jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhanpeng Sun | Dongliang Zhang | Zijun Qi | Qijun Wang | Xiang Sun | Kang Liang | Fang Dong | Yuan Zhao | Diwei Zou | Lijie Li | Gai Wu | Wei Shen | Sheng Liu
Source: ACS Applied Materials & Interfaces (article, 2024-06-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Insight into Interfacial Heat Transfer of β-Ga<sub>2</sub>O<sub>3</sub>/Diamond Heterostructures via the Machine Learning Potential β-Ga<sub>2</sub>O<sub>3</sub> is an ultrawide-band gap semiconductor with excellent potential for high-power and ultraviolet optoelectronic device applications. Low thermal conductivity is one of the major obstacles to enable the full performance of β-Ga<sub>2</sub>O<sub>3</sub>-based devices. A promising solution for this problem is to integrate β-Ga<sub>2</sub>O<sub>3</sub> with a diamond heat sink. However, the thermal properties of the β-Ga<sub>2</sub>O<sub>3</sub>/diamond heterostructures after the interfacial bonding have not been studied extensively, which are influenced by the crystal orientations and interfacial atoms for the β-Ga<sub>2</sub>O<sub>3</sub> and diamond interfaces. In this work, molecular dynamics simulations based on machine learning potential have been adopted to investigate the crystal-orientation-dependent and interfacial-atom-dependent thermal boundary resistance (TBR) of the β-Ga<sub>2</sub>O<sub>3</sub>/diamond heterostructure after interfacial bonding. The differences in TBR at different interfaces are explained in detail through the explorations of thermal conductivity value, thermal conductivity spectra, vibration density of states, and interfacial structures. Based on the above explorations, a further understanding of the influence of different crystal orientations and interfacial atoms on the β-Ga<sub>2</sub>O<sub>3</sub>/diamond heterostructure was achieved. Finally, insightful optimization strategies have been proposed in the study, which could pave the way for better thermal design and management of β-Ga<sub>2</sub>O<sub>3</sub>/diamond heterostructures according to guidance in the selection of the crystal orientations and interfacial atoms of the β-Ga<sub>2</sub>O<sub>3</sub> and diamond interfaces. Materials science ; Heterojunction ; Diamond ; Thermal conductivity ; Semiconductor ; Crystal (programming language) ; Heat sink ; Optoelectronics ; Nanotechnology ; Chemical physics ; Composite material ; Thermodynamics Ga2O3 and related materials ; Electronic and Structural Properties of Oxides ; Semiconductor materials and devices
Authors: Jun Yuan | Duo Pan | Junxiang Chen | Yangjie Liu | Jiaqi Yu | Xiangyun Hu | Hongbing Zhan | Zhenhai Wen
Source: Advanced Materials (article, 2024-11-05)
Field: Materials Science — Materials Chemistry

Ultrafast Na‐Ion Storage in Amorphization Engineered Hollow Vanadium Oxide/MXene Nanohybrids for High‐Performance Sodium‐Ion Hybrid Capacitors Sodium ion hybrid capacitors (SIHCs) address the high power and energy requirements in energy storage devices but face significant challenges arising from the slow kinetics and cycling instability of the anode side. Introducing atomic disorder and employing structural engineering in anode materials proves to be effective strategies for achieving rapid charge storage. Here, it is demonstrated that N-doped MXene encapsulated amorphous vanadium oxide hollow spheres (VO<sub>x</sub>@N-MXene HSs) offer multidirectional open pathways and sufficient vacancies, enabling reversible and fast Na<sup>+</sup> insertion/extraction. Machine learning potentials, coupled with molecular simulation techniques, confirm the presence of more abundant pores within the amorphous vanadium oxide (VO<sub>x</sub>) structure. The simulation of the charging/discharging process elucidates the authentic reaction path and structural evolutions of the VO<sub>x</sub>@N-MXene HSs, providing sufficient insight into the atomic-scale mechanisms associated with these structural superiorities. The full SIHCs devices demonstrate a high energy density of 198.3 Wh kg<sup>-1</sup>, along with a long-term cycling lifespan of 8000 cycles. This study offers valuable strategies into the intricate design and exploration of amorphous electrodes, contributing to the advancement of next-generation electrochemical energy devices. Materials science ; Anode ; Vanadium oxide ; Amorphous solid ; Vanadium ; Energy storage ; Electrochemistry ; Capacitor ; Oxide ; Nanotechnology ; Ion ; Chemical engineering ; Electrode ; Voltage ; Power (physics) ; Electrical engineering ; Physical chemistry ; Metallurgy ; Crystallography MXene and MAX Phase Materials ; Advancements in Battery Materials ; Supercapacitor Materials and Fabrication
Authors: Vladislav S. Tuchin | Evgeniia A. Stepanidenko | Anna A. Vedernikova | Sergei A. Cherevkov | Di Li | Lei Li | Aaron Döring | Michal Otyepka | Elena V. Ushakova | Andrey L. Rogach
Source: Small (article, 2024-02-11)
Field: Materials Science — Materials Chemistry

Optical Properties Prediction for Red and Near‐Infrared Emitting Carbon Dots Using Machine Learning Functional nanostructures build up a basis for the future materials and devices, providing a wide variety of functionalities, a possibility of designing bio-compatible nanoprobes, etc. However, development of new nanostructured materials via trial-and-error approach is obviously limited by laborious efforts on their syntheses, and the cost of materials and manpower. This is one of the reasons for an increasing interest in design and development of novel materials with required properties assisted by machine learning approaches. Here, the dataset on synthetic parameters and optical properties of one important class of light-emitting nanomaterials - carbon dots are collected, processed, and analyzed with optical transitions in the red and near-infrared spectral ranges. A model for prediction of spectral characteristics of these carbon dots based on multiple linear regression is established and verified by comparison of the predicted and experimentally observed optical properties of carbon dots synthesized in three different laboratories. Based on the analysis, the open-source code is provided to be used by researchers for the prediction of optical properties of carbon dots and their synthetic procedures. Materials science ; Carbon fibers ; Nanomaterials ; Infrared ; Nanotechnology ; Near-infrared spectroscopy ; Computer science ; Spectral properties ; Nanostructure ; Optics ; Composite number ; Composite material ; Physics Carbon and Quantum Dots Applications ; Advanced Nanomaterials in Catalysis ; Quantum Dots Synthesis And Properties
Authors: Seyed Mohamad Javidan | Ahmad Banakar | Keyvan Asefpour Vakilian | Yiannis Ampatzidis | K Rahnama
Source: Heliyon (article, 2024-09-19)
Field: Chemistry — Analytical Chemistry

Early detection and spectral signature identification of tomato fungal diseases (Alternaria alternata, Alternaria solani, Botrytis cinerea, and Fusarium oxysporum) by RGB and hyperspectral image analysis and machine learning Early identification of plant fungal diseases is critical for timely treatment, which can prevent significant agricultural losses. While molecular analysis offers high accuracy, it is often expensive and time-consuming. In contrast, image processing combined with machine learning provides a rapid and cost-effective alternative for disease diagnosis. This study presents a novel approach for detecting four common fungal diseases in tomatoes, <i>Botrytis cinerea</i>, <i>Fusarium oxysporum</i>, <i>Alternaria alternata</i>, and <i>Alternaria solani</i>, using both RGB (visible) and hyperspectral (400-950 nm) imaging of plant leaves over the first 11 days post-infection. Data sets were generated from leaf samples, and a range of statistical, texture, and shape features were extracted to train machine learning models. The spectral signatures of each disease were also developed for improved classification. The random forest model achieved the highest accuracy, with classification rates for RGB images of 65%, 71%, 75%, 77%, 83%, and 87% on days 1, 3, 5, 7, 9, and 11, respectively. For hyperspectral images, the classification accuracy increased from 86% on day 1 to 98% by day 11. Two- and three-dimensional spectral analyses clearly differentiated healthy plants from infected ones as early as day 3 for <i>Botrytis cinerea</i>. The Laplacian score method further highlighted key texture features, such as energy at 550 and 841 nm, entropy at 600 nm, correlation at 746 nm, and standard deviation at 905 nm, that contributed most significantly to disease detection. The method developed in this study offers a valuable and efficient tool for accelerating plant disease diagnosis and classification, providing a practical alternative to molecular techniques. . Alternaria alternata ; Botrytis cinerea ; Alternaria solani ; Fusarium oxysporum ; Hyperspectral imaging ; Alternaria ; Biology ; Fusarium solani ; Botrytis ; Spectral signature ; Fusarium ; Botany ; Artificial intelligence ; Fungicide ; Computer science ; Remote sensing Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Naouri Ladaci | A. C. Saadia | Ahmed Belaadi | Messaouda Boumaaza | Boon Xian Chai | Mahmood M. S. Abdullah | Amar Al-Khawlani | Djamel Ghernaout
Source: Journal of Natural Fibers (article, 2024-06-02)
Field: Materials Science — Polymers and Plastics

ANN and RSM Prediction of Water Uptake of Recycled HDPE Biocomposite Reinforced with Treated Palm Waste <i>W. filifera</i> This study examined the water uptake (WU) behavior of recycled high-density polyethylene (RHDPE). The biocomposites made of palm waste Washingtonia (PWW) fibers were treated with 3% sodium bicarbonate (NaHCO3) for 24 h. Several RHDPE materials reinforced with different concentrations of PWW fibers (5 to 30 wt.%) until saturation, or roughly 25 days, were developed to investigate the WU kinetics and diffusion in biocomposites. An artificial neural network (ANN) and the response surface methodology (RSM) methods were applied to model the behavior of uptake measured in experiments and optimize the immersion period and PWW fiber content in RHDPE/PWW biocomposite WU. The WU moved swiftly during the first test phase and was completed after 400 h of soaking. The outcomes demonstrated a perfect fit between the observed and anticipated data. Findings showed that the ANN models’ training, test, and validation correlation coefficients were 0.9984, 0.9955, and 0.9723, respectively, for predicting WU. Concerning accuracy and reliability, the ANN model outperformed the RSM model, making it suitable for various industrial uses. The results offer helpful information for professionals to consider when developing and implementing PWW fiber biocomposites. Biocomposite ; High-density polyethylene ; Response surface methodology ; Materials science ; Pulp and paper industry ; Composite material ; Mathematics ; Waste management ; Composite number ; Polyethylene ; Engineering Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; biodegradable polymer synthesis and properties
Authors: Sheetal Kumari | Jyoti Chowdhry | Alakto Choudhury | Smriti Agarwal | Priyanka Narad | Manoj Chandra Garg
Source: Environmental Science and Pollution Research (article, 2024-01-16)
Field: Chemistry — Analytical Chemistry

Machine learning approaches for the treatment of textile wastewater using sugarcane bagasse (Saccharum officinarum) biochar Biochar ; Response surface methodology ; Wastewater ; Bagasse ; Adaptive neuro fuzzy inference system ; Adsorption ; Pulp and paper industry ; Fourier transform infrared spectroscopy ; Textile ; Central composite design ; Materials science ; Chemistry ; Environmental science ; Chemical engineering ; Environmental engineering ; Composite material ; Chromatography ; Computer science ; Artificial intelligence ; Pyrolysis ; Organic chemistry ; Fuzzy logic ; Engineering Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal ; Water Quality Monitoring and Analysis
Authors: Rahul Kant Jha | Bertrand J. Neyhouse | Morgan S. Young | Danielle E. Fagnani | Anne J. McNeil
Source: Chemical Science (review, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Revisiting poly(vinyl chloride) reactivity in the context of chemical recycling Poly(vinyl chloride) (PVC) is one of the highest production volume polymers due to its many applications, and it is one of the least recycled due to its chemical structure and frequent formulation with additives. Developing efficient PVC recycling techniques would enable PVC waste to be reused or repurposed in other processes. Within this context, the literature on PVC modification offers considerable insight into versatile reaction pathways, potentially inspiring new approaches for repurposing PVC waste into value-added products. This perspective provides an overview of PVC functionalization through a lens of chemical recycling, discussing various PVC reactivity trends and their applications with a critical assessment and future outlook of their recycling implications. Reactivity (psychology) ; Context (archaeology) ; Vinyl chloride ; Chloride ; Chemistry ; Organic chemistry ; Polymer chemistry ; Materials science ; Polymer ; Geology Polymer Science and PVC ; Extraction and Separation Processes ; biodegradable polymer synthesis and properties
Authors: Yaohui Xu | Yang Zhou | Yuting Li | Yechen Hao | Pingkeng Wu | Zhao Ding
Source: Molecules (article, 2024-05-23)
Field: Materials Science — Materials Chemistry

Recent Advances in the Preparation Methods of Magnesium-Based Hydrogen Storage Materials Magnesium-based hydrogen storage materials have garnered significant attention due to their high hydrogen storage capacity, abundance, and low cost. However, the slow kinetics and high desorption temperature of magnesium hydride hinder its practical application. Various preparation methods have been developed to improve the hydrogen storage properties of magnesium-based materials. This review comprehensively summarizes the recent advances in the preparation methods of magnesium-based hydrogen storage materials, including mechanical ball milling, methanol-wrapped chemical vapor deposition, plasma-assisted ball milling, organic ligand-assisted synthesis, and other emerging methods. The principles, processes, key parameters, and modification strategies of each method are discussed in detail, along with representative research cases. Furthermore, the advantages and disadvantages of different preparation methods are compared and evaluated, and their influence on hydrogen storage properties is analyzed. The practical application potential of these methods is also assessed, considering factors such as hydrogen storage performance, scalability, and cost-effectiveness. Finally, the existing challenges and future research directions in this field are outlined, emphasizing the need for further development of high-performance and cost-effective magnesium-based hydrogen storage materials for clean energy applications. This review provides valuable insights and references for researchers working on the development of advanced magnesium-based hydrogen storage technologies. Hydrogen storage ; Magnesium hydride ; Materials science ; Magnesium ; Ball mill ; Hydrogen ; Energy storage ; Process engineering ; Nanotechnology ; Chemistry ; Metallurgy ; Engineering Hydrogen Storage and Materials ; Ammonia Synthesis and Nitrogen Reduction ; MXene and MAX Phase Materials
Authors: Niklas Geue | Richard E. P. Winpenny | Perdita E. Barran
Source: Journal of the American Chemical Society (review, 2024-03-18)
Field: Chemistry — Spectroscopy

Ion Mobility Mass Spectrometry for Large Synthetic Molecules: Expanding the Analytical Toolbox Understanding the composition, structure and stability of larger synthetic molecules is crucial for their design, yet currently the analytical tools commonly used do not always provide this information. In this perspective, we show how ion mobility mass spectrometry (IM-MS), in combination with tandem mass spectrometry, complementary techniques and computational methods, can be used to structurally characterize synthetic molecules, make and predict new complexes, monitor disassembly processes and determine stability. Using IM-MS, we present an experimental and computational framework for the analysis and design of complex molecular architectures such as (metallo)supramolecular cages, nanoclusters, interlocked molecules, rotaxanes, dendrimers, polymers and host-guest complexes. Chemistry ; Mass spectrometry ; Toolbox ; Ion-mobility spectrometry ; Molecule ; Ion ; Chromatography ; Organic chemistry Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Molecular Sensors and Ion Detection
Authors: Saeed Rajabi | Zahra Derakhshan | Majid Hashemi | Mehrzad Feilizadeh | Saeed Heidari Kochaki | Hassan Hashemi | Mohammadhossein Salehi | Amirreza Zare | Narges Sadat Shourabi | Saeideh Moradalizadeh
Source: Applied Water Science (article, 2024-04-09)
Field: Chemistry — Organic Chemistry

Metronidazole adsorption by bio-synthesized silver-zinc ferrite nanoadsorbent in presence of chitosan from aqueous media: response surface methodology Abstract A novel magnetic biocomposite adsorbent, denoted as AgZnFe 2 O 4 @Ch, was utilized for the degradation of Metronidazole (MNZ) from water. Various analytical techniques, including vibrating sample magnetometer (VSM), X-ray diffraction (XRD), Brunauer–Emmett–Teller, Fourier transform infrared spectroscopy, and field emission scanning electron microscopy (FESEM), were applied to investigate the characteristics of the magnetic biocomposite adsorbent. XRD examination confirmed the formation of spinel ferrites phases. FESEM assessment indicated a notable reduction in sample aggregation. The ferromagnetic character of the adsorbent was well demonstrated by VSM analysis. The saturation magnetization value for straightforward separating by the outside magnetic fields was 14.64 emu/g. An analytical modeling approach was used to evaluate and analyze the impacts of factors including MNZ initial concentration, temperature, contact time, adsorbent dosage, and pH. Optimized conditions involved an adsorbent dosage of 0.9 g/L, pH of 7, MNZ initial concentration of 10 mg/L, and a contact time of 50 min, resulting in a peak adsorption efficiency of 65.53% under favorable circumstances. A good degree of fit was achieved with the linear model. The experimental equilibrium data fitting to the Langmuir, Freundlich, and Temkin isotherm models demonstrates that the Langmuir model was an effective and appropriate model for evaluating adsorption. Intraparticle kinetic modeling was also shown to be better suitable for characterizing the MNZ adsorption onto the adsorbent. The thermodynamic analysis indicated that the process of MNZ adsorption by AgZnFe 2 O 4 @Ch was characterized by exothermicity and lacked spontaneity. Adsorption ; Chitosan ; Zinc ferrite ; Aqueous solution ; Zinc ; Ferrite (magnet) ; Aqueous medium ; Chemistry ; Nuclear chemistry ; Materials science ; Inorganic chemistry ; Chemical engineering ; Metallurgy ; Organic chemistry ; Composite material ; Engineering Nanomaterials for catalytic reactions ; Electrochemical sensors and biosensors ; Advanced biosensing and bioanalysis techniques
Authors: Samuel Van Gele | Sebastian Bette | Bettina V. Lotsch
Source: JACS Au (article, 2024-12-23)
Field: Materials Science — Materials Chemistry

The Devil Is in the Details: Pitfalls and Ambiguities in the Analysis of X-ray Powder Diffraction Data of 2D Covalent Organic Frameworks X-ray powder diffraction (XRPD) data of covalent organic frameworks (COFs) seem to be simple and apparently do not contain a lot of structural information, as these patterns usually do not show more than 3-5 distinguishable Bragg peaks. As COFs are inherently complex materials exhibiting a variety of disorder phenomena like stacking faults, layer curving, or disordered solvent molecules populating the pores, the interpretation of XRPD patterns is far from being trivial. Here we emphasize the critical need for precision and caution in XRPD data acquisition, refinement, and interpretation to avoid common pitfalls and overinterpretations in data analysis. This perspective serves as a comprehensive guide, educating the community on the nuances of refinement processes necessary for advancing COF research with clarity and accuracy. Powder diffraction ; X-ray ; Materials science ; Diffraction ; Covalent bond ; X-ray crystallography ; Nanotechnology ; Crystallography ; Chemistry ; Physics ; Optics ; Organic chemistry Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Radioactive element chemistry and processing
Authors: Sundus Saeed Qureshi | Sabzoi Nizamuddin | Jia Xu | Tony Vancov | Chengrong Chen
Source: Environmental Science and Pollution Research (review, 2024-09-28)
Field: Materials Science — Biomaterials

Cellulose nanocrystals from agriculture and forestry biomass: synthesis methods, characterization and industrial applications Agricultural and forestry biomass wastes, often discarded or burned without adequate management, lead to significant environmental harm. However, cellulose nanocrystals (CNCs), derived from such biomass, have emerged as highly promising materials due to their unique properties, including high tensile strength, large surface area, biocompatibility, and renewability. This review provides a detailed analysis of the lignocellulosic composition, as well as the elemental and proximate analysis of different biomass sources. These assessments help determine the yield and characteristics of CNCs. Detailed discussion of CNC synthesis methods -ranging from biomass pretreatment to hydrolysis techniques such as acid, mineral, solid acid, ionic liquid, and enzymatic methods-are provided. The key physical, chemical, and thermal properties of CNCs are also highlighted, particularly in relation to their industrial applications. Recommendations for future research emphasize the need to optimize CNC synthesis processes, identify suitable biomass feedstocks, and explore new industrial applications. Biomass (ecology) ; Cellulose ; Lignocellulosic biomass ; Environmental science ; Pulp and paper industry ; Chemistry ; Agronomy ; Organic chemistry ; Engineering Advanced Cellulose Research Studies ; Biofuel production and bioconversion ; Lignin and Wood Chemistry
Authors: Giuseppe Sassone | Ӧzden Çelikbilek | Maxime Hubert | Katherine Develos-Bagarinao | Thomas David | Laure Guétaz | Isabelle Martin | Julie Villanova | Anass Benayad | Léa Rorato | Julien Vulliet | Bertrand Morel | Aline Léon | Jérôme Laurencin
Source: Journal of Power Sources (article, 2024-04-17)
Field: Materials Science — Materials Chemistry

Effect of the operating temperature on the degradation of solid oxide electrolysis cells Electrolyte ; Clark electrode ; Materials science ; Electrode ; Electrolysis ; Oxide ; Electrochemistry ; Hydrogen ; Reversible hydrogen electrode ; Standard hydrogen electrode ; High-temperature electrolysis ; Oxygen ; Yttria-stabilized zirconia ; Chemical engineering ; Reference electrode ; Chemistry ; Ceramic ; Composite material ; Metallurgy ; Cubic zirconia ; Physical chemistry Advancements in Solid Oxide Fuel Cells ; Chemical Looping and Thermochemical Processes ; Catalysis and Oxidation Reactions