Research: Recent submissions
Now showing items 1-20 of 30823
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A Stable Neural Network-Based Eikonal Tomography using Hard-Constrained Measurements(Authorea, Inc., 2023-03-26) [Preprint]Eikonal tomography, or travel time inversion, has been one of the primary seismological tools for decades and has been used to understand Earth’s properties and dynamic processes. At the heart of the inversion process is the need for an accurate, and preferably flexible, eikonal solver to compute the travel time field. Most of the conventional eikonal solvers, however, suffer from first-order convergence errors and difficulties in dealing with irregular computational grids. Physics-informed neural networks (PINNs) have been introduced to tackle these problems and have shown great success in addressing those challenges. Nevertheless, these approaches still suffer from slow convergence and unstable training dynamics due to the multi-term nature of the loss function. To improve on this, we propose a new formulation for the isotropic eikonal equation, which imposes boundary conditions as hard constraints. We employ the theory of functional connections to the eikonal tomography problem, which allows for the utilization of a single loss term for training the PINN model. Through rigorous numerical tests, its efficiency, stability, and flexibility in tackling a variety of cases, including topography-dependent and 3D models, are attested, thus providing an efficient and stable PINN-based eikonal tomography.
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Bioengineering of air-filled protein nanoparticles by genetic and chemical functionalization.(Journal of nanobiotechnology, Springer Science and Business Media LLC, 2023-03-25) [Article]Background: Various bacteria and archaea, including halophilic archaeon Halobacterium sp. NRC-1 produce gas vesicle nanoparticles (GVNPs), a unique class of stable, air-filled intracellular proteinaceous nanostructures. GVNPs are an attractive tool for biotechnological applications due to their readily production, purification, and unique physical properties. GVNPs are spindle- or cylinder-shaped, typically with a length of 100 nm to 1.5 μm and a width of 30–250 nm. Multiple monomeric subunits of GvpA and GvpC proteins form the GVNP shell, and several additional proteins are required as minor structural or assembly proteins. The haloarchaeal genetic system has been successfully used to produce and bioengineer GVNPs by fusing several foreign proteins with GvpC and has shown various applications, such as biocatalysis, diagnostics, bioimaging, drug delivery, and vaccine development. Results: We demonstrated that native GvpC can be removed in a low salt buffer during the GVNP purification, leaving the GvpA-based GVNP's shell intact and stable under physiological conditions. Here, we report a genetic engineering and chemical modification approach for functionalizing the major GVNP protein, GvpA. This novel approach is based on combinatorial cysteine mutagenesis within GvpA and genetic expansion of the N-terminal and C-terminal regions. Consequently, we generated GvpA single, double, and triple cysteine variant libraries and investigated the impact of mutations on the structure and physical shape of the GVNPs formed. We used a thiol–maleimide chemistry strategy to introduce the biotechnological relevant activity by maleimide-activated streptavidin–biotin and maleimide-activated SpyTag003-SpyCatcher003 mediated functionalization of GVNPs. Conclusion: The merger of these genetic and chemical functionalization approaches significantly extends these novel protein nanomaterials' bioengineering and functionalization potential to assemble catalytically active proteins, biomaterials, and vaccines onto one nanoparticle in a modular fashion.
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Efficient Near-Infrared Electroluminescence from Lanthanide-Doped Perovskite Quantum Cutters(Angewandte Chemie (International ed. in English), Wiley, 2023-03-25) [Article]Perovskite nanocrystals (PeNCs) deliver size and composition-tunable luminescence of high efficiency and color purity in the visible. However, attaining efficient electroluminescence (EL) in the near-infrared (NIR) region from PeNCs is challenging, limiting their potential applications. Here we demonstrate a highly efficient NIR light emitting diode (LED) by doping ytterbium ions into the PeNCs host (Yb3+:PeNCs), extending the EL wavelengths toward 1000 nm, which is achieved through a direct sensitization of Yb3+ ions by the PeNC host. Efficient quantum cutting processes enable high photoluminescence quantum yields (PLQYs) of up to 126% from the Yb3+:PeNCs. Through halide-composition engineering and surface passivation strategy to improve both PLQY and charge transport balance, we demonstrate an efficient NIR LED with a peak EQE of 7.7% at a central wavelength of 990 nm, representing the most efficient perovskite-based LEDs with emission wavelengths beyond 850 nm.
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Nano-Strategies for Lignin Biomaterials towards Cancer Therapy(Advanced Healthcare Materials, Wiley, 2023-03-25) [Article]Lignin is a nontoxic and biocompatible biopolymer with many promising characteristics, including a high tensile strength and antioxidant properties. This natural polymer can be processed through several chemical methods and modified into lignin nanomaterials for potential biomedical applications. This review summarizes the latest developments in nanolignin (NL)-based biomaterials for cancer therapy; various NL applications related to cancer therapy are considered, including drug and gene delivery, biosensing, bioimaging, and tissue engineering. The manuscript also outlines the potential use of these materials to improve the therapeutic potency of chemotherapeutic drugs by decreasing their dose and reducing their adverse effects. Due to its high surface area-to-volume ratio and the easy modification of its chemical components, NL could serve as an appropriate matrix for the binding and controlled release of various pharmaceutical agents. Moreover, the challenges in the utilization of NL-based materials for cancer therapy are discussed, along with the prospects of advances in such nanomaterials for medical research applications.
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Frankenstein’s data-driven computing approach to model-free mechanics(Computational Mechanics, Springer Science and Business Media LLC, 2023-03-25) [Article]This paper proposes a data-driven method to predict mechanical responses for structures directly from full-field observations obtained on previously tested structures, with minimal introduction of arbitrary models. The fundamental concept is to directly use raw data, called patches from hereon, comprising displacement fields over large domains, obtained during data harvesting through full-field measurement. These displacement fields have been observed on domains of real structures, and hence are naturally viable solutions from static, kinematic, and constitutive viewpoint. We compile a library of such patches to compute response for new structures. Patches are assembled as pieces of a jigsaw puzzle, similar to how Frankenstein put his monster together from human patches. The approach is illustrated using a traditional beam problem for simplicity. However, the approach is not limited to beam or even solid mechanics, the concept can be applied to predict a wide range of physics and multi-physics phenomena.
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Quartz–H2–Brine Bacterium Wettability under Realistic Geo-Conditions: Towards Geological Hydrogen Storage(Energy & Fuels, American Chemical Society (ACS), 2023-03-24) [Article]In this study, quartz substrates were incubated in sulfate-reducing bacteria (SRB) culture for 21 days at room temperature. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were used to quantify the bacterium effect, i.e., organic metabolite acids on the wetting behavior of the mineral surface. We examined the wettability of the quartz substrate before and after microorganism effects under reservoir conditions, i.e., 0 to 27 MPa pressures and 50 °C temperature. Nevertheless, there is no study reported to date for real geologic conditions, including for hydrogen–bacteria–rock wettability, which is proven to determine storage capacities, withdrawal rates, and containment security. Our findings reveal that the pH value of quartz dipped in the nutrient solution without SRB did not change meaningfully for 21 days. However, it significantly reduced from 7.58 to 5.98 with SRB. These microorganisms produce H2S, release the organic metabolite acids, and change the wettability of the mineral. The wettability of quartz surface changes from 4.2° to 14.4°, i.e., a 10.2% increase at 27 MPa and 50 °C after the bacterium effect. FTIR indicates the hydroxyl, amine, and carboxyl group (i.e., acetic acid) spectra in the microorganism solution. Inductively coupled plasma mass spectrometry (ICP-MS) shows that the concentrations of sulfate (SO42− ), aluminum (Al), iron (Fe), calcium (Ca), and magnesium (Mg) have significantly reduced after the SRB effect. Overall, strong water-wet quartz shifted to less water-wet quartz after the microorganism effect under the reservoir conditions. SRB slightly reduce the residual trapping effect. Hence, this process might have enhanced the withdrawing efficiency of H2 in high brine-saturated sandstone reservoir rock under the microbial activity.
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Editorial Special Issue on Dielectrics for 2-D Electronics(IEEE Transactions on Electron Devices, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-24) [Article, Editorial]It is our great pleasure to introduce this Special Issue on Dielectrics for 2-D Electronics to the IEEE TRANSACTIONS ON ELECTRON DEVICES readership. This Special Issue features the latest research aiming to clarify which would be the most suitable dielectric materials for state-of-the-art electronic devices containing 2-D materials.
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Runtime Assurance for Safety-Critical Systems: An Introduction to Safety Filtering Approaches for Complex Control Systems(IEEE Control Systems, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-24) [Article]More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force of gravity), flying over 400 kn (over 460 mi/h). With its pilot unconscious, the aircraft turn devolved into a dive, dropping from over 17,000 ft to lower than 8,000 ft in altitude in less than 10 s. An auditory warning in the cockpit called out to the pilot “altitude, altitude” just before he crossed through 11,000 ft, switching to a command to “pull up” around 8,000 ft. Meanwhile, the student’s instructor was watching the event unfold from his own aircraft. As the student’s aircraft passed through 12,500 ft, the instructor called over the radio “two recover,” commanding the student (“two”) to end the dive. As the student’s aircraft passed through 11,000 ft, the instructor’s “two recover!” came with increased urgency. At 9,000 ft, and with terror rising in his voice, the instructor yelled “TWO RECOVER!” Fortunately, at the same time as the instructor’s third panicked radio call, a new runtime assurance (RTA) system kicked in to automatically recover the aircraft. The Automatic Ground Collision Avoidance System (Auto GCAS), an RTA system integrated on the jets fewer than two years earlier, in fall 2014, detected that the aircraft was about to collide, commanded a roll to wings level and pull-up maneuver, and recovered the aircraft fewer than 3,000 ft above the ground. The event described here occurred in May 2016. A video from the event was declassified and publicly released in September 2016, and the footage can be found at [1] . While Auto GCAS monitored the behavior of a safety-critical cyberphysical system with a human providing the primary control functions, the same concept is gaining attention in the autonomy community looking to assure safety while integrating complex and intelligent control system designs.
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Joint Demosaicing and Fusion of Multiresolution Coded Acquisitions: An Unified Image Formation and Reconstruction Method(IEEE Transactions on Computational Imaging, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-24) [Article]Novel optical imaging devices allow for hybrid acquisition modalities such as compressed acquisitions with locally different spatial and spectral resolutions captured by the same focal plane array. In this work, we propose to model a multiresolution coded acquisition (MRCA) in a generic framework, which natively includes acquisitions by conventional systems such as those based on spectral/color filter arrays, compressed coded apertures, and multiresolution sensing. We propose a model-based image reconstruction algorithm performing a joint demosaicing and fusion (JoDeFu) of any acquisition modeled in the MRCA framework. The JoDeFu reconstruction algorithm solves an inverse problem with a proximal splitting technique and is able to reconstruct an uncompressed image datacube at the highest available spatial and spectral resolution.
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Rice Gene Index (RGI): a comprehensive pan-genome database for comparative and functional genomics of Asian rice.(Molecular plant, Elsevier BV, 2023-03-24) [Article]To integrate the genomic information of the rice pan-genome, we performed comparative analyses and established a user-friendly Rice Gene Index (RGI, https://riceome.hzau.edu.cn) platform with 16 platinum standard reference genomes and supplementary transcriptome data. To logically organize and scientifically the index of 744,233 genes among rice accessions, we detected 112,658 Ortholog Gene Indices, and provide ‘GeneCard’ pages to query genomic, transcriptomic, and homology information for each gene. The RGI allows users to search for relationships and comprehensive information of genes in keyword-based, sequence-based, and relationship-based ways. Furthermore, users can visualize these relationships at local and global scales corresponding to ‘Microcollinearity’ and ‘Macrocollinearity’ modules.
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Ferroelectricity in layered bismuth oxide down to 1 nanometer(Science, American Association for the Advancement of Science (AAAS), 2023-03-24) [Article]Atomic-scale ferroelectrics are of great interest for high-density electronics, particularly field-effect transistors, low-power logic, and nonvolatile memories. We devised a film with a layered structure of bismuth oxide that can stabilize the ferroelectric state down to 1 nanometer through samarium bondage. This film can be grown on a variety of substrates with a cost-effective chemical solution deposition. We observed a standard ferroelectric hysteresis loop down to a thickness of ~1 nanometer. The thin films with thicknesses that range from 1 to 4.56 nanometers possess a relatively large remanent polarization from 17 to 50 microcoulombs per square centimeter. We verified the structure with first-principles calculations, which also pointed to the material being a lone pair–driven ferroelectric material. The structure design of the ultrathin ferroelectric films has great potential for the manufacturing of atomic-scale electronic devices.
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Catch the Pitch of 5G FWA: EMF and Throughput Measurements of 3.5 GHz Standalone Deployment in a Baseball Stadium(IEEE Open Journal of the Communications Society, Institute of Electrical and Electronics Engineers (IEEE), 2023-03-23) [Article]The provisioning of 5G technology does not only involve mobile terminals, but also new services such as Fixed Wireless Access (FWA). The aim of this study is to examine the ElectroMagnetic Field (EMF) and throughput performance of a FWA deployment utilizing Standalone technology operating at 3.5 GHz. To address the unique characteristics of 5G FWA signals, an innovative framework has been designed based on the measurement of 5G FWA spectrum using four independent chains and an additional traffic generation chain to saturate the radio link capacity at the measurement location. Methodologies for evaluating 5G FWA exposure under conservative conditions, such as measurements of exposure during active traffic generation and maximum power extrapolations, are also introduced. Results from real measurements taken at a baseball stadium show that 5G FWA exposure is consistently low, typically below 0.4 V/m, with an upper bound of 0.59 V/m, while the achieved throughput is up to 250 Mbps. Additionally, the measured 5G exposure levels are a small fraction compared to those emitted by other technologies such as 4G. Furthermore, the values estimated by simulation from the output power counters of the base station are found to be in close agreement with the measured exposure levels.
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Cooling Energy and Climate Change Nexus in Arid Climate and the Role of Energy Transition(Buildings, MDPI AG, 2023-03-23) [Article]Buildings are significant contributors to climate change through their energy consumption, particularly in countries with hot and dry climates where cooling services require substantial amounts of energy. Climate change is expected to increase cooling demand, further exacerbating the problem. This study investigates the impact of climate change on cooling demands in different building types in Qatar and evaluates related environmental impacts. Using a high-resolution regional climate model, future climate data were obtained for 2071 and 2100 under the Representative Concentration Pathway (RCP) 4.5. The energy consumption of eight prototype buildings was simulated under baseline and future climates, and the environmental impacts were assessed using Life Cycle Assessment (LCA) for natural gas and solar power as energy sources. The study found that the cooling demand could increase by 13–53% and 19–67% in 2071 and 2100, respectively, with buildings having higher thermal insulation and lower window-to-wall ratio being less affected by climate change. The LCA results showed that replacing natural gas with solar power can reduce cooling energy-associated CO2 emissions by 92%. However, challenges such as human toxicity and metal depletion need to be addressed. The study highlights the importance of considering potential climate change scenarios to develop more resilient buildings and encourages implementing efficient recycling and waste management strategies before implementing PV panels.
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Updated guidelines for gene nomenclature in wheat(Theoretical and Applied Genetics, Springer Science and Business Media LLC, 2023-03-23) [Article]Key message: Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.
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Applications of Depth Minimization of Decision Trees Containing Hypotheses for Multiple-Value Decision Tables(Entropy, MDPI AG, 2023-03-23) [Article]In this research, we consider decision trees that incorporate standard queries with one feature per query as well as hypotheses consisting of all features’ values. These decision trees are used to represent knowledge and are comparable to those investigated in exact learning, in which membership queries and equivalence queries are used. As an application, we look into the issue of creating decision trees for two cases: the sorting of a sequence that contains equal elements and multiple-value decision tables which are modified from UCI Machine Learning Repository. We contrast the efficiency of several forms of optimal (considering the parameter depth) decision trees with hypotheses for the aforementioned applications. We also investigate the efficiency of decision trees built by dynamic programming and by an entropy-based greedy method. We discovered that the greedy algorithm produces very similar results compared to the results of dynamic programming algorithms. Therefore, since the dynamic programming algorithms take a long time, we may readily apply the greedy algorithms.
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Elastic response of porous rock to accumulated slip on strike slip fault networks in geo-reservoirs(International Journal of Rock Mechanics and Mining Sciences, Elsevier BV, 2023-03-23) [Article]Subsurface reservoirs are generally highly fractured, whereby fractures constitute a natural fluid flow path and define the preferential flow direction. Slip accumulated during the faulting process alters also the petrophysical properties of the host rock. Although the mechanical alteration of the host rock, and related porosity and permeability changes, due to fault slip has been previously described, a predictive physics-based model has not been scaled with fault length in reservoirs to provide an initial porosity permeability alteration model yet. In this study, we develop a predictive model to quantify how accumulated fault slip changes porosity and permeability in a porous medium, by combining deformation modeling based on triangular dislocations and linearized poro-elasticity equations. We applied our model the Ghawar field fault map and rock-types. We conducted a Monte-Carlo simulation, varying fault roughness and accumulated slip, to quantify the corresponding variation in porosity and permeability using a 5 km long strike-slip fault and three different rock-types. Our Monte-Carlo simulation shows that long-term accumulated slip on rough strike-slip fault surfaces change porosity by ±1%, leading to an absolute permeability change of up to 22.5%. We further used these results as a benchmark for the elastic response of porous rocks to accumulated slip scaled to certain fault length. Using these benchmark results for Ghawar field reservoir rocks, we determined the slip-related porous medium permeability changes for every fault on the Ghawar fault map, accounting for their length, location, and orientation. In doing so, we found that fault roughness, slip amount, and shear sense all affect the medium's permeability, creating substantial permeability anisotropies. Locally, these anisotropies are further enhanced by superposition of permeability changes of individual faults that constitute the fault system. We suggest the resulting permeability distribution model should be used as the initial permeability model for porous media in fractured reservoirs.
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Polyoxometalate-cyclodextrin supramolecular entities for real-time in situ monitoring of dopamine released from neuroblastoma cells(Biosensors & bioelectronics, Elsevier BV, 2023-03-23) [Article]Optimized and sensitive biomarker detection has recently been shown to have a critical impact on quality of diagnosis and medical care options. In this research study, polyoxometalate-γ-cyclodextrin metal-organic framework (POM-γCD MOF) was utilized as an electrocatalyst to fabricate highly selective sensors to detect in-situ released dopamine. The POM-γCD MOF produced multiple modes of signals for dopamine including electrochemical, colorimetric, and smartphone read-outs. Real-time quantitative monitoring of SH-SY5Y neuroblastoma cellular dopamine production was successfully demonstrated under various stimuli at different time intervals. The POM-CD MOF sensor and linear regression model were used to develop a smartphone read-out platform, which converts dopamine visual signals to digital signals within a few seconds. Ultimately, POM-γCD MOFs can play a significant role in the diagnosis and treatment of various diseases that involve dopamine as a significant biomarker.
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Experimental Assessment on the Coupling Effect of Mixing Length and Methane-Ammonia Blends on Flame Stability and Emissions(Energies, MDPI AG, 2023-03-23) [Article]Lean premixed combustion mode has become attractive for utilization in industrial gas turbines due to its ability to meet strict emissions regulations without compromising engine efficiency. In this combustion mode, the mixing process is the key player that affect the flame structure and stability, as well as the generated emissions. Many studies have investigated the aspects that influence premixed flames, including the effects of turbulence, combustor geometry, and level of partial premixing, while mostly using conventional natural gas fuel represented by methane. Recently, ammonia, a sustainable energy source, has been considered in gas turbines due to its carbon-free fuel producing no CO2. Utilizing 100% ammonia or a blend of methane and ammonia alters the combustion performance of a premixed flame due to the variation associated with the physical and chemical properties of ammonia. Thus, investigating the coupling between blend ratios and mixing length of methane-ammonia on flame stability and emissions is an essential step toward implementing ammonia in industrial gas turbines. In this study, the influence of various methane-ammonia blends, from 0 (pure methane) to XNH3 = 75%, and mixing lengths on the flame performance were studied. The mixing length was altered by delaying the injection (i.e., partially premixing) of the ammonia while using a fixed injection location for the reference methane-air mixture. This was done by using three fuel ports located at three different heights upstream of the combustion chamber. The results showed that the flame stability is negatively influenced by increasing (decreasing) ammonia fraction (mixing length ratio) and is more sensitive to the ammonia fraction than to the mixing length. At a constant equivalence ratio, the CO and NOx performances improved positively by increasing the ammonia volume fractions (especially at XNH3 = 75% compared to XNH3 = 25% and 50%) and the mixing length.
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Giant Nonlinear Optical Response via Coherent Stacking of In-Plane Ferroelectric Layers(Advanced Materials, Wiley, 2023-03-23) [Article]Thin ferroelectric materials hold great promise for compact nonvolatile memory, nonlinear optical and optoelectronic devices. Herein, we report an ultrathin in-plane ferroelectric material that exhibits a giant nonlinear optical effect: group-IV monochalcogenide SnSe. Nanometer-scale ferroelectric domains with ∼90°/270° twin boundaries or ∼180° domain walls are revealed in physical vapor deposited SnSe by lateral piezoresponse force microscopy. Atomic structure characterization reveals both parallel and antiparallel stacking of neighboring van der Waals (vdW) ferroelectric layers, leading to ferroelectric or antiferroelectric ordering. Ferroelectric domains exhibit giant nonlinear optical activity due to coherent enhancement of second harmonic fields, and the as-resulted second-harmonic generation was observed to be 100 times more intense than monolayer WS2. This work demonstrates in-plane ferroelectric ordering and giant nonlinear optical activity in SnSe, which paves the way for applications in on-chip nonlinear optical components and nonvolatile memory devices.
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High-performance MTJ-based sensors for monitoring of atmospheric pollution(AIP Advances, AIP Publishing, 2023-03-23) [Article]Solid and liquid particles in the atmosphere, referred to as airborne particulate matter (PM), have been rising significantly over the past two decades. Exposure to PM carries significant health risks such as lungs damage, heart disease, cancer, and death. PM2.5 is a subgroup of PM particles that are smaller than 2.5 µm and is a major concern as it is more harmful to health and more difficult to detect. One problematic component of PM2.5 is magnetite nanoparticles (<200 nm), which are readily absorbed into the bloodstream through the respiratory system. Eventually, magnetite nanoparticles deposit inside the brain causing neurodegenerative diseases such as Alzheimer’s or cancerous tumors by inducing oxidative stress. Additionally, Magnetite nanoparticles are often surrounded by heavy metal nanoparticles such as Cadmium and lead which are a great concern to the environment and health. Traditional PM detection methods such as laser scattering are bulky, expensive, and incapable of detecting particles smaller than 200 nm such as magnetite nanoparticles. Therefore, developing a low-cost highly sensitive sensor for monitoring magnetite nanoparticles is vital. Tunneling Magneto-Resistance (TMR) sensors are an attractive option due to their low-cost and high sensitivity toward magnetic nanoparticle detection. Moreover, developing a cheap, portable, and precise remote monitoring technique will allow for the creation of high spatial resolution highly sensitive monitoring networks for magnetic PM2.5. This work focuses on developing, modeling, and simulation of low-cost highly sensitive TMR sensor based on Magnetic Tunnel Junction (MTJ) that can detect and count magnetite nanoparticles.