decentralized SoS architecture for the energy management of a MMG system and, accordingly, formulates it as a bilevel optimization problem. Energy management at the level of individual MGs is modeled as a multiple-stage robust optimization to handle the issue of RES uncertainty. Energy management at the level of MMG system further addresses the problem of spatially unbalanced demand and generation in the area. The proposed MMG energy management is further verified through a case study.
TL;DR: This research provides support for the usefulness of the laddering approach to data collection and analysis, and provides some insight into key design criteria to better fit users’ needs and interests.
Abstract: This article examined factors associated with the adoption of smart wearable devices. More specifically, this research explored the contributing and inhibiting factors that influence the adoption o...
13 Jul 2018
TL;DR: The structural, elastic and electronic properties of two-dimensional (2D) titanium carbide/nitride based pristine and functionalized MXenes (Tin+1Cn/Tin + 1Nn) are investigated by density functional theory calculations as discussed by the authors.
Abstract: The structural, elastic and electronic properties of two-dimensional (2D) titanium carbide/nitride based pristine (Tin+1Cn/Tin+1Nn) and functionalized MXenes (Tin+1CnT2/Tin+1NnT2, T stands for the terminal groups: –F, –O and –OH, n = 1, 2, 3) are investigated by density functional theory calculations. Carbide-based MXenes possess larger lattice constants and monolayer thicknesses than nitride-based MXenes. The in-plane Young's moduli of Tin+1Nn are larger than those of Tin+1Cn, whereas in both systems they decrease with the increase of the monolayer thickness. Cohesive energy calculations indicate that MXenes with a larger monolayer thickness have a better structural stability. Adsorption energy calculations imply that Tin+1Nn have stronger preference to adhere to the terminal groups, which suggests more active surfaces for nitride-based MXenes. More importantly, nearly free electron states are observed to exist outside the surfaces of –OH functionalized carbide/nitride based MXenes, especially in Tin+1Nn(OH)2, which provide almost perfect transmission channels without nuclear scattering for electron transport. The overall electrical conductivity of nitride-based MXenes is determined to be higher than that of carbide-based MXenes. The exceptional properties of titanium nitride-based MXenes, including strong surface adsorption, high elastic constant and Young's modulus, and good metallic conductivity, make them promising materials for catalysis and energy storage applications.
TL;DR: In this paper, pozzolan slurry (including silica fume, nano-SiO2, and fly ash slurries) and CO2 treatments were investigated as enhancement methods for RCA.
Abstract: One of the most promising strategies to manage the large volume of construction and demolition (C&D) waste is recycling and utilizing it for the production of new concrete. However, recycled concrete aggregate (RCA) derived from C&D waste possesses relatively higher porosity and water absorption capability, which often limits its wild utilization. In this study, pozzolan slurry (includes silica fume, nano-SiO2, and fly ash slurries) and CO2 treatments as enhancement methods for RCA were investigated. Test results showed that CO2 treatment was more effective in reducing water absorption and enhancing fluidity, whereas pozzolan slurry treatment could decrease fluidity. Mortars prepared with treated RCA exhibited better mechanical strength and higher resistance towards carbonation and chloride-ion diffusion than those with untreated RCA. Both pozzolan slurry and CO2 treatments enhanced not only the properties of RCA, but also the old and new interfacial transition zones (ITZs) as demonstrated in the measured micro-hardness and SEM observation.
TL;DR: In this Review, the materials and fabrication methods to make micromodels, the main research activities that are conducted with micromadels and their applications in petroleum, geologic, and environmental engineering, as well as in the food and wood industries, are discussed.
Abstract: Complex fluid flow in porous media is ubiquitous in many natural and industrial processes. Direct visualization of the fluid structure and flow dynamics is critical for understanding and eventually manipulating these processes. However, the opacity of realistic porous media makes such visualization very challenging. Micromodels, microfluidic model porous media systems, have been developed to address this challenge. They provide a transparent interconnected porous network that enables the optical visualization of the complex fluid flow occurring inside at the pore scale. In this Review, the materials and fabrication methods to make micromodels, the main research activities that are conducted with micromodels and their applications in petroleum, geologic, and environmental engineering, as well as in the food and wood industries, are discussed. The potential applications of micromodels in other areas are also discussed and the key issues that should be addressed in the near future are proposed.
TL;DR: In this paper, the interfacial bond properties between embedded steel fibers with different shapes (straight, hooked, and corrugated fibers) and UHPC matrices proportioned with either 15% or 20% silica fume, by mass of binder, under different curing times were investigated.
Abstract: The use of steel fiber is essential to secure high strength and ductility in producing ultra-high performance concrete (UHPC). In this study, the interfacial bond properties between embedded steel fibers with different shapes (straight, hooked, and corrugated fibers) and UHPC matrices proportioned with either 15% or 20% silica fume, by mass of binder, under different curing times were investigated. Flexural properties of UHPC reinforced with 2% different shaped fibers were also evaluated. Test results showed that corrugated and hooked fibers significantly improved the bond properties by three to seven times when compared to those with straight fibers. The flexural strength of UHPC with corrugated and hooked fibers were enhanced by 8%–28% and 17%–50%, respectively. Microstructural results from MIP, BSEM, and TG confirmed the change in bond properties. The bond strength of straight fibers exponentially increased with the decrease of calcium hydroxide content. Based on the composite theory, the flexural strengths of UHPC made with different shaped fibers can be efficiently predicted using the fiber-matrix bond strength, the flexural strength of the UHPC matrix (non-fibrous matrix), and the parameters of fibers. The ratios of predicted to measured flexural strengths ranged between 0.8 and 1.1, in which straight fibers showed a larger discreteness due to higher sensitivity of flexural strength associated with the orientation of fibers.
TL;DR: In this article, a review of the recent literature on nano-technology and determine the most reliable mechanisms associated with different particles is presented along with different experimental studies, and possible limitations and challenges that face the combination of surfactants and nanoparticles in EOR applications are presented.
TL;DR: This paper proposes a novel multi-task allocation framework named MTasker, which adopts a descent greedy approach, where a quasi-optimal allocation plan is evolved by removing a set of task-worker pairs from the full set.
Abstract: Task allocation is a fundamental research issue in mobile crowd sensing. While earlier research focused mainly on single tasks, recent studies have started to investigate multi-task allocation, which considers the interdependency among multiple tasks. A common drawback shared by existing multi-task allocation approaches is that, although the overall utility of multiple tasks is optimized, the sensing quality of individual tasks may become poor as the number of tasks increases. To overcome this drawback, we re-define the multi-task allocation problem by introducing task-specific minimal sensing quality thresholds, with the objective of assigning an appropriate set of tasks to each worker such that the overall system utility is maximized. Our new problem also takes into account the maximum number of tasks allowed for each worker and the sensor availability of each mobile device. To solve this newly-defined problem, this paper proposes a novel multi-task allocation framework named MTasker. Different from previous approaches which start with an empty set and iteratively select task-worker pairs, MTasker adopts a descent greedy approach, where a quasi-optimal allocation plan is evolved by removing a set of task-worker pairs from the full set. Extensive evaluations based on real-world mobility traces show that MTasker outperforms the baseline methods under various settings, and our theoretical analysis proves that MTasker has a good approximation bound.
TL;DR: Detailed characterization of Fe( tri)2 and the Fe(tri)2(BF4) x materials via powder X-ray diffraction, Mössbauer spectroscopy, and IR and UV-vis-NIR diffuse reflectance spectroscopies reveals that the high conductivity arises from intervalence charge transfer between mixed-valence low-spin FeII/III centers.
Abstract: Metal–organic frameworks are of interest for use in a variety of electrochemical and electronic applications, although a detailed understanding of their charge transport behavior, which is of critical importance for enhancing electronic conductivities, remains limited. Herein, we report isolation of the mixed-valence framework materials, Fe(tri)2(BF4)x (tri– = 1,2,3-triazolate; x = 0.09, 0.22, and 0.33), obtained from the stoichiometric chemical oxidation of the poorly conductive iron(II) framework Fe(tri)2, and find that the conductivity increases dramatically with iron oxidation level. Notably, the most oxidized variant, Fe(tri)2(BF4)0.33, displays a room-temperature conductivity of 0.3(1) S/cm, which represents an increase of 8 orders of magnitude from that of the parent material and is one of the highest conductivity values reported among three-dimensional metal–organic frameworks. Detailed characterization of Fe(tri)2 and the Fe(tri)2(BF4)x materials via powder X-ray diffraction, Mossbauer spectrosco...
TL;DR: This paper develops and investigates a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform, and introduces a knowledge resource center (KRC) built on a cloud server for information intensive applications.
TL;DR: This review focuses on material reactivity, ink availability, printability, and process compatibility for facile manufacturing of bioresorbable electronics.
Abstract: Bioresorbable electronics refer to a new class of advanced electronics that can completely dissolve or disintegrate with environmentally and biologically benign byproducts in water and biofluids. They have provided a solution to the growing electronic waste problem with applications in temporary usage of electronics such as implantable devices and environmental sensors. Bioresorbable materials such as biodegradable polymers, dissolvable conductors, semiconductors, and dielectrics are extensively studied, enabling massive progress of bioresorbable electronic devices. Processing and patterning of these materials are predominantly relying on vacuum-based fabrication methods so far. However, for the purpose of commercialization, nonvacuum, low-cost, and facile manufacturing/printing approaches are the need of the hour. Bioresorbable electronic materials are generally more chemically reactive than conventional electronic materials, which require particular attention in developing the low-cost manufacturing processes in ambient environment. This review focuses on material reactivity, ink availability, printability, and process compatibility for facile manufacturing of bioresorbable electronics.
TL;DR: The aim is to quantify the potential of human activity recognition from kinetic energy harvesting (HARKE) and demonstrate that HARKE can save 79 percent of the overall system power consumption of conventional accelerometer-based HAR.
Abstract: Kinetic energy harvesting (KEH) may help combat battery issues in wearable devices. While the primary objective of KEH is to generate energy from human activities, the harvested energy itself contains information about human activities that most wearable devices try to detect using motion sensors. In principle, it is therefore possible to use KEH both as a power generator and a sensor for human activity recognition (HAR), saving sensor-related power consumption. Our aim is to quantify the potential of human activity recognition from kinetic energy harvesting (HARKE). We evaluate the performance of HARKE using two independent datasets: (i) a public accelerometer dataset converted into KEH data through theoretical modeling; and (ii) a real KEH dataset collected from volunteers performing activities of daily living while wearing a data-logger that we built of a piezoelectric energy harvester. Our results show that HARKE achieves an accuracy of 80 to 95 percent, depending on the dataset and the placement of the device on the human body. We conduct detailed power consumption measurements to understand and quantify the power saving opportunity of HARKE. The results demonstrate that HARKE can save 79 percent of the overall system power consumption of conventional accelerometer-based HAR.
TL;DR: The high-speed synchrotron X-ray imaging technique was synchronized with a custom-built laser-melting setup to capture the dynamics of laser powder-bed fusion processes in situ with high spatial and temporal resolution.
Abstract: The high-speed synchrotron X-ray imaging technique was synchronized with a custom-built laser-melting setup to capture the dynamics of laser powder-bed fusion processes in situ. Various significant phenomena, including vapor-depression and melt-pool dynamics and powder-spatter ejection, were captured with high spatial and temporal resolution. Imaging frame rates of up to 10 MHz were used to capture the rapid changes in these highly dynamic phenomena. At the same time, relatively slow frame rates were employed to capture large-scale changes during the process. This experimental platform will be vital in the further understanding of laser additive manufacturing processes and will be particularly helpful in guiding efforts to reduce or eliminate microstructural defects in additively manufactured parts.
TL;DR: In this paper, a multi-layer graphene embedded composite of aluminium alloys by direct exfoliation of graphite into graphene with the help of Friction Stir Alloying (FSA) was reported.
Abstract: The paper reports manufacturing of a multi-layer graphene embedded composite of aluminium alloys by direct exfoliation of graphite into graphene with the help of Friction Stir Alloying (FSA). The formation of this nano composite and optimization of the process parameters led to an approximately two-fold increase in the strength, without loss in ductility, due to the dispersion of the graphene in aluminium. The manufacturing process is scalable and cost effective as it uses graphite powder and aluminium sheets as the raw materials. The presence of graphene layers in the metal matrix was confirmed using Raman spectroscopy as well as TEM. The graphene sheet thickness was measured using AFM after extracting it from the composite. Molecular dynamic simulation results reveal the evolution of newer structures and defects that have resulted in the enhanced properties of the nano-composite. These findings open up newer possibilities toward efficient and scalable manufacturing of high strength high-ductility metal matrix based graphene nano-composites.