jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Haonan Zhang | Cheng Hao | Tongtong Fu | Dian Yu | Jane Y. Howe | Kaiwen Chen | Ning Yan | Hao Ren | Huimin Zhai
Source: Nano-Micro Letters (article, 2024-10-17)
Field: Materials Science — Materials Chemistry

Gradient-Layered MXene/Hollow Lignin Nanospheres Architecture Design for Flexible and Stretchable Supercapacitors With the rapid development of flexible wearable electronics, the demand for stretchable energy storage devices has surged. In this work, a novel gradient-layered architecture was design based on single-pore hollow lignin nanospheres (HLNPs)-intercalated two-dimensional transition metal carbide (Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene) for fabricating highly stretchable and durable supercapacitors. By depositing and inserting HLNPs in the MXene layers with a bottom-up decreasing gradient, a multilayered porous MXene structure with smooth ion channels was constructed by reducing the overstacking of MXene lamella. Moreover, the micro-chamber architecture of thin-walled lignin nanospheres effectively extended the contact area between lignin and MXene to improve ion and electron accessibility, thus better utilizing the pseudocapacitive property of lignin. All these strategies effectively enhanced the capacitive performance of the electrodes. In addition, HLNPs, which acted as a protective phase for MXene layer, enhanced mechanical properties of the wrinkled stretchable electrodes by releasing stress through slip and deformation during the stretch-release cycling and greatly improved the structural integrity and capacitive stability of the electrodes. Flexible electrodes and symmetric flexible all-solid-state supercapacitors capable of enduring 600% uniaxial tensile strain were developed with high specific capacitances of 1273 mF cm<sup>-2</sup> (241 F g<sup>-1</sup>) and 514 mF cm<sup>-2</sup> (95 F g<sup>-1</sup>), respectively. Moreover, their capacitances were well preserved after 1000 times of 600% stretch-release cycling. This study showcased new possibilities of incorporating biobased lignin nanospheres in energy storage devices to fabricate stretchable devices leveraging synergies among various two-dimensional nanomaterials. Materials science ; Supercapacitor ; MXenes ; Electrode ; Capacitive sensing ; Nanotechnology ; Energy storage ; Porosity ; Composite material ; Stretchable electronics ; Lignin ; Electrochemistry ; Electronics MXene and MAX Phase Materials ; Supercapacitor Materials and Fabrication ; Advanced Sensor and Energy Harvesting Materials
Authors: Shuiwen Zhu | Shunxin Wu | Yu Fu | Shuangxi Guo
Source: AIP Advances (article, 2024-04-01)
Field: Materials Science — Polymers and Plastics

Prediction of particle-reinforced composite material properties based on an improved Halpin–Tsai model This paper introduces an improved Halpin–Tsai model to predict the mechanical, thermal, and electrical properties of silicon-carbide-reinforced polypropylene composites. The model considers the influence of porosity and corresponding silicon-carbide volume fractions and derives relationships between material property shape factors and the aspect ratio, silicon-carbide volume fraction, and porosity. The improved model’s predictions exhibit errors of 4.00% for mechanical properties, 2.13% for thermal properties, and 2.24% for electrical properties when compared to finite element analysis. This study demonstrates that the improved Halpin–Tsai model can effectively predict the properties of silicon-carbide-reinforced polypropylene composites, aiding in the design and optimization of these materials. Composite number ; Materials science ; Composite material ; Particle (ecology) Natural Fiber Reinforced Composites ; Composite Material Mechanics ; Polymer Nanocomposites and Properties
Authors: Tabussam Tufail | Huma Bader Ul Ain | Jin Chen | Muhammad Safiullah Virk | Zahoor Ahmed | Jawad Ashraf | Noor Ul Ain Shahid | Bin Xu
Source: Foods (article, 2024-04-24)
Field: Chemistry — Organic Chemistry

Contemporary Views of the Extraction, Health Benefits, and Industrial Integration of Rice Bran Oil: A Prominent Ingredient for Holistic Human Health Globally, 50% of people consume rice (<i>Oryza sativa</i>), which is among the most abundant and extensively ingested cereal grains. Rice bran is a by-product of the cereal industry and is also considered a beneficial waste product of the rice processing industry. Rice bran oil (RBO) is created from rice bran (20-25 wt% in rice bran), which is the outermost layer of the rice kernel; has a lipid content of up to 25%; and is a considerable source of a plethora of bioactive components. The main components of RBO include high levels of fiber and phytochemicals, including vitamins, oryzanols, fatty acids, and phenolic compounds, which are beneficial to human health and well-being. This article summarizes the stabilization and extraction processes of rice bran oil from rice bran using different techniques (including solvent extraction, microwaving, ohmic heating, supercritical fluid extraction, and ultrasonication). Some studies have elaborated the various biological activities linked with RBO, such as antioxidant, anti-platelet, analgesic, anti-inflammatory, anti-thrombotic, anti-mutagenic, aphrodisiac, anti-depressant, anti-emetic, fibrinolytic, and cytotoxic activities. Due to the broad spectrum of biological activities and economic benefits of RBO, the current review article focuses on the extraction process of RBO, its bioactive components, and the potential health benefits of RBO. Furthermore, the limitations of existing studies are highlighted, and suggestions are provided for future applications of RBO as a functional food ingredient. Ingredient ; Rice bran oil ; Human health ; Active ingredient ; Health benefits ; Bran ; Extraction (chemistry) ; Traditional medicine ; Biotechnology ; Food science ; Biochemical engineering ; Biology ; Chemistry ; Medicine ; Engineering ; Environmental health ; Pharmacology ; Chromatography ; Organic chemistry Edible Oils Quality and Analysis ; Fatty Acid Research and Health ; Natural Products and Biological Research
Authors: Masoud Shafiei | Yousef Kazemzadeh | Mehdi Escrochi | Farid B. Cortés | Camilo A. Franco | Masoud Riazi
Source: Scientific Reports (review, 2024-03-29)
Field: Chemistry — Analytical Chemistry

A comprehensive review direct methods to overcome the limitations of gas injection during the EOR process Among the Enhanced Oil Recovery (EOR) methods, gas-based EOR methods are very popular all over the world. The gas injection has a high ability to increase microscopic sweep efficiency and can increase production efficiency well. However, it should be noted that in addition to all the advantages of these methods, they have disadvantages such as damage due to asphaltene deposition, unfavorable mobility ratio, and reduced efficiency of macroscopic displacement. In this paper, the gas injection process and its challenges were investigated. Then the overcoming methods of these challenges were investigated. To inhibit asphaltene deposition during gas injection, the use of nanoparticles was proposed, which were examined in two categories: liquid-soluble and gas-soluble, and the limitations of each were examined. Various methods were used to overcome the problem of unfavorable mobility ratio and their advantages and disadvantages were discussed. Gas-phase modification has the potential to reduce the challenges and limitations of direct gas injection and significantly increase recovery efficiency. In the first part, the introduction of gas injection and the enhanced oil recovery mechanisms during gas injection were mentioned. In the next part, the challenges of gas injection, which included unfavorable mobility ratio and asphaltene deposition, were investigated. In the third step, gas-phase mobility control methods investigate, emphasizing thickeners, thickening mechanisms, and field applications of mobility control methods. In the last part, to investigate the effect of nanoparticles on asphaltene deposition and reducing the minimum miscible pressure in two main subsets: 1- use of nanoparticles indirectly to prevent asphaltene deposition and reduce surface tension and 2- use of nanoparticles as a direct asphaltene inhibitor and Reduce MMP of the gas phase in crude oil was investigated. Asphaltene ; Enhanced oil recovery ; Deposition (geology) ; Materials science ; Nanoparticle ; Petroleum engineering ; Fossil fuel ; Gas phase ; Chemical engineering ; Process engineering ; Environmental science ; Nanotechnology ; Chemistry ; Organic chemistry ; Geology ; Engineering Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Igor V. Tetko | Ruud van Deursen | Guillaume Godin
Source: Journal of Cheminformatics (article, 2024-12-09)
Field: Materials Science — Materials Chemistry

Be aware of overfitting by hyperparameter optimization! Hyperparameter optimization is very frequently employed in machine learning. However, an optimization of a large space of parameters could result in overfitting of models. In recent studies on solubility prediction the authors collected seven thermodynamic and kinetic solubility datasets from different data sources. They used state-of-the-art graph-based methods and compared models developed for each dataset using different data cleaning protocols and hyperparameter optimization. In our study we showed that hyperparameter optimization did not always result in better models, possibly due to overfitting when using the same statistical measures. Similar results could be calculated using pre-set hyperparameters, reducing the computational effort by around 10,000 times. We also extended the previous analysis by adding a representation learning method based on Natural Language Processing of smiles called Transformer CNN. We show that across all analyzed sets using exactly the same protocol, Transformer CNN provided better results than graph-based methods for 26 out of 28 pairwise comparisons by using only a tiny fraction of time as compared to other methods. Last but not least we stressed the importance of comparing calculation results using exactly the same statistical measures.Scientific Contribution We showed that models with pre-optimized hyperparameters can suffer from overfitting and that using pre-set hyperparameters yields similar performances but four orders faster. Transformer CNN provided significantly higher accuracy compared to other investigated methods. Hyperparameter ; Overfitting ; Computer science ; Hyperparameter optimization ; Machine learning ; Artificial intelligence ; Pairwise comparison ; Graph ; Random forest ; Artificial neural network ; Theoretical computer science ; Support vector machine Machine Learning in Materials Science ; Machine Learning and Data Classification ; Computational Drug Discovery Methods
Authors: Junyi Ji | Guoliang Yu | Changsong Xu | Hongjun Xiang
Source: Nature Communications (article, 2024-01-02)
Field: Materials Science — Materials Chemistry

Fractional quantum ferroelectricity For an ordinary ferroelectric, the magnitude of the spontaneous electric polarization is at least one order of magnitude smaller than that resulting from the ionic displacement of the lattice vectors, and the direction of the spontaneous electric polarization is determined by the point group of the ferroelectric. Here, we introduce a new class of ferroelectricity termed Fractional Quantum Ferroelectricity. Unlike ordinary ferroelectrics, the polarization of Fractional Quantum Ferroelectricity arises from substantial atomic displacements that are comparable to lattice constants. Applying group theory analysis, we identify 28 potential point groups that can realize Fractional Quantum Ferroelectricity, including both polar and non-polar groups. The direction of polarization in Fractional Quantum Ferroelectricity is found to always contradict with the symmetry of the "polar" phase, which violates Neumann's principle, challenging conventional symmetry-based knowledge. Through the Fractional Quantum Ferroelectricity theory and density functional calculations, we not only explain the puzzling experimentally observed in-plane polarization of monolayer α-In<sub>2</sub>Se<sub>3</sub>, but also predict polarization in a cubic compound of AgBr. Our findings unveil a new realm of ferroelectric behavior, expanding the understanding and application of these materials beyond the limits of traditional ferroelectrics. Ferroelectricity ; Condensed matter physics ; Polarization density ; Polarization (electrochemistry) ; Physics ; Quantum ; Quantum mechanics ; Dielectric ; Chemistry Ferroelectric and Piezoelectric Materials ; 2D Materials and Applications ; Ferroelectric and Negative Capacitance Devices
Authors: Milan Avila Clasen | Max Ruwolt | Cong Wang | Julia Ruta | Boris Bogdanow | Louise Ulrich Kurt | Zehong Zhang | Shuai Wang | Fábio C. Gozzo | Tao Chen | Paulo C. Carvalho | Diogo Borges Lima | Fan Liu
Source: Nature Methods (article, 2024-10-31)
Field: Chemistry — Spectroscopy

Proteome-scale recombinant standards and a robust high-speed search engine to advance cross-linking MS-based interactomics Advancing data analysis tools for proteome-wide cross-linking mass spectrometry (XL-MS) requires ground-truth standards that mimic biological complexity. Here we develop well-controlled XL-MS standards comprising hundreds of recombinant proteins that are systematically mixed for cross-linking. We use one standard dataset to guide the development of Scout, a search engine for XL-MS with MS-cleavable cross-linkers. Using other, independent standard datasets and published datasets, we benchmark the performance of Scout and existing XL-MS software. We find that Scout offers an excellent combination of speed, sensitivity and false discovery rate control. The results illustrate how our large recombinant standard can support the development of XL-MS analysis tools and evaluation of XL-MS results. Benchmark (surveying) ; Proteome ; Computer science ; False discovery rate ; Recombinant DNA ; Data mining ; Computational biology ; Scale (ratio) ; Software ; Sensitivity (control systems) ; Bioinformatics ; Chemistry ; Biology ; Engineering ; Operating system ; Biochemistry Advanced Proteomics Techniques and Applications ; Computational Drug Discovery Methods ; Bioinformatics and Genomic Networks
Authors: Jens Pogorzelski | Ludwig Horsthemke | Jonas Homrighausen | Dennis Stiegekötter | Markus Gregor | Peter Glösekötter
Source: Sensors (article, 2024-01-24)
Field: Materials Science — Materials Chemistry

Compact and Fully Integrated LED Quantum Sensor Based on NV Centers in Diamond Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in diamond nano or microcrystals is a promising technology for sensitive, integrated magnetic-field sensors. Currently, this technology is still cost-intensive and mainly found in research. Here we propose one of the smallest fully integrated quantum sensors to date based on nitrogen vacancy (NV) centers in diamond microcrystals. It is an extremely cost-effective device that integrates a pump light source, photodiode, microwave antenna, filtering and fluorescence detection. Thus, the sensor offers an all-electric interface without the need to adjust or connect optical components. A sensitivity of 28.32nT/Hz and a theoretical shot noise limited sensitivity of 2.87 nT/Hz is reached. Since only generally available parts were used, the sensor can be easily produced in a small series. The form factor of (6.9 × 3.9 × 15.9) mm3 combined with the integration level is the smallest fully integrated NV-based sensor proposed so far. With a power consumption of around 0.1W, this sensor becomes interesting for a wide range of stationary and handheld systems. This development paves the way for the wide usage of quantum magnetometers in non-laboratory environments and technical applications. Magnetometer ; Quantum sensor ; Diamond ; Optoelectronics ; Microwave ; Sensitivity (control systems) ; Photodiode ; Materials science ; Quantum ; Computer science ; Physics ; Electrical engineering ; Magnetic field ; Electronic engineering ; Quantum computer ; Telecommunications ; Quantum network ; Engineering Diamond and Carbon-based Materials Research ; High-pressure geophysics and materials ; Carbon Nanotubes in Composites
Authors: Véronique Sauvé | Eric Stefan | Nathalie Croteau | Thomas Goiran | Rayan Fakih | Nupur Bansal | Adelajda Hadzipasic | Jing Fang | Paramasivam Murugan | Shimin Chen | Edward A. Fon | Warren D. Hirst | Laura Silvian | Jean‐François Trempe | Kalle Gehring
Source: Nature Communications (article, 2024-09-19)
Field: Materials Science — Biomaterials

Activation of parkin by a molecular glue Mutations in parkin and PINK1 cause early-onset Parkinson's disease (EOPD). The ubiquitin ligase parkin is recruited to damaged mitochondria and activated by PINK1, a kinase that phosphorylates ubiquitin and the ubiquitin-like domain of parkin. Activated phospho-parkin then ubiquitinates mitochondrial proteins to target the damaged organelle for degradation. Here, we present the mechanism of activation of a new class of small molecule allosteric modulators that enhance parkin activity. The compounds act as molecular glues to enhance the ability of phospho-ubiquitin (pUb) to activate parkin. Ubiquitination assays and isothermal titration calorimetry with the most active compound (BIO-2007817) identify the mechanism of action. We present the crystal structure of a closely related compound (BIO-1975900) bound to a complex of parkin and two pUb molecules. The compound binds next to pUb on RING0 and contacts both proteins. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) experiments confirm that activation occurs through release of the catalytic Rcat domain. In organello and mitophagy assays demonstrate that BIO-2007817 partially rescues the activity of parkin EOPD mutants, R42P and V56E, offering a basis for the design of activators as therapeutics for Parkinson's disease. Parkin ; GLUE ; Computational biology ; Chemistry ; Computer science ; Biology ; Medicine ; Materials science ; Disease ; Pathology ; Parkinson's disease biodegradable polymer synthesis and properties ; Click Chemistry and Applications ; Parkinson's Disease Mechanisms and Treatments
Authors: Zhen Ji | Zhiyi Li | Liyao Liu | Ye Zou | Chong‐an Di | Daoben Zhu
Source: Advanced Materials Technologies (article, 2024-03-26)
Field: Materials Science — Materials Chemistry

Organic Thermoelectric Devices for Energy Harvesting and Sensing Applications Abstract The rise of artificial intelligence and the Internet of Things have spurred an increasing demand for wearable, sustainable, and maintenance‐free power sources. Organic thermoelectric (OTE) devices are emerged as promising candidates because they are capable of converting heat energy into electricity directly without the need of moving parts, capable of flexible and seamless integration with multifunctional miniaturized electronics. In addition, OTE devices can perform straightforward as various self‐powered sensors, boosting their applications in the field of intelligent interactions. This review focuses on recent advances in OTE materials and devices for applications in energy harvesting and sensing. The basic knowledge and key parameters of OTE materials and devices are presented, followed by detailed introduction of recent progress of OTE generators, sensors, and other OTE‐integrated devices. Next, several aspects of optimizing OTE devices toward multifunctional applications are highlighted. Finally, an overview of the current challenges and future research directions of OTE‐based devices is addressed. It is hoped that this review can pave the way for speeding up a bright future for the development and practical applications of OTE devices. Energy harvesting ; Electronics ; Computer science ; Wearable technology ; Electricity ; Wearable computer ; Systems engineering ; Nanotechnology ; Electrical engineering ; Energy (signal processing) ; Engineering ; Materials science ; Embedded system Advanced Thermoelectric Materials and Devices ; Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Manuel Matzinger | Anna Schmücker | Ramesh Yelagandula | Karel Stejskal | Gabriela Krššáková | Frédéric Berger | Karl Mechtler | Rupert L. Mayer
Source: Nature Communications (article, 2024-02-03)
Field: Chemistry — Spectroscopy

Micropillar arrays, wide window acquisition and AI-based data analysis improve comprehensiveness in multiple proteomic applications Comprehensive proteomic analysis is essential to elucidate molecular pathways and protein functions. Despite tremendous progress in proteomics, current studies still suffer from limited proteomic coverage and dynamic range. Here, we utilize micropillar array columns (µPACs) together with wide-window acquisition and the AI-based CHIMERYS search engine to achieve excellent proteomic comprehensiveness for bulk proteomics, affinity purification mass spectrometry and single cell proteomics. Our data show that µPACs identify ≤50% more peptides and ≤24% more proteins, while offering improved throughput, which is critical for large (clinical) proteomics studies. Combining wide precursor isolation widths of m/z 4-12 with the CHIMERYS search engine identified +51-74% and +59-150% more proteins and peptides, respectively, for single cell, co-immunoprecipitation, and multi-species samples over a conventional workflow at well-controlled false discovery rates. The workflow further offers excellent precision, with CVs <7% for low input bulk samples, and accuracy, with deviations <10% from expected fold changes for regular abundance two-proteome mixes. Compared to a conventional workflow, our entire optimized platform discovered 92% more potential interactors in a protein-protein interaction study on the chromatin remodeler Smarca5/Snf2h. These include previously described Smarca5 binding partners and undescribed ones including Arid1a, another chromatin remodeler with key roles in neurodevelopmental and malignant disorders. Computer science ; Window (computing) ; Computational biology ; Biology ; World Wide Web Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Advanced Biosensing Techniques and Applications