jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Michael Ingham | Alex Aziz | Devis Di Tommaso | Rachel Crespo‐Otero
Source: Materials Advances (article, 2023-01-01)
Field: Chemistry — Inorganic Chemistry

Simulating excited states in metal organic frameworks: from light-absorption to photochemical CO<sub>2</sub> reduction Quantum chemical simulations have shed light on the complex photochemical processes occurring within metal–organic frameworks. This perspective explores the computational techniques used to describe the excited states of MOFs, considering molecular, periodic, and embedding models. Excited state ; Reduction (mathematics) ; Photochemistry ; Quantum chemical ; Metal ; Embedding ; Absorption (acoustics) ; Metal-organic framework ; Materials science ; Chemical physics ; Chemistry ; Molecule ; Atomic physics ; Physics ; Physical chemistry ; Computer science ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Nanoplatforms for cancer theranostics
Authors: Jin-Seok Yoo | Nguyen Thuy Chung | Yoonho Lee | Yong Won Kim | Jung-Gu Kim
Source: Materials (article, 2023-12-28)
Field: Materials Science — Materials Chemistry

Effect of Sulfide and Chloride Ions on Pitting Corrosion of Type 316 Austenitic Stainless Steel in Groundwater Conditions Using Response Surface Methodology This study investigates the corrosion resistance of Type 316 stainless steel as a candidate material for radioactive waste disposal canisters. The viability of stainless steel is examined under groundwater conditions with variations in pH, bisulfide ions (HS<sup>-</sup>), and chloride ions (Cl<sup>-</sup>) concentrations. Utilizing response surface methodology, correlations between corrosion factors and two crucial response variables, passive film breakdown potential and protection potential, are established. Cyclic potentiodynamic polarization tests and advanced analytical techniques provide detailed insights into the material's behavior. This research goes beyond, deriving an equation through response surface methodology that elucidates the relationship between the factors and breakdown potential. HS<sup>-</sup> weakens the passive film and reduces the pitting corrosion resistance of the stainless steel. However, this study highlights the inhibitory effect of HS<sup>-</sup> on pitting corrosion when Cl<sup>-</sup> concentrations are below 0.001 M and at equivalent concentrations of HS<sup>-</sup>. Under these conditions, immediate re-passivation occurs from the destroyed passive film to metal sulfides such as FeS<sub>2</sub>, MoS<sub>2</sub>, and MoS<sub>3</sub>. As a result, no hysteresis loop occurs in the cyclic polarization curve in these conditions. This research contributes to the understanding of Type 316 stainless-steel corrosion behavior, offering implications for the disposal of radioactive waste in geological repositories. Corrosion ; Chloride ; Passivation ; Austenitic stainless steel ; Sulfide ; Pitting corrosion ; Materials science ; Polarization (electrochemistry) ; Metallurgy ; Groundwater ; Composite material ; Geology ; Geotechnical engineering ; Chemistry Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Pei Zhang | Logan T. Kearney | Debsindhu Bhowmik | Zachary Fox | Amit K. Naskar | John Gounley
Source: Journal of Chemical Information and Modeling (article, 2023-12-06)
Field: Materials Science — Materials Chemistry

Transferring a Molecular Foundation Model for Polymer Property Predictions Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. State-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks. Computer science ; Transformer ; Benchmark (surveying) ; Labeled data ; Transfer of learning ; Polymer ; Artificial intelligence ; Machine learning ; Materials science ; Engineering ; Electrical engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: José J. Plata | Ernesto J. Blancas | Antonio M. Márquez | Víctor Posligua | Javier Fdez. Sanz | Ricardo Grau‐Crespo
Source: Journal of Materials Chemistry A (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Harnessing the unusually strong improvement of thermoelectric performance of AgInTe<sub>2</sub> with nanostructuring Nanostructuring is a well-established approach to improve the thermoelectric behavior of materials. Thermoelectric effect ; Materials science ; Thermoelectric materials ; Nanotechnology ; Engineering physics ; Optoelectronics ; Composite material ; Thermal conductivity ; Engineering ; Physics ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Chalcogenide Semiconductor Thin Films ; Quantum Dots Synthesis And Properties
Authors: Aokai Zhang | Xiuling Yang | Feng Yang | Chunmei Zhang | Qixiong Zhang | Gaigai Duan | Shaohua Jiang
Source: Molecules (review, 2023-02-22)
Field: Chemistry — Physical and Theoretical Chemistry

Research Progress of the Ion Activity Coefficient of Polyelectrolytes: A Review Polyelectrolyte has wide applications in biomedicine, agriculture and soft robotics. However, it is among one of the least understood physical systems because of the complex interplay of electrostatics and polymer nature. In this review, a comprehensive description is presented on experimental and theoretical studies of the activity coefficient, one of the most important thermodynamic properties of polyelectrolyte. Experimental methods to measure the activity coefficient were introduced, including direct potentiometric measurement and indirect methods such as isopiestic measurement and solubility measurement. Next, progress on the various theoretical approaches was presented, ranging from analytical, empirical and simulation methods. Finally, challenges for future development are proposed on this field. Polyelectrolyte ; Potentiometric titration ; Nanotechnology ; Materials science ; Biochemical engineering ; Chemistry ; Polymer ; Ion ; Engineering ; Organic chemistry Electrostatics and Colloid Interactions ; Analytical Chemistry and Sensors ; Polymer Nanocomposite Synthesis and Irradiation
Authors: Shi‐Chao Qi | Zhen Sun | Zhihui Yang | Yunjie Zhao | Jiaxin Li | Xiao‐Qin Liu | Lin‐Bing Sun
Source: Research (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Photo-Responsive Carbon Capture over Metalloporphyrin-C <sub>60</sub> Metal-Organic Frameworks via Charge-Transfer Great efforts have been devoted to the study of photo-responsive adsorption, but its current methodology largely depends on the well-defined photochromic units and their photo-driven molecular deformation. Here, a methodology to fabricate nondeforming photo-responsive sorbents is successfully exploited. With C<sub>60</sub>-fullerene doping in metalloporphyrin metal-organic frameworks (PCN-M, M = Fe, Co, or Ni) and intensively interacting with the metalloporphyrin sites, effective charge-transfer can be achieved over the metalloporphyrin-C<sub>60</sub> architectures once excited by the light at 350 to 780 nm. The electron density distribution and the resultant adsorption activity are thus changed by excited states, which are also stable enough to meet the timescale of microscopic adsorption equilibrium. The charge-transfer over Co(II)-porphyrin-C<sub>60</sub> is proved to be more efficient than the Fe(II)- and Ni(II)-porphyrin-C<sub>60</sub> sites, as well as than all the metalloporphyrin sites, so the CO<sub>2</sub> adsorption capacity (CAC; at 0 °C and 1 bar) over the C<sub>60</sub>-doped PCN-Co can be largely improved from 2.05 mmol g<sup>-1</sup> in the darkness to 2.69 mmol g<sup>-1</sup> with light, increased by 31%, in contrast to photo-irresponsive CAC over all C<sub>60</sub>-undoped PCN-M sorbents and only the photo-loss CAC over C<sub>60</sub>. Porphyrin ; Fullerene ; Adsorption ; Metal-organic framework ; Photochemistry ; Excited state ; Doping ; Metal ; Electron transfer ; Carbon fibers ; Charge (physics) ; Materials science ; Chemistry ; Chemical physics ; Physical chemistry ; Organic chemistry ; Optoelectronics ; Atomic physics Porphyrin and Phthalocyanine Chemistry ; Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications
Authors: Wahid Zamani | Saeedeh Rastgar | Aliakbar Hedayati
Source: Scientific Reports (article, 2023-10-24)
Field: Materials Science — Materials Chemistry

Capability of TiO2 and Fe3O4 nanoparticles loaded onto Algae (Scendesmus sp.) as a novel bio-magnetic photocatalyst to degration of Red195 dye in the sonophotocatalytic treatment process under ultrasonic/UVA irradiation In this study, the magnetic photocatalyst Scendesmus/Fe<sub>3</sub>O<sub>4</sub>/TiO<sub>2</sub> was synthesized, and its sonophotocatalytic properties in relation to the degradation of the Red195 dye were evaluated. Particles were characterized using a scanning electron microscope (SEM), Fourier's transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), and a vibrating-sample magnetometer (VSM). At a pH of 5, a photocatalyst dosage of 100 mg, an initial R195 concentration of 100 mg/l, an ultrasound power of 38W, and an exposure time of 20 min, the maximum Red195 removal efficiency (100%) was achieved. After five cycles of recycling, the composite's sonophotocatalytic degradation stability for R195 remains above 95%. Experiments on scavenging indicate that electrons (h<sup>+</sup>) and hydroxyls (OH<sup>-</sup>) are indispensable decomposition agents. The removal of R195 by Scendesmus/Fe<sub>3</sub>O<sub>4</sub>/TiO<sub>2</sub> is consistent with the pseudo-first-order kinetic, Freundlich, and Henderson's isotherm models, as determined by kinetic and isotherm investigations. The negative activation enthalpy of the standard (ΔH°) illuminates the exothermic adsorption mechanism. The increase in standard Gibbs activation free energy (ΔG°) with increasing temperature reveals the process is not spontaneous. As indicated by the negative value of the standard entropy of activation (ΔS°), activation of the reactants resulted in a loss of freedom. Photocatalysis ; Scanning electron microscope ; Fourier transform infrared spectroscopy ; Freundlich equation ; Gibbs free energy ; Nuclear chemistry ; Enthalpy ; Materials science ; Analytical Chemistry (journal) ; Diffuse reflectance infrared fourier transform ; Chemical engineering ; Adsorption ; Chemistry ; Physical chemistry ; Composite material ; Chromatography ; Organic chemistry ; Catalysis ; Thermodynamics Ultrasound and Cavitation Phenomena ; TiO2 Photocatalysis and Solar Cells ; Advanced Photocatalysis Techniques
Authors: Tzu Yu Wang | Simon P. Neville | Michael S. Schuurman
Source: The Journal of Physical Chemistry Letters (article, 2023-08-24)
Field: Materials Science — Materials Chemistry

Machine Learning Seams of Conical Intersection: A Characteristic Polynomial Approach The machine learning of potential energy surfaces (PESs) has undergone rapid progress in recent years. The vast majority of this work, however, has been focused on the learning of ground state PESs. To reliably extend machine learning protocols to excited state PESs, the occurrence of seams of conical intersections between adiabatic electronic states must be correctly accounted for. This introduces a serious problem, for at such points, the adiabatic potentials are not differentiable to any order, complicating the application of standard machine learning methods. We show that this issue may be overcome by instead learning the coordinate-dependent coefficients of the characteristic polynomial of a simple decomposition of the potential matrix. We demonstrate that, through this approach, quantitatively accurate machine learning models of seams of conical intersection may be constructed. Conical intersection ; Intersection (aeronautics) ; Differentiable function ; Polynomial ; Conical surface ; Adiabatic process ; Potential energy ; Computer science ; Artificial intelligence ; Calculator ; Algorithm ; Mathematics ; Physics ; Geometry ; Mathematical analysis ; Engineering ; Quantum mechanics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies
Authors: R. Saravanan | T. Sathish | V. Vijayan | S. Rajkumar | Shubham Sharma | Changhe Li | Yanbin Zhang | Kamal Sharma | Sayed M. Eldin
Source: REVIEWS ON ADVANCED MATERIALS SCIENCE (article, 2023-01-01)
Field: Materials Science — Biomaterials

Eco-friendly MoS<sub>2</sub>/waste coconut oil nanofluid for machining of magnesium implants Abstract The cost of the coolant and its disposal cost are significant issues in metal machining processes. In biocompatible magnesium alloy-based medical implants and instrument manufacturing, the cost hikes are owing to the use of unconventional machining processes and computerised numerical control machines. This research aims to improve machinability performance and optimize process parameters for biocompatible magnesium implant manufacturing for biomedical applications using eco-friendly nanofluid of MoS 2 nanoparticles suspended in waste coconut oil. The nanofluid was prepared from the multiple times used waste coconut oil (waste) and was mixed with MoS 2 nanoparticles. The orthogonal array L16, Taguchi analysis, and analysis of variance were employed in experimental design and statistical optimization. The machinability performance was determined by measuring and comparing the responses like cutting force, feed force, surface roughness, cutting zone temperature, and tool wear. They were compared with machining using a nanofluid and conventional commercial coolant. The results reveal that the proposed method of machining improved machinability performance appreciably; therefore, the observations of the proposed method were used and the process parameters were optimized. Mathematical models were developed for the prediction of process parameters. The proposed method exhibited the average reduction of the cutting force by 68.23167 N, feed force requirements by 34.180 N, the cutting zone temperature by 60.435°C, the surface roughness by 0.118908 µm, and the tool wear by 039938 mg·h −1 . Machinability ; Materials science ; Nanofluid ; Machining ; Coolant ; Surface roughness ; Taguchi methods ; Orthogonal array ; Vegetable oil ; Coconut oil ; Environmentally friendly ; Composite material ; Nanoparticle ; Mechanical engineering ; Metallurgy ; Nanotechnology Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Advanced materials and composites
Authors: Fangfang Du | Yuan Gao | Xibo Zhang | Lili Wang
Source: ACS Omega (article, 2023-10-23)
Field: Materials Science — Materials Chemistry

Bismuth, Nitrogen-Codoped Carbon Dots as a Dual-Read Optical Sensing Platform for Highly Sensitive, Ultrarapid, Ratiometric Detection of Doxorubicin Doxorubicin (DOX) is a potent anticancer drug, but it has side effects on normal tissues, particularly myocardial cells. Therefore, it is crucial to detect the DOX concentration in body fluids for effective clinical treatment. In this work, N,Bi-codoped CDs (Bi,N-CDs) were synthesized through a one-step hydrothermal method to carbonize the raw materials of 2,4-dinitroaniline and bismuth nitrate. The resulting Bi,N-CDs showed a reduced emission at 490 nm and an enhanced emission at 590 nm in the presence of DOX. The ratio of fluorescence (FL) intensity (F<sub>590</sub>/F<sub>490</sub>) was found to be a reliable indicator of DOX concentration, ranging from 0.05 to 30 μM and 40-200 μM, with detection limits (LOD) of 34 and 24 nM, respectively. A ratiometric fluorescence nanoprobe was established for highly selective and sensitive detection of DOX using a specific electrostatic interaction and inner filter effect between Bi,N-CDs and DOX. Meanwhile, Bi,N-CDs exhibited a distinct color change ranging from yellow to orange-red when exposed to DOX, allowing for a colorimetric method to measure DOX levels in the range of 0.05-30 μM, with a detection limit of 169 nM. The probe was triumphantly used to monitor DOX in actual samples via a dual-mode optical sensing strategy. This study contributes to the development of heteroatom-doped CDs and expands their potential applications for detecting biological samples. Detection limit ; Nanoprobe ; Fluorescence ; Bismuth ; Doxorubicin ; Chemistry ; Analytical Chemistry (journal) ; Materials science ; Nuclear chemistry ; Nanotechnology ; Nanoparticle ; Chromatography ; Optics ; Organic chemistry Carbon and Quantum Dots Applications ; Advanced biosensing and bioanalysis techniques ; Graphene and Nanomaterials Applications
Authors: Y. G. Anusha | Lavanya Mulky
Source: Biofouling (review, 2023-11-26)
Field: Materials Science — Materials Chemistry

Biofilms and beyond: a comprehensive review of the impact of Sulphate Reducing Bacteria on steel corrosion Sulphate-reducing bacteria (SRB) are known to cause severe corrosion of steel structures in various industries, resulting in significant economic and environmental consequences. This review paper critically examines the impact of SRB-induced corrosion on steel, including the formation of SRB biofilms, the effect on different types of steel, and the various models developed to investigate this phenomenon. The role of environmental factors in SRB-induced corrosion, molecular techniques for studying SRBs, and strategies for mitigating corrosion are discussed. Additionally, the sustainability implications of SRB-induced corrosion and the potential use of alternative materials were explored. By examining the current state of knowledge on this topic, this review aims to provide a comprehensive understanding of the impact of SRB-induced corrosion on steel and identify opportunities for further research and development. Corrosion ; Sulfate-reducing bacteria ; Biofilm ; Environmental science ; Metallurgy ; Materials science ; Biochemical engineering ; Bacteria ; Engineering ; Geology ; Sulfate Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Metal Extraction and Bioleaching
Authors: Maike Eckhoff | Johannes V. Diedrich | Maike Mücke | Jonny Proppe
Source: The Journal of Physical Chemistry A (article, 2023-12-19)
Field: Materials Science — Materials Chemistry

Quantitative Structure–Reactivity Relationships for Synthesis Planning: The Benzhydrylium Case Selective and feasible reactions are among the top targets in synthesis planning. Mayr's approach to quantifying chemical reactivity has greatly facilitated the planning process, but reactivity parameters for new compounds require time-consuming experiments. In the past decade, data-driven modeling has been gaining momentum in the field, as it shows promise in terms of efficient reactivity prediction. However, state-of-the-art models use quantum chemical data as input, which prevent access to real-time planning in organic synthesis. Here, we present a novel data-driven workflow for predicting reactivity parameters of molecules that takes only structural information as input, enabling <i>de facto</i> real-time reactivity predictions. We use the well-understood chemical space of benzhydrylium ions as an example to demonstrate the functionality of our approach and the performance of the resulting quantitative structure-reactivity relationships (QSRRs). Our results suggest that it is straightforward to build low-cost QSRR models that are accurate, interpretable, and transferable to unexplored systems within a given scope of application. Moreover, our QSRR approach suggests that Hammett σ parameters are only approximately additive. Reactivity (psychology) ; Computer science ; Scope (computer science) ; Workflow ; Process (computing) ; Biochemical engineering ; Field (mathematics) ; Chemistry ; Biological system ; Machine learning ; Data mining ; Mathematics ; Database Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Zhenzhen Liu | Xiaofei Lu | Menglin Liu | Wenjing Wang
Source: Molecules (article, 2023-03-26)
Field: Materials Science — Materials Chemistry

Blue, Yellow, and Red Carbon Dots from Aromatic Precursors for Light-Emitting Diodes In this work, multicolor fluorescent carbon dots with red (R-CDs), yellow (Y-CDs), and blue (B-CDs) emissions were prepared by choosing proper aromatic precursors with different amounts of benzene rings through a simple solvothermal method. The characterization showed that the prepared carbon dots were spherical with a size under 10 nm, rich surface functional groups, and good stability. The emission wavelengths were located at 440, 530, and 580 nm under the excitation of 370 nm. The relative fluorescence quantum yield (<i>QY</i>) of R-CDs, Y-CDs, and B-CDs was 11%, 59%, and 33%, respectively. The related characterization demonstrated that the redshift in the photoluminescence was caused by the synergistic effect of the increasing graphitic nitrogen content, quantum size effect and surface oxidation state. By mixing the three prepared CDs into a PVA matrix, the transparent and flexible films produced relucent blue, yellow, and red emissions under 365 nm UV light, and solid-state quenching was effectively avoided. LEDs were fabricated by using B-CDs, Y-CDs, and R-CDs/PVA with a semiconductor chip. These CDs-based LEDs produced bright blue, yellow, and red light with CIE color coordinates of (0.16, 0.02), (0.38, 0.58), and (0.50, 0.49) were successfully manufactured utilizing the prepared blue, yellow and red multicolor carbon dots as the solid luminescent materials. The results showed that the synthesized CDs can be potentially applied in multi-color monitors as a promising candidate for light-emitting diodes (LEDs). This work blazes a novel trail for the controllable preparation of multicolor fluorescent carbon dots. Light-emitting diode ; Materials science ; Fluorescence ; Photoluminescence ; Quantum yield ; Carbon fibers ; Luminescence ; Quantum dot ; Photochemistry ; Diode ; Quenching (fluorescence) ; Optoelectronics ; Analytical Chemistry (journal) ; Chemistry ; Optics ; Organic chemistry Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Luminescence and Fluorescent Materials