jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ergys Pahija | Soonho Hwangbo | Thomas Saulnier‐Bellemare | Gregory S. Patience
Source: The Canadian Journal of Chemical Engineering (article, 2024-06-26)
Field: Materials Science — Materials Chemistry

Experimental methods in chemical engineering: Monte Carlo Abstract Monte Carlo (MC) methods employ a statistical approach to evaluate complex mathematical models that lack analytical solutions and assess their uncertainties. To this end, techniques such as Markov chain Monte Carlo (MCMC), bootstrap, and sequential MC methods repeat the same operations over a specified range of conditions. Consequently, both the frequentist and Bayesian statistical approaches are computationally intensive, depending on the problem formulation. Improving sampling techniques and identifying sources of error reduce the computational demand but do not guarantee that the solution reaches the global optimum. Moreover, efficient algorithms and advances in hardware continue to decrease computation time. MC methods are applicable to a plethora of problems ranging from medicine to computational chemistry, economics, and industrial safety, making them integral to the ongoing industrial digitalization by evaluating the quality of applied models. In chemical engineering, MC simulations are used in four clusters of research: design, systems, and optimization; molecular simulation, including CO 2 and carbon capture; adsorption and molecular dynamics; and thermodynamics. There is limited cross‐referencing between the design cluster and the other three, which presents an interesting area for future research. This mini‐review presents two applications within chemical engineering: emissions and energy forecasting. Monte Carlo method ; Computer science ; Markov chain Monte Carlo ; Frequentist inference ; Sampling (signal processing) ; Range (aeronautics) ; Uncertainty quantification ; Bayesian inference ; Mathematical optimization ; Bayesian probability ; Machine learning ; Engineering ; Mathematics ; Artificial intelligence Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Carbon Dioxide Capture Technologies
Authors: Huiyuan Liang | Yijie Xian | Xujing Wang
Source: Frontiers in Chemistry (review, 2024-08-12)
Field: Materials Science — Materials Chemistry

Preparation and application of single-atom nanozymes in oncology: a review Single-atom nanozymes (SAzymes) represent a cutting-edge advancement in nanomaterials, merging the high catalytic efficiency of natural enzymes with the benefits of atomic economy. Traditionally, natural enzymes exhibit high specificity and efficiency, but their stability are limited by environmental conditions and production costs. Here we show that SAzymes, with their large specific surface area and high atomic utilization, achieve superior catalytic activity. However, their high dispersibility poses stability challenges. Our review focuses on recent structural and preparative advancements aimed at enhancing the catalytic specificity and stability of SAzymes. Compared to previous nanozymes, SAzymes demonstrate significantly improved performance in biomedical applications, particularly in tumor medicine. This progress positions SAzymes as a promising tool for future cancer treatment strategies, integrating the robustness of inorganic materials with the specificity of biological systems. The development and application of SAzymes could revolutionize the field of biocatalysis, offering a stable, cost-effective alternative to natural enzymes. Nanotechnology ; Biochemical engineering ; Nanomaterials ; Robustness (evolution) ; Biocatalysis ; Computer science ; Catalytic efficiency ; Catalysis ; Chemistry ; Materials science ; Computational biology ; Biology ; Engineering ; Biochemistry Advanced Nanomaterials in Catalysis ; Nanocluster Synthesis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Krista M. Kulesa | Erin Hirtzel | Vinh T. Nguyen | Dallas Freitas | Madison E. Edwards | Xin Yan | Lane A. Baker
Source: Analytical Chemistry (article, 2024-05-08)
Field: Chemistry — Electrochemistry

Interfacing High-Throughput Electrosynthesis and Mass Spectrometric Analysis of Azines Combinatorial electrochemistry has great promise for accelerated reaction screening, organic synthesis, and catalysis. Recently, we described a new high-throughput electrochemistry platform, colloquially named "Legion". Legion fits the footprint of a 96-well microtiter plate with simultaneous individual control over all 96 electrochemical cells. Here, we demonstrate the versatility of Legion when coupled with high-throughput mass spectrometry (MS) for electrosynthetic product screening and quantitation. Electrosynthesis of benzophenone azine was selected as a model reaction and was arrayed and optimized using a combination of Legion and nanoelectrospray ionization MS. The combination of high-throughput synthesis with Legion and analysis via MS proves a compelling strategy for accelerating reaction discovery and optimization in electro-organic synthesis. Electrosynthesis ; Chemistry ; Throughput ; Mass spectrometry ; Benzophenone ; Electrochemistry ; Interfacing ; Combinatorial chemistry ; High-throughput screening ; Microtiter plate ; Nanotechnology ; Chromatography ; Organic chemistry ; Electrode ; Computer hardware Electrochemical Analysis and Applications ; Innovative Microfluidic and Catalytic Techniques Innovation ; Radical Photochemical Reactions
Authors: Mary Hashemitaheri | Ebrahim Ebrahimi | G. Silva | Hamed Attariani
Source: Advanced Sensor and Energy Materials (article, 2024-06-20)
Field: Chemistry — Spectroscopy

Optical sensor for BTEX detection: Integrating machine learning for enhanced sensing Optical sensors provide a fast and real-time approach to detect benzene, toluene, ethylbenzene, and xylenes (BTEX) in environmental monitoring and industrial safety. However, detecting the concentration of a particular gas in a mixture can be challenging. Here, we develop a machine-learning model that can precisely measure BTEX concentrations simultaneously based on an absorption spectroscopy gas sensing system. The convolutional neural network (CNN) is utilized to identify the absorbance spectra for each volatile, along with their concentrations in a mixture. A synthetic data set is generated using a series of physics-based simulations to create the predictive model. The data set consists of the overall absorbance of numerous random BTEX mixtures over time, based on various percentages of the permissible exposure limit (PEL). It is worth noting that benzene has a negligible absorbance (very low PEL, 1-5 ppm) compared to other volatile gases, which makes it difficult to detect. To address this challenge, we introduce a 3-stage solution to accurately discriminate between all BTEX species, regardless of their concentration levels. As a result, the <i>R</i>-squared above 0.99 for toluene, ethylbenzene, and <i>o</i>-xylene, and the <i>R</i>-squared above 0.96 for benzene, is achieved, indicating the model's capability to predict BTEX concentrations. BTEX ; Computer science ; Chemical sensor ; Environmental science ; Remote sensing ; Artificial intelligence ; Machine learning ; Chemistry ; Geology ; Ethylbenzene ; Benzene Spectroscopy and Laser Applications ; Advanced Fiber Optic Sensors ; Gas Sensing Nanomaterials and Sensors
Authors: Si‐Min Lu | Jean‐Marc Noël | Jean‐François Lemineur
Source: Current Opinion in Electrochemistry (article, 2024-04-15)
Field: Chemistry — Electrochemistry

Collision electrochemistry: A simple methodology for investigating complex processes Simplicity ; Computer science ; Collision ; Biological system ; Nanotechnology ; Biochemical engineering ; Transient (computer programming) ; Simple (philosophy) ; Mechanism (biology) ; Materials science ; Physics ; Biology Electrochemical Analysis and Applications ; Conducting polymers and applications ; Electrochemical sensors and biosensors
Authors: Supriya Atta | Tuan Vo‐Dinh
Source: Talanta (article, 2024-06-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Improved solution-based SERS detection of creatinine by inducing hydrogen-bonding interaction for effective analyte capture Chemistry ; Detection limit ; Analyte ; Biomolecule ; Nanotechnology ; Silver nanoparticle ; Creatinine ; Chromatography ; Nanoparticle ; Materials science Gold and Silver Nanoparticles Synthesis and Applications ; Biosensors and Analytical Detection ; Advanced Nanomaterials in Catalysis
Authors: Hussaini Adam | Subash C.B. Gopinath | Tijjani Adam | Makram A. Fakhri | Evan T. Salim | Sreeramanan Subramanıam
Source: Heliyon (article, 2024-03-01)
Field: Materials Science — Polymers and Plastics

Exploring faradaic and non-faradaic electrochemical impedance spectroscopy approaches in Parkinson's disease diagnosis Parkinson's disease is a neurodegenerative condition defined by the progressive death of dopaminergic neurons in the brain. The diagnosis of Parkinson's disease often uses time-consuming clinical evaluations and subjective assessments. Electrochemical Impedance Spectroscopy (EIS) is a useful technique for electroanalytical devices due to its label-free performance, in-situ measurements, and low cost. The development of reliable diagnostic tools for Parkinson's disease can be significantly enhanced by exploring novel techniques like faradaic and non-faradaic EIS detection methods. These techniques have the ability to identify specific biomarkers or changes in electrochemical properties linked to Parkinson's disease, allowing for an early and accurate diagnosis. Faradaic EIS detection methods utilize redox processes on the electrode surface, while non-faradaic EIS methods rely on charge transfer or capacitive properties. EIS can identify biomarkers or changes in electrical properties as indicators of Parkinson's disease by measuring impedance at different frequencies. By combining both faradaic and non-faradaic EIS approaches, it may be possible to obtain a comprehensive understanding of the electrochemical changes occurring in Parkinson's disease patients. This may lead to the development of more effective diagnostic techniques and potentially opening up new avenues for personalized treatment strategies. This review explores the current research on faradaic and non-faradaic EIS approaches for diagnosing Parkinson's disease using electrochemical impedance spectroscopy. Faradaic current ; Dielectric spectroscopy ; Parkinson's disease ; Disease ; Medicine ; Chemistry ; Electrochemistry ; Electrode ; Electrode potential ; Internal medicine Conducting polymers and applications ; Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors
Authors: Natalia G. Baranska | Bryn Jones | Mark R. Dowsett | Christopher N. Rhodes | Darrell Elton | Jie Zhang | Alan M. Bond | David J. Gavaghan | Henry Lloyd-Laney | Alison Parkin
Source: ACS Measurement Science Au (article, 2024-05-07)
Field: Chemistry — Electrochemistry

Practical Guide to Large Amplitude Fourier-Transformed Alternating Current Voltammetry─What, How, and Why Fourier-transformed alternating current voltammetry (FTacV) is a technique utilizing a combination of a periodic (frequently sinusoidal) oscillation superimposed onto a staircase or linear potential ramp. The advanced utilization of a large amplitude sine wave induces substantial nonlinear current responses. Subsequent filter processing (via Fourier-transformation, band selection, followed by inverse Fourier-transformation) generates a series of harmonics in which rapid electron transfer processes may be separated from non-Faradaic and competing electron transfer processes with slower kinetics. Thus, FTacV enables the isolation of current associated with redox processes under experimental conditions that would not generate meaningful data using direct current voltammetry (dcV). In this study, the enhanced experimental sensitivity and selectivity of FTacV versus dcV are illustrated in measurements that (i) separate the Faradaic current from background current contributions, (ii) use a low (5 μM) concentration of analyte (exemplified with ferrocene), and (iii) enable discrimination of the reversible [Ru(NH<sub>3</sub>)<sub>6</sub>]<sup>3+/2+</sup> electron-transfer process from the irreversible reduction of oxygen under a standard atmosphere, negating the requirement for inert gas conditions. The simple, homebuilt check-cell described ensures that modern instruments can be checked for their ability to perform valid FTacV experiments. Detailed analysis methods and open-source data sets that accompany this work are intended to facilitate other researchers in the integration of FTacV into their everyday electrochemical methodological toolkit. Faradaic current ; Fourier transform ; Analytical Chemistry (journal) ; Harmonics ; Voltammetry ; Chemistry ; Current (fluid) ; Fourier analysis ; Oscillation (cell signaling) ; Electron transfer ; Physics ; Electrochemistry ; Electrode ; Mathematics ; Thermodynamics ; Mathematical analysis ; Physical chemistry ; Working electrode ; Voltage Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Analytical Chemistry and Sensors
Authors: Emanuela Sgreccia | Francia Sarhaly Gallardo Gonzalez | P. Prosposito | Luca Burratti | Michele Sisani | Maria Bastianini | Philippe Knauth | Maria Luisa Di Vona
Source: Membranes (article, 2024-06-06)
Field: Materials Science — Materials Chemistry

Heavy Metal Detection and Removal by Composite Carbon Quantum Dots/Ionomer Membranes The combination of ion exchange membranes with carbon quantum dots (CQDs) is a promising field that could lead to significant advances in water treatment. Composite membranes formed by sulfonated poly(ether ether ketone) (SPEEK) with embedded CQDs were used for the detection and removal of heavy metal ions, such as lead and cadmium, from water. SPEEK is responsible for the capture of heavy metals based on the cation exchange mechanism, while CQDs detect their contamination by exhibiting changes in fluorescence. Water-insoluble "red" carbon quantum dots (rCQDs) were synthesized from p-phenylenediamine so that their photoluminescence was shifted from that of the polymer matrix. CQDs and the composites were characterized by several techniques: FTIR, Raman, UV/VIS, photoluminescence, XPS spectroscopies, and AFM microscopy. The heavy metal ion concentration was analyzed by inductively coupled plasma-optical emission spectroscopy (ICP-OES). The concentration ranges were 10.8-0.1 mM for Pb<sup>2+</sup> and 10.0-0.27 mM for Cd<sup>2+</sup>. SPEEK/rCQDs showed a more pronounced turn-off effect for lead. The composite achieved 100% removal efficiency for lead and cadmium when the concentration was below a half of the ion exchange capacity of SPEEK. The regeneration of membranes in 1 M NaCl was also studied. A second order law was effective to describe the kinetics of the process. Membrane ; Photoluminescence ; Raman spectroscopy ; Fourier transform infrared spectroscopy ; X-ray photoelectron spectroscopy ; Ion exchange ; Cadmium ; Metal ions in aqueous solution ; Materials science ; Inductively coupled plasma ; Carbon fibers ; Composite number ; Metal ; Analytical Chemistry (journal) ; Chemistry ; Chemical engineering ; Ion ; Composite material ; Organic chemistry ; Metallurgy ; Plasma Carbon and Quantum Dots Applications ; Electrochemical sensors and biosensors ; Advanced Nanomaterials in Catalysis
Authors: Diego Vergara | Γεώργιος Λαμπρόπουλος | Pablo Fernández‐Arias | Álvaro Antón‐Sancho
Source: Applied Sciences (review, 2024-09-10)
Field: Materials Science — Materials Chemistry

Artificial Intelligence Reinventing Materials Engineering: A Bibliometric Review The use of artificial intelligence (AI) is revolutionizing many professions and research fields. Thus, the present study focuses on the implications that AI is having on research in materials science and engineering (MSE). To this end, a bibliometric review has been conducted to analyze the advances that AI is generating in MSE. Although expectations for AI advances in the field of MSE are high, the results of this study indicate that we are still at a preliminary stage of development. It is worth highlighting that despite the progress made, the potential of AI in MSE has not been fully exploited and numerous challenges remain to be overcome to achieve effective and widespread implementation. It should be noted that the subarea “Materials structure, processing, and properties” is the one that currently presents the largest number of research works linked to AI. It appears that the United States and China are currently the countries with the greatest involvement in the use of AI in the field of MSE. The emerging themes and thematic map of the topic are revealed, and future research directions are provided. Engineering ; Engineering ethics Machine Learning in Materials Science ; Manufacturing Process and Optimization ; Advanced Materials Characterization Techniques
Authors: Hengnian Qi | Jiahao Luo | Xiaoping Wu | Chu Zhang
Source: Journal of Food Science (review, 2024-10-04)
Field: Chemistry — Analytical Chemistry

Application of nondestructive techniques for peach ( <i>Prunus persica</i> ) quality inspection: A review Peaches are highly valued for their rich nutritional content. Traditional fruit quality accessing methods (i.e., manual squeezing the fruit for firmness) are both subjective and destructive, which tend to diminish the integrity of fruit samples, consequently undermining their market value. Compared to traditional detection methods, nondestructive technology offers efficient and noninvasive solutions for rapidly and accurately assessing internal external quality of peaches. This can significantly enhance product classification and quality assurance while reducing the need for extensive human resources and minimizing potential physical damage to peaches. This review provided a comprehensive overview of nondestructive techniques for peach quality evaluation, including visible/near-infrared spectroscopy, machine vision technology, hyperspectral imaging, dielectric and optical properties, fluorescence spectroscopy, electronic nose/tongue, and acoustic vibration methods. It also evaluates the effectiveness of each technique in assessing internal quality, maturity, and disease detection of peaches. The advantages and limitations of each method were also summarized. This study focuses specifically on peaches and encompasses all existing nondestructive testing methods, providing valuable insights and references for future studies in the field of peach quality analysis using nondestructive testing methods. Nondestructive testing ; Quality assurance ; Hyperspectral imaging ; Quality (philosophy) ; Computer science ; Visual inspection ; Prunus ; Artificial intelligence ; Engineering ; Physics ; Operations management ; Biology ; Horticulture Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Plant Pathogens and Fungal Diseases
Authors: Murilo H. M. Facure | Gulnaz Gahramanova | Danzhen Zhang | Teng Zhang | Christopher E. Shuck | Luiza A. Mercante | Daniel S. Côrrea | Yury Gogotsi
Source: Biosensors and Bioelectronics (article, 2024-06-25)
Field: Materials Science — Materials Chemistry

All-MXene electronic tongue for neurotransmitters detection MXenes ; Electronic tongue ; Tongue ; Neuroscience ; Acetylcholine ; Glutamate receptor ; Chemistry ; Biology ; Medicine ; Pathology ; Biochemistry ; Pharmacology MXene and MAX Phase Materials ; Polydiacetylene-based materials and applications ; Advanced biosensing and bioanalysis techniques
Authors: Xinhui Jin | Siliang Yue | Jiangcheng Zhang | Liang Qian | Xiaohui Guo
Source: Nanomaterials (article, 2024-03-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Three-Dimensional Vanadium and Nitrogen Dual-Doped Ti3C2 Film with Ultra-High Specific Capacitance and High Volumetric Energy Density for Zinc-Ion Hybrid Capacitors Zinc-ion hybrid capacitors (ZICs) can achieve high energy and power density, ultralong cycle life, and a wide operating voltage window, and they are widely used in wearable devices, portable electronics devices, and other energy storage fields. The design of advanced ZICs with high specific capacity and energy density remains a challenge. In this work, a novel kind of V, N dual-doped Ti<sub>3</sub>C<sub>2</sub> film with a three-dimensional (3D) porous structure (3D V-, N-Ti<sub>3</sub>C<sub>2</sub>) based on Zn-ion pre-intercalation can be fabricated via a simple synthetic process. The stable 3D structure and heteroatom doping provide abundant ion transport channels and numerous surface active sites. The prepared 3D V-, N-Ti<sub>3</sub>C<sub>2</sub> film can deliver unexpectedly high specific capacitance of 855 F g<sup>-1</sup> (309 mAh g<sup>-1</sup>) and demonstrates 95.26% capacitance retention after 5000 charge/discharge cycles. In addition, the energy storage mechanism of 3D V-, N-Ti<sub>3</sub>C<sub>2</sub> electrodes is the chemical adsorption of H<sup>+</sup>/Zn<sup>2+</sup>, which is confirmed by ex situ XRD and ex situ XPS. ZIC full cells with a competitive energy density (103 Wh kg<sup>-1</sup>) consist of a 3D V-, N-Ti<sub>3</sub>C<sub>2</sub> cathode and a zinc foil anode. The impressive results provide a feasible strategy for developing high-performance MXene-based energy storage devices in various energy-related fields. Materials science ; Energy storage ; Cathode ; Anode ; Capacitance ; Heteroatom ; Capacitor ; Power density ; FOIL method ; Optoelectronics ; Nanotechnology ; Electrode ; Chemical engineering ; Composite material ; Voltage ; Electrical engineering ; Chemistry Supercapacitor Materials and Fabrication ; MXene and MAX Phase Materials ; Advancements in Battery Materials
Authors: Ali Shaan Manzoor Ghumman | Rashid Shamsuddin | Zeid A. ALOthman | Ammara Waheed | Ahmed Muteb Aljuwayid | Rabia Sabir | Amin Abbasi | Abdul Sami
Source: ACS Omega (article, 2024-01-17)
Field: Materials Science — Polymers and Plastics

Amine-Decorated Methacrylic Acid-based Inverse Vulcanized Polysulfide for Effective Mercury Removal from Wastewater Mercury [Hg(II)] contamination is an indefatigable global hazard that causes severe permanent damage to human health. Extensive research has been carried out to produce mercury adsorbents; however, they still face certain challenges, limiting their upscaling. Herein, we report the synthesis of a novel amine-impregnated inverse vulcanized copolymer for effective mercury removal. Poly(S-MA) was prepared using sulfur and methacrylic acid employing the inverse vulcanization method, followed by functionalization. The polyethylenimine (PEI) was impregnated on poly(S-MA) to increase the adsorption active sites. The adsorbent was then characterized byusing Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). FTIR spectroscopy confirmed the formation of the copolymer, and successful impregnation of PEI and SEM revealed the composite porous morphology of the copolymer. Amine-impregnated copolymer [amine@poly(S-MA)] outperformed poly(S-MA) in mercury as it showed 20% superior performance with 44.7 mg/g of mercury adsorption capacity. The adsorption data best fit the pseudo-second-order, indicating that chemisorption is the most effective mechanism, in this case, indicating the involvement of NH<sub>2</sub> in mercury removal. The adsorption is mainly a monolayer on a homogeneous surface as indicated by the 0.76 value of Redlich-Peterson exponent (<i>g</i>), which describes the adsorption nature advent from the <i>R</i><sup>2</sup> value of 0.99. Adsorption ; Copolymer ; Fourier transform infrared spectroscopy ; Mercury (programming language) ; Methacrylic acid ; Chemistry ; Amine gas treating ; Nuclear chemistry ; Polymer chemistry ; Chemical engineering ; Materials science ; Polymer ; Organic chemistry Synthesis and properties of polymers ; Membrane Separation and Gas Transport ; Covalent Organic Framework Applications