jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Adegoke Isiaka Adetunji | Mariana Erasmus
Source: Polymers (review, 2024-05-08)
Field: Materials Science — Biomaterials

Green Synthesis of Bioplastics from Microalgae: A State-of-the-Art Review The synthesis of conventional plastics has increased tremendously in the last decades due to rapid industrialization, population growth, and advancement in the use of modern technologies. However, overuse of these fossil fuel-based plastics has resulted in serious environmental and health hazards by causing pollution, global warming, etc. Therefore, the use of microalgae as a feedstock is a promising, green, and sustainable approach for the production of biobased plastics. Various biopolymers, such as polyhydroxybutyrate, polyurethane, polylactic acid, cellulose-based polymers, starch-based polymers, and protein-based polymers, can be produced from different strains of microalgae under varying culture conditions. Different techniques, including genetic engineering, metabolic engineering, the use of photobioreactors, response surface methodology, and artificial intelligence, are used to alter and improve microalgae stocks for the commercial synthesis of bioplastics at lower costs. In comparison to conventional plastics, these biobased plastics are biodegradable, biocompatible, recyclable, non-toxic, eco-friendly, and sustainable, with robust mechanical and thermoplastic properties. In addition, the bioplastics are suitable for a plethora of applications in the agriculture, construction, healthcare, electrical and electronics, and packaging industries. Thus, this review focuses on techniques for the production of biopolymers and bioplastics from microalgae. In addition, it discusses innovative and efficient strategies for large-scale bioplastic production while also providing insights into the life cycle assessment, end-of-life, and applications of bioplastics. Furthermore, some challenges affecting industrial scale bioplastics production and recommendations for future research are provided. Bioplastic ; Biopolymer ; Environmentally friendly ; Polyhydroxybutyrate ; Biochemical engineering ; Biorefining ; Polyhydroxyalkanoates ; Raw material ; Materials science ; Biotechnology ; Environmental science ; Waste management ; Engineering ; Biorefinery ; Biofuel ; Polymer ; Chemistry ; Organic chemistry biodegradable polymer synthesis and properties ; Algal biology and biofuel production ; Enzyme Catalysis and Immobilization
Authors: Mahendra Kumar Sahu | Amit Kumar Nayak | Bisrat Hailemeskel | Ozan Emre Eyüpoğlu
Source: International Journal Of Pharmaceutical Research And Allied Sciences (article, 2024-01-01)
Field: Chemistry — Organic Chemistry

Exploring Recent Updates on Molecular Docking: Types, Method, Application, Limitation &amp;amp; Future Prospects Molecular docking serves as a crucial computational tool in the realm of drug discovery and development, aimed at understanding the interactions between small molecules and target proteins. This study delves into the objective of elucidating the evolution of molecular docking techniques, their current applications, and potential future directions. Through a comprehensive review of the literature and analysis of recent advancements, this study provides insights into the methodologies employed in Docking (animal) ; Computer science ; Computational biology ; Biochemical engineering ; Data science ; Biology ; Engineering ; Medicine Click Chemistry and Applications ; Computational Drug Discovery Methods ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Chao Qian | Yuetian Jia | Zhedong Wang | Jieting Chen | Pujing Lin | Xiaoyue Zhu | Er‐Ping Li | Hongsheng Chen
Source: Advanced Photonics (article, 2024-01-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Autonomous aeroamphibious invisibility cloak with stochastic-evolution learning Being invisible ad libitum has long captivated the popular imagination, particularly in terms of safeguarding modern high-end instruments from potential threats. Decades ago, the advent of metamaterials and transformation optics sparked considerable interest in invisibility cloaks, which have been mainly demonstrated in ground and waveguide modalities. However, an omnidirectional flying cloak has not been achieved, primarily due to the challenges associated with dynamic synthesis of metasurface dispersion. We demonstrate an autonomous aeroamphibious invisibility cloak that incorporates a suite of perception, decision, and execution modules, capable of maintaining invisibility amidst kaleidoscopic backgrounds and neutralizing external stimuli. The physical breakthrough lies in the spatiotemporal modulation imparted on tunable metasurfaces to sculpt the scattering field in both space and frequency domains. To intelligently control the spatiotemporal metasurfaces, we introduce a stochastic-evolution learning that automatically aligns with the optimal solution through maximum probabilistic inference. In a fully self-driving experiment, we implement this concept on an unmanned drone and showcase adaptive invisibility in three canonical landscapes—sea, land, and air—with a similarity rate of up to 95%. Our work extends the family of invisibility cloaks to flying modality and inspires other research on material discoveries and homeostatic meta-devices. Invisibility ; Cloak ; Computer science ; Metamaterial ; Cloaking ; Field (mathematics) ; Artificial intelligence ; Human–computer interaction ; Physics ; Optics ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies
Authors: Lidan Zhang | Zhou Chen | Bofeng Liu | Yimin Ding | Hyun-Ju Ahn | Shengyuan Chang | Yao Duan | Md Tarek Rahman | Tunan Xia | Xi Chen | Zhiwen Liu | Xingjie Ni
Source: Science Advances (article, 2024-09-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Real-time machine learning–enhanced hyperspectro-polarimetric imaging via an encoding metasurface Light fields carry a wealth of information, including intensity, spectrum, and polarization. However, standard cameras capture only the intensity, disregarding other valuable information. While hyperspectral and polarimetric imaging systems capture spectral and polarization information, respectively, in addition to intensity, they are often bulky, slow, and costly. Here, we have developed an encoding metasurface paired with a neural network enabling a normal camera to acquire hyperspectro-polarimetric images from a single snapshot. Our experimental results demonstrate that this metasurface-enhanced camera can accurately resolve full-Stokes polarization across a broad spectral range (700 to 1150 nanometer) from a single snapshot, achieving a spectral sensitivity as high as 0.23 nanometer. In addition, our system captures full-Stokes hyperspectro-polarimetric video in real time at a rate of 28 frames per second, primarily limited by the camera's readout rate. Our encoding metasurface offers a compact, fast, and cost-effective solution for multidimensional imaging that effectively uses information within light fields. Hyperspectral imaging ; Polarimetry ; Snapshot (computer storage) ; Stokes parameters ; Computer science ; Polarization (electrochemistry) ; Optics ; Frame rate ; Spectral imaging ; Artificial intelligence ; High-dynamic-range imaging ; Physics ; Computer vision ; Dynamic range ; High dynamic range ; Scattering Metamaterials and Metasurfaces Applications ; Optical Polarization and Ellipsometry ; Random lasers and scattering media
Authors: Minhye Kim | Myeongyeon Shin | Yaping Zhao | Mrinmoy Ghosh | Young‐Ok Son
Source: Small Science (article, 2024-09-17)
Field: Materials Science — Biomaterials

Transformative Impact of Nanocarrier‐Mediated Drug Delivery: Overcoming Biological Barriers and Expanding Therapeutic Horizons Advancing therapeutic progress is centered on developing drug delivery systems (DDS) that control therapeutic molecule release, ensuring precise targeting and optimal concentrations. Targeted DDS enhances treatment efficacy and minimizes off-target effects, but struggles with drug degradation. Over the last three decades, nanopharmaceuticals have evolved from laboratory concepts into clinical products, highlighting the profound impact of nanotechnology in medicine. Despite advancements, the effective delivery of therapeutics remains challenging because of biological barriers. Nanocarriers offer a solution with a small size, high surface-to-volume ratios, and customizable properties. These systems address physiological and biological challenges, such as shear stress, protein adsorption, and quick clearance. They allow targeted delivery to specific tissues, improve treatment outcomes, and reduce adverse effects. Nanocarriers exhibit controlled release, decreased degradation, and enhanced efficacy. Their size facilitates cell membrane penetration and intracellular delivery. Surface modifications increase affinity for specific cell types, allowing precise treatment delivery. This study also elucidates the potential integration of artificial intelligence with nanoscience to innovate future nanocarrier systems. Nanocarriers ; Transformative learning ; Drug delivery ; Drug ; New horizons ; Targeted drug delivery ; Medicine ; Nanotechnology ; Pharmacology ; Psychology ; Materials science ; Engineering Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; RNA Interference and Gene Delivery
Authors: Md. Toukir Ahmed | Ocean Monjur | Mohammed Kamruzzaman
Source: Journal of Food Engineering (preprint, 2024-07-09)
Field: Chemistry — Analytical Chemistry

Deep learning-based hyperspectral image reconstruction for quality assessment of agro-product Hyperspectral imaging (HSI) has recently emerged as a promising tool for many agricultural applications; however, the technology cannot be directly used in real-time for immediate decision-making and actions due to the extensive time needed to capture, process, and analyze large volumes of data. Consequently, the development of a simple, compact, and cost-effective imaging system is not possible with the current HSI systems. Therefore, the overall goal of this study was to reconstruct hyperspectral images from RGB images through deep learning for agricultural applications. Specifically, this study used Hyperspectral Convolutional Neural Network - Dense (HSCNN-D) to reconstruct hyperspectral images from RGB images for predicting soluble solid content (SSC) in sweet potatoes. The algorithm reconstructed the hyperspectral images from RGB images, with the resulting spectra closely matching the ground-truth. The partial least squares regression (PLSR) model based on reconstructed spectra outperformed the model using the full spectral range, demonstrating its potential for SSC prediction in sweet potatoes. These findings highlight the potential of deep learning-based hyperspectral image reconstruction as a low-cost, efficient tool for various agricultural uses. Hyperspectral imaging ; Artificial intelligence ; RGB color model ; Computer science ; Convolutional neural network ; Deep learning ; Partial least squares regression ; Pattern recognition (psychology) ; Ground truth ; Iterative reconstruction ; Artificial neural network ; Precision agriculture ; Computer vision ; Remote sensing ; Machine learning ; Geography ; Agriculture Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Advanced Chemical Sensor Technologies
Authors: Taigao Ma | Haozhu Wang | L. Jay Guo
Source: Opto-Electronic Advances (article, 2024-01-01)
Field: Materials Science — Surfaces, Coatings and Films

OptoGPT: A foundation model for inverse design in optical multilayer thin film structures Optical multilayer thin film structures have been widely used in numerous photonic applications. However, existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets, or are difficult to suit for different types of structures, e.g., designing for different materials at each layer. These methods also cannot accommodate versatile design situations under different angles and polarizations. In addition, how to benefit practical fabrications and manufacturing has not been extensively considered yet. In this work, we introduce OptoGPT (Opto Generative Pretrained Transformer), a decoder-only transformer, to solve all these drawbacks and issues simultaneously. Foundation (evidence) ; Inverse ; Materials science ; Computer science ; Engineering ; Mathematics ; Geometry ; Political science Optical Coatings and Gratings ; Thermal Radiation and Cooling Technologies ; Photonic Crystals and Applications
Authors: Siavash Iravani | Navid Rabiee | Pooyan Makvandi
Source: Journal of Materials Chemistry B (review, 2024-01-01)
Field: Materials Science — Materials Chemistry

Advancements in MXene-based composites for electronic skins MXenes are a class of two-dimensional (2D) materials that have gained significant attention in the field of electronic skins (E-skins). MXene-based composites offer several advantages for E-skins, including high electrical conductivity, mechanical flexibility, transparency, and chemical stability. Their mechanical flexibility allows for conformal integration onto various surfaces, enabling the creation of E-skins that can closely mimic human skin. In addition, their high surface area facilitates enhanced sensitivity and responsiveness to external stimuli, making them ideal for sensing applications. Notably, MXene-based composites can be integrated into E-skins to create sensors that can detect various stimuli, such as temperature, pressure, strain, and humidity. These sensors can be used for a wide range of applications, including health monitoring, robotics, and human-machine interfaces. However, challenges related to scalability, integration, and biocompatibility need to be addressed. One important challenge is achieving long-term stability under harsh conditions such as high humidity. MXenes are susceptible to oxidation, which can degrade their electrical and mechanical properties over time. Another crucial challenge is the scalability of MXene synthesis, as large-scale production methods need to be developed to meet the demand for commercial applications. Notably, the integration of MXenes with other components, such as energy storage devices or flexible electronics, requires further developments to ensure compatibility and optimize overall performance. By addressing issues related to material stability, mechanical flexibility, scalability, sensing performance, and power supply, MXene-based E-skins can develop the fields of healthcare monitoring/diagnostics, prosthetics, motion monitoring, wearable electronics, and human-robot interactions. The integration of MXenes with emerging technologies, such as artificial intelligence or internet of things, can unlock new functionalities and applications for E-skins, ranging from healthcare monitoring to virtual reality interfaces. This review aims to examine the challenges, advantages, and limitations of MXenes and their composites in E-skins, while also exploring the future prospects and potential advancements in this field. MXenes ; Materials science ; Composite material ; Composite number ; Nanotechnology MXene and MAX Phase Materials ; Advanced Memory and Neural Computing ; Energy Harvesting in Wireless Networks
Authors: Weipeng Chen | Shunda Qiao | Ying He | Jie Zhu | Kang Wang | Lei Qi | Sheng Zhou | Limin Xiao | Yufei Ma
Source: Photoacoustics (article, 2024-02-09)
Field: Chemistry — Spectroscopy

Mid-infrared all-fiber light-induced thermoelastic spectroscopy sensor based on hollow-core anti-resonant fiber In this article, a mid-infrared all-fiber light-induced thermoelastic spectroscopy (LITES) sensor based on a hollow-core anti-resonant fiber (HC-ARF) was reported for the first time. The HC-ARF was applied as a light transmission medium and gas chamber. The constructed all-fiber structure has merits of low loss, easy optical alignment, good system stability, reduced sensor size and cost. The mid-infrared transmission structure can be utilized to target the strongest gas absorption lines. The reversely-tapered SM1950 fiber and the HC-ARF were spatially butt-coupled with a V-shaped groove between the two fibers to facilitate gas entry. Carbon monoxide (CO) with an absorption line at 4291.50 cm<sup>-1</sup> (2.33 µm) was chosen as the target gas to verify the sensing performance. The experimental results showed that the all-fiber LITES sensor based on HC-ARF had an excellent linear response to CO concentration. Allan deviation analysis indicated that the system had excellent long-term stability. A minimum detection limit (MDL) of 3.85 ppm can be obtained when the average time was 100 s. Materials science ; Optical fiber ; Core (optical fiber) ; Fiber ; Allan variance ; Infrared ; Spectroscopy ; Thermoelastic damping ; Infrared spectroscopy ; Optics ; Fiber optic sensor ; Absorption (acoustics) ; Carbon monoxide ; Optoelectronics ; Composite material ; Chemistry ; Standard deviation ; Physics Spectroscopy and Laser Applications ; Advanced Fiber Laser Technologies ; Photonic and Optical Devices
Authors: Setianto Setianto | Liu Kin Men | Ayi Bahtiar | Camellia Panatarani | I Made Joni
Source: Scientific Reports (article, 2024-01-23)
Field: Materials Science — Materials Chemistry

Carbon quantum dots with honeycomb structure: a novel synthesis approach utilizing cigarette smoke precursors This study presents a novel approach to synthesizing honeycomb carbon quantum dots (CQDs) from cigarette smoke by a hydrothermal process. A comprehensive characterization of these CQDs, conducted through high-resolution transmission electron microscopy (HRTEM), showcases their unique honeycomb structure, with an average particle size of 6.3 nm. Photoluminescence (PL) in CQDs is a captivating phenomenon where these nanoscale carbon structures emit strong blue luminescence at 461 nm upon exposure to ultraviolet light, with their excitation peak occurring at 380 nm. Fourier Transform Infrared (FTIR) analysis also identifies specific functional groups within the CQDs, offering valuable insights into the mechanisms governing their photoluminescence. Analysis of excitation spectra indicates the presence of both aromatic C=C bonds at 254 nm and C-O bonds from 280 to 420 nm. Carbon quantum dots ; Quantum dot ; Honeycomb ; Cigarette smoke ; Smoke ; Carbon fibers ; Honeycomb structure ; Nanotechnology ; Materials science ; Chemistry ; Biology ; Composite material ; Toxicology ; Organic chemistry Carbon and Quantum Dots Applications ; Luminescence and Fluorescent Materials ; Nanocluster Synthesis and Applications
Authors: Kush G. Patel | Ryan K. Maynard | Lawrence S. Ferguson | Michael L. Broich | Joshua C. Bledsoe | Caitlin C. Wood | Grant Crane | Jessica A. Bramhall | Jonathan M. Rust | Amanda M. Williams-Rhaesa | Jason Locklin
Source: ACS Sustainable Chemistry & Engineering (article, 2024-02-01)
Field: Materials Science — Biomaterials

Experimentally Determined Hansen Solubility Parameters of Biobased and Biodegradable Polyesters Hansen solubility parameters (HSP) of 15 commercially relevant biobased and biodegradable polyesters were experimentally determined by applying a novel approach to the classic solubility study method. In this approach, the extent of swelling in polymer films was determined using a simple equation based on the mass difference between swollen and nonswollen film samples to obtain normalized solvent uptake (<b><i>N</i></b>). Using <b><i>N</i></b> and HSPiP software, highly accurate HSP values were obtained for all 15 polyesters. Qualitative evaluation of the HSP values was conducted by predicting the miscibility of poly(3-hydroxybutyrate-<i>co</i>-3-hydroxyhexanoate) (PHB-<i>co</i>-HHx, 7 mol % HHx) and poly(lactic acid) (PLA) with a novel lignin-based plasticizer (ethyl 3-(4-ethoxy-3-methoxyphenyl)propanoate, EP) with a relative energy difference (RED) less than 0.4. Additionally, an HSP-predicted plasticizer (di(2-ethylhexyl) adipate, DA) with a larger RED (>0.7) was used to demonstrate the effects of less-miscible additives. Plasticized samples were analyzed by differential scanning calorimetry and polarized optical microscopy (POM) to determine the <i>T</i><sub>g</sub> depression, with EP showing linear <i>T</i><sub>g</sub> depression up to 50% plasticizer loading, whereas DA shows minimal <i>T</i><sub>g</sub> depression past 10% loading. Further analysis by POM reveals that the DA phase separates from both polymers at loadings as low as 2.5% (PHB-<i>co</i>-HHx, 7 mol % HHx) and 5% (PLA), while the EP phase separates at a much higher loading of 50% (PHB-<i>co</i>-HHx, 7 mol% HHx) and 30% (PLA). Plasticizer ; Miscibility ; Differential scanning calorimetry ; Hildebrand solubility parameter ; Solubility ; Polyester ; Chemistry ; Adipate ; Polymer chemistry ; Polymer ; Chemical engineering ; Materials science ; Organic chemistry ; Thermodynamics biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Polymer crystallization and properties
Authors: Weiwei Zhang | Shibo Li | Xiachen Fan | Xuejin Zhang | Shukai Fan | Guoping Bei
Source: Carbon Energy (article, 2024-09-12)
Field: Materials Science — Materials Chemistry

Two‐dimensional carbonitride MXenes: From synthesis to properties and applications Abstract Carbonitride MXenes, such as Ti 3 CNT x , Ti 2 C 0.5 N 0.5 T x , and Ti 4 (C 0.2 N 0.8 ) 3 T x , have attracted much interest in the large family of two‐dimensional (2D) nanomaterials. Like their carbide MXene counterparts, the nanolayered structure and functional groups endow carbonitride MXenes with an attractive combination of physical and chemical properties. More interestingly, the replacement of C by N changes the lattice parameters and electron distribution of carbonitride MXenes due to the greater electronegativity of N as compared to C, thus resulting in significantly enhanced functional properties. This paper reviews the development of carbonitride MXenes, the preparation of 2D carbonitride MXenes, and the current understanding of the microstructure, electronic structure, and functional properties of carbonitride MXenes. In addition, applications, especially in energy storage, sensors, catalysts, electromagnetic wave shielding and absorption, fillers, and environmental and biomedical fields, are summarized. Finally, their current limitations and future opportunities are presented. MXenes ; Computer science ; Materials science ; Nanotechnology MXene and MAX Phase Materials ; 2D Materials and Applications ; Graphene research and applications