jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Julie Horne | Pierre Beckers | Pierre‐Yves Sacré | Charlotte De Bleye | Pierre Francotte | Nicolas Thelen | Philippe Hubert | Eric Ziémons | Cédric Hubert
Source: Molecules (article, 2024-07-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimisation of a Microwave Synthesis of Silver Nanoparticles by a Quality by Design Approach to Improve SERS Analytical Performances A major limitation preventing the use of surface-enhanced Raman scattering (SERS) in routine analyses is the signal variability due to the heterogeneity of metallic nanoparticles used as SERS substrates. This study aimed to robustly optimise a synthesis process of silver nanoparticles to improve the measured SERS signal repeatability and the protocol synthesis repeatability. The process is inspired by a chemical reduction method associated with microwave irradiation to guarantee better controlled and uniform heating. The innovative Quality by Design strategy was implemented to optimise the different parameters of the process. A preliminary investigation design was firstly carried out to evaluate the influence of four parameters selected by means of an Ishikawa diagram. The critical quality attributes were to maximise the intensity of the SERS response and minimise its variance. The reaction time, temperature and stirring speed are critical process parameters. These were optimised using an I-optimal design. A robust operating zone covering the optimal reaction conditions (3.36 min-130 °C-600 rpm) associated with a probability of success was modelled. Validation of this point confirmed the prediction with intra- and inter-batch variabilities of less than 15%. In conclusion, this study successfully optimised silver nanoparticles by a rapid, low cost and simple technique enhancing the quantitative perspectives of SERS. Repeatability ; Materials science ; Microwave ; Process engineering ; Process (computing) ; Nanoparticle ; Nanotechnology ; Raman scattering ; Response surface methodology ; Quality by Design ; Computer science ; Biological system ; Raman spectroscopy ; Chemical engineering ; Machine learning ; Chromatography ; Chemistry ; Optics Gold and Silver Nanoparticles Synthesis and Applications ; Quantum Dots Synthesis And Properties ; Nanocluster Synthesis and Applications
Authors: Sofiene Achour | Zied Hosni
Source: ChemRxiv (preprint, 2024-02-22)
Field: Chemistry — Inorganic Chemistry

Machine Learning-driven models for predicting CO2 Uptake in Metal-Organic Frameworks (MOFs) This study advances the discourse on the application of machine learning (ML) algorithms for the predictive analysis of CO2 uptake in Metal-Organic Frameworks (MOFs), with a nuanced focus on the CATBoost model's capability to navigate the complexities inherent in MOFs' heterogeneous landscape. Building upon and extending the comparative analysis, our investigation underscores the CATBoost model's remarkable predictive prowess, characterized by a significant reduction in root mean square error (RMSE) and an enhanced R-squared (R²) value, thereby affirming its superior accuracy and reliability in forecasting CO2 adsorption. A pivotal aspect of our research is the integration of SHAP values for a detailed assessment of feature importance, which not only corroborated 'Pressure' and 'Surface Area' as pivotal determinants of CO2 uptake but also illuminated the model's advanced analytical capabilities in handling categorical features and mitigating overfitting, even within a dataset marked by intricate and non-linear patterns. Our quantitative and conceptual analysis, showcasing up to a 15% improvement in (RMSE) over previous models, reveals the CATBoost model’s unparalleled efficiency in discerning the multifaceted interplay of factors influencing CO2 adsorption. This is crucial for the strategic engineering of MOFs with optimized properties. Beyond 'Pressure' and 'Surface Area', our SHAP analysis highlighted other descriptors with substantial values, elucidating their nuanced contributions to CO2 uptake and providing invaluable insights for the MOF design process. Through this work, we aim to foster a deeper understanding and application of ML algorithms in environmental sustainability, thereby building upon the foundational research of Abdi et al. and pushing the boundaries of machine learning applications in the field. Metal-organic framework ; Computer science ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Catalytic Processes in Materials Science
Authors: Toufique Ahmed | R. Tuğrul Ogulata | Osman Gülnaz
Source: Textile & Leather Review (article, 2024-02-07)
Field: Materials Science — Materials Chemistry

Multifarious Uses of UV-VIS Spectroscopy for Green Synthesis of Silver Nanoparticles for Antibacterial Textiles Green synthesis is an easy and economical method of synthesizing silver nanoparticles (AgNPs). However, many variables, including the ideal temperature, the volume and concentration of silver nitrate, the amount of plant extract, etc., affect the green synthesis. This article aims to determine the ideal temperature and plant extract amount using the UV-VIS spectrum. It was found above 40 °C was required for both Calendula arvensis (field marigold) leave extract and silver nitrate to synthesize AgNPs. The optimum temperatures were 55 °C and 60 °C for AgNO3 and plant extract, respectively and it was determined using Taguchi orthogonal array based on the UV-VIS spectrum. Silver nanoparticles (AgNPs) can be incorporated into textiles by padding and in-situ methods, but they need accurate plant extract amounts for good antibacterial efficiency. Two equations were proposed for determining the optimum plant extract amount for padding and in-situ methods. Several AgNPs loaded samples were prepared following the derived equations. For evaluating the efficiency of the equations C.reticulata (orange) peel extract was used besides C.arvensis plant extract. The samples were also characterized by antibacterial tests, Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS), and X-ray diffraction (XRD). It showed when plant extract was taken according to the equations, around 45 nm nanoparticle size and 100% antibacterial activity were obtained. However, taking 1 ml more plant extract than that of the calculated amount of plant extract increased nanoparticle size to 107 nm and reduced antibacterial activity to 90%. Silver nanoparticle ; Silver nitrate ; Antibacterial activity ; Nuclear chemistry ; Scanning electron microscope ; Materials science ; Nanoparticle ; Spectroscopy ; Analytical Chemistry (journal) ; Chemistry ; Nanotechnology ; Chromatography ; Composite material ; Physics ; Bacteria Nanoparticles: synthesis and applications ; Dyeing and Modifying Textile Fibers ; Essential Oils and Antimicrobial Activity
Authors: Ahmed S. Al‐Fatesh | Ramakrishna Chava | Saba M. Alwan | Ahmed A. Ibrahim | Anis H. Fakeeha | Jehad K. Abu‐Dahrieh | Ahmed Yagoub Elnour | Ahmed E. Abasaeed | Othman Y. Alothman | Srinivas Appari
Source: Catalysis Letters (article, 2024-09-30)
Field: Materials Science — Materials Chemistry

Effect of Ga-Promoted on Ni/Zr + Al2O3 Catalysts for Enhanced CO2 Reforming and Process Optimization Abstract In this study, zirconia-modified alumina support (S) was used to investigate Ga-promoted Ni catalysts for dry reforming of methane (DRM). The catalysts (Ni + (0–3) wt% Ga/S) were prepared using the wet impregnation method and calcined at 700 °C for 3 h. The inclusion of Ga enhanced the surface area, basicity, and metal-support interaction of the Ni-Ga/S catalysts. Smaller Ni particles containing Ga were seen in the TEM. The most active and stable catalyst was Ni + 2.0 Ga/S, having a conversion of 35% CO 2 and 28% CH 4 at 600 °C and displaying less (17%) carbon deposition. Furthermore, the DRM process was optimized by a mathematical model. The model determined the optimal conditions as follows: temperature (800 °C), gas flow rate (GHSV—30,000 ml h −1 gcat −1 ), and methane to carbon dioxide ratio (1:1). The model predicts CH 4 and CO 2 conversions of 76.76% and 82.0%, respectively, and an H 2 /CO ratio of 1.02, compared to experimental results showing CH 4 conversion at 74.56%, CO 2 conversion at 83.25%, and an H 2 /CO ratio of 1.01. The model demonstrates excellent agreement with the experimental observations, exhibiting less than 3% error. Graphical Abstract Chemistry ; Catalysis ; Organometallic chemistry ; Process (computing) ; Heterogeneous catalysis ; Chemical engineering ; Organic chemistry Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Oxidation Reactions
Authors: Masoud Shahrokhi | Tzonka Mineva | A. Benabbas | Catherine Especel | Anthony Le Valant | Christian Ricolleau | Guillaume Wang | Jaysen Nelayah | Florence Epron | Hazar Guesmi
Source: ChemCatChem (article, 2024-06-04)
Field: Materials Science — Materials Chemistry

DFT Atomic‐Scale Insight into Pt/Cu Single Atom Alloy Clusters Supported on γ‐Al<sub>2</sub>O<sub>3</sub>: The Effect of Hydrogen Environment Abstract Single atom alloy (SAA) clusters formed by anchoring single atoms in small supported host clusters are emerging as catalysts with high performance. In this work, density functional theory (DFT) calculations and ab‐initio molecular dynamics (AIMD) simulations are performed to study the stability and the structure evolution of γ‐alumina‐supported platinum/copper SAA clusters of sub‐nanometer size in hydrogen environment. Due to the strong dynamic nature of both Cu cluster and anchored Pt single atom and their evolving interaction with the support, different isomers with different geometric and energetic properties are predicted. Extensive sampling through AIMD simulations reveals strong effect of hydrogen on the location of Pt single atom and strong variation of the cluster shape, evolving from 3D to concave and planar shapes wetting the alumina support. Interfacial site location of Pt single atom is found to be hydrogen coverage dependent. When the hydrogen coverage increases, the Pt single atom located preferentially at the interfacial site is pulled up by hydrogen atoms toward the upper surface Cu layers. The interaction of Pt/Cu cluster with alumina is predicted to decrease with increasing hydrogen coverage. Finally, electronic structure analysis reveals dramatic effect of hydrogen on the metallic nature of the catalysts. Cluster (spacecraft) ; Density functional theory ; Hydrogen ; Chemical physics ; Atom (system on chip) ; Hydrogen atom ; Molecular dynamics ; Catalysis ; Platinum ; Materials science ; Crystallography ; Metal ; Alloy ; Copper ; Ab initio ; Chemistry ; Physical chemistry ; Computational chemistry ; Metallurgy Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Nanomaterials for catalytic reactions
Authors: Artem Kozmin | E. Yu. Erushin | И. Б. Мирошниченко | Nadezhda Y. Kostyukova | Аndrey А. Boyko | Alexey Redyuk
Source: Optics (article, 2024-04-03)
Field: Chemistry — Spectroscopy

Wavelet-Based Machine Learning Algorithms for Photoacoustic Gas Sensing The significance of intelligent sensor systems has grown across diverse sectors, including healthcare, environmental surveillance, industrial automation, and security. Photoacoustic gas sensors are a promising type of optical gas sensor due to their high sensitivity, enhanced frequency selectivity, and fast response time. However, they have limitations such as dependence on a high-power light source, a requirement for a high-quality acoustic signal detector, and sensitivity to environmental factors, affecting their accuracy and reliability. Machine learning has great potential in the analysis and interpretation of sensor data as it can identify complex patterns and make accurate predictions based on the available data. We propose a novel approach that utilizes wavelet analysis and neural networks with enhanced architectures to improve the accuracy and sensitivity of photoacoustic gas sensors. Our proposed approach was experimentally tested for methane concentration measurements, showcasing its potential to significantly advance the field of gas detection and analysis, providing more accurate and reliable results. Wavelet ; Photoacoustic imaging in biomedicine ; Computer science ; Artificial intelligence ; Machine learning ; Algorithm ; Pattern recognition (psychology) ; Optics ; Physics Spectroscopy and Laser Applications ; Advanced Chemical Sensor Technologies ; Air Quality Monitoring and Forecasting
Authors: Haoran Qu | Yulun Han | Jacob Fortner | Xiaojian Wu | Svetlana Kilina | Dmitri S. Kilin | Sergei Tretiak | YuHuang Wang
Source: Journal of the American Chemical Society (article, 2024-08-05)
Field: Chemistry — Organic Chemistry

[2 + 2] Cycloaddition Produces Divalent Organic Color-Centers with Reduced Heterogeneity in Single-Walled Carbon Nanotubes Organic color centers (OCCs), generated by the covalent functionalization of single-walled carbon nanotubes, have been exploited for chemical sensing, bioimaging, and quantum technologies. However, monovalent OCCs can assume at least 6 different bonding configurations on the sp2 carbon lattice of a chiral nanotube, resulting in heterogeneous OCC photoluminescence emissions. Herein, we show that a heat-activated [2 + 2] cycloaddition reaction enables the synthesis of divalent OCCs with a reduced number of atomic bonding configurations. The chemistry occurs by simply mixing enophile molecules (e.g., methylmaleimide, maleic anhydride, and 4-cyclopentene-1,3-dione) with an ethylene glycol suspension of SWCNTs at elevated temperature (70–140 °C). Unlike monovalent OCC chemistries, we observe just three OCC emission peaks that can be assigned to the three possible bonding configurations of the divalent OCCs based on density functional theory calculations. Notably, these OCC photoluminescence peaks can be controlled by temperature to decrease the emission heterogeneity even further. This divalent chemistry provides a scalable way to synthesize OCCs with tightly controlled emissions for emerging applications. Chemistry ; Carbon nanotube ; Cycloaddition ; Divalent ; Photoluminescence ; Covalent bond ; Molecule ; Maleic anhydride ; Ethylene glycol ; Density functional theory ; Nanotechnology ; Chemical engineering ; Photochemistry ; Computational chemistry ; Organic chemistry ; Polymer ; Catalysis ; Optoelectronics ; Materials science Synthesis and Properties of Aromatic Compounds ; Carbon Nanotubes in Composites ; Luminescence and Fluorescent Materials
Authors: Alexander Anatolyevich Ganyukov | Kirill Anatolyevich Sinelnikov | Sapar Zhomartovich Kabikenov | Akbope Zholaevna Karsakova
Source: Material and Mechanical Engineering Technology (article, 2024-10-01)
Field: Materials Science — Materials Chemistry

Research and Calculation of the Deformed State of the Roadway Mobile Overpass The article proposes a new type of transport equipment that is a mobile overpass. The proposed design is used during underground repairs of urban utility networks and is a prefabricated modular bridge structure equipped with its own chassis. The overpass structure is installed through open repair trenches on highways, which will ensure continuous traffic through repair sections. The overpass is equipped with its own chassis and is mobile. The use of the overpass improves the city transport logistics during repair work: eliminates traffic jams due to the lack of need to detour repair sections, reduces the accident rate, distributes traffic flows, improves the environment, etc. It can also be used during emergency situations where it is necessary to overcome various landslides, ditches, trenches, etc. After the end of operation, the overpass structure is dismantled and can be used multiple times. The aim of the study is to calculate the deformed state of the structurally orthotropic slab of the roadway of a mobile overpass with a check for standard rigidity. Calculations of the roadway for rigidity from moving motor vehicles are performed by means of the Bubnov-Galerkin variational method. The final results include calculations of deflections in the center of the slab clamped along the contour, as well as the conditions for implementing the deflection limitation according to the standards of automobile bridge construction. Based on the results obtained, the design parameters of the slab satisfying the rigidity and strength condition are determined. The studies and calculations conducted allow for the practical design of the roadway structure of the overpass Slab ; Deflection (physics) ; Chassis ; Rigidity (electromagnetism) ; Orthotropic material ; Modular design Structural mechanics and materials ; Advanced Energy Technologies and Civil Engineering Innovations ; Transportation Systems and Logistics
Authors: Ana Carolina de Jesus Oliveira | Camilla Alves Pereira Rodrigues | Maria Carolina de Almeida | Eliane Teixeira Mársico | Paulo Sérgio Scalize | Tatianne Ferreira de Oliveira | Víctor A. Solar | Héctor Váldes
Source: Molecules (article, 2024-06-07)
Field: Materials Science — Materials Chemistry

Ethylene Elimination Using Activated Carbons Obtained from Baru (Dipteryx alata vog.) Waste and Impregnated with Copper Oxide Ethylene is a plant hormone regulator that stimulates chlorophyll loss and promotes softening and aging, resulting in a deterioration and reduction in the post-harvest life of fruit. Commercial activated carbons have been used as ethylene scavengers during the storage and transportation of a great variety of agricultural commodities. In this work, the effect of the incorporation of copper oxide over activated carbons obtained from baru waste was assessed. Samples were characterized by X-ray diffraction (XRD), N<sub>2</sub> adsorption-desorption at -196 °C, field-emission scanning electron microscopy (FESEM) coupled with energy-dispersive X-ray spectroscopy (EDS), and infrared (IR) spectroscopy. The results showed that the amount of ethylene removed using activated carbon obtained from baru waste and impregnated with copper oxide (1667 μg g<sup>-1</sup>) was significantly increased in comparison to the raw activated carbon (1111 μg g<sup>-1</sup>). In addition, carbon impregnated with copper oxide exhibited better adsorption performance at a low ethylene concentration. Activated carbons produced from baru waste are promising candidates to be used as adsorbents in the elimination of ethylene during the storage and transportation of agricultural commodities at a lower cost. Copper ; Ethylene oxide ; Chemistry ; Baru ; Ethylene ; Nuclear chemistry ; Activated carbon ; Waste management ; Adsorption ; Organic chemistry ; Engineering ; Archaeology Catalytic Processes in Materials Science ; Mesoporous Materials and Catalysis ; Catalysis and Hydrodesulfurization Studies
Authors: Kara A. Zielinski | Cole Dolamore | Harrison K. Wang | Robert Henning | Mark A. Wilson | Lois Pollack | V. Šrajer | Doeke R. Hekstra | Kevin M. Dalton
Source: Structural Dynamics (article, 2024-11-01)
Field: Materials Science — Materials Chemistry

Scaling and merging time-resolved pink-beam diffraction with variational inference Time-resolved x-ray crystallography (TR-X) at synchrotrons and free electron lasers is a promising technique for recording dynamics of molecules at atomic resolution. While experimental methods for TR-X have proliferated and matured, data analysis is often difficult. Extracting small, time-dependent changes in signal is frequently a bottleneck for practitioners. Recent work demonstrated this challenge can be addressed when merging redundant observations by a statistical technique known as variational inference (VI). However, the variational approach to time-resolved data analysis requires identification of successful hyperparameters in order to optimally extract signal. In this case study, we present a successful application of VI to time-resolved changes in an enzyme, DJ-1, upon mixing with a substrate molecule, methylglyoxal. We present a strategy to extract high signal-to-noise changes in electron density from these data. Furthermore, we conduct an ablation study, in which we systematically remove one hyperparameter at a time to demonstrate the impact of each hyperparameter choice on the success of our model. We expect this case study will serve as a practical example for how others may deploy VI in order to analyze their time-resolved diffraction data. Hyperparameter ; Inference ; Bottleneck ; Computer science ; Diffraction ; Algorithm ; Scaling ; Physics ; Statistical physics ; Optics ; Artificial intelligence ; Mathematics Enzyme Structure and Function ; Advanced X-ray Imaging Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Elisangela da Silva Barboza | Alexandre C. Dias | L. Craco | S. S. Carara | D. R. da Costa | T. A. S. Pereira
Source: ACS Omega (article, 2024-11-16)
Field: Materials Science — Materials Chemistry

Electronic, Excitonic, and Optical Properties of Zinc Blende Boron Arsenide Tuned by Hydrostatic Pressure Based on first-principles calculations combined with a maximally localized Wannier function tight-binding method and the Bethe-Salpeter equation formalism, we theoretically investigate the effects of hydrostatic pressure on the electronic, excitonic, and optical properties of zinc blende boron arsenide. Our findings show: (i) a pressure-induced semiconductor-to-metallic phase transition without causing any change in the structural crystallographic ordering, (ii) a decrease in excitonic binding energy with increasing pressure as a consequence of band gap engineering, and (iii) a small excitonic response in the indirect absorption regime due to the indirect band gap. Hydrostatic pressure ; Binding energy ; Band gap ; Condensed matter physics ; Exciton ; Semiconductor ; Boron ; Gallium arsenide ; Arsenide ; Wannier function ; Zinc ; Electronic band structure ; Materials science ; Tight binding ; Direct and indirect band gaps ; Chemistry ; Electronic structure ; Optoelectronics ; Physics ; Atomic physics ; Thermodynamics 2D Materials and Applications ; Graphene research and applications ; Boron and Carbon Nanomaterials Research