jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zenghe Li | D. Pei | Rui Tian | Chao Lu
Source: Chemosensors (article, 2023-05-14)
Field: Chemistry — Inorganic Chemistry

Screening the Specific Surface Area for Metal-Organic Frameworks by Cataluminescence Metal-organic frameworks (MOFs) are famous for their large surface area, which is responsible for the dispersed active sites and decent behaviors in gas adsorption, storage, and catalytic reactions. However, it remains a great challenge to acquire a cost-effective and accurate evaluation on the surface area for the MOFs. In this work, we have proposed cataluminescence (CTL) to evaluate the specific surface area for the MOFs, based on the adsorption–desorption and the catalytic reaction of ethanol. Aluminum-based MOFs with large-pore (lp), narrow-pore (np), and medium-pore (mp-130, mp-140, and mp-150 synthesized under 130, 140, and 150 °C) have been prepared. Distinguished CTL signals were acquired from ethanol in the presence of these MOFs: lp &gt; mp-150 &gt; mp-130 &gt; mp-140 &gt; np. Note that the CTL intensities were positively correlated with the specific surface areas of these MOFs acquired by the Brunauer–Emmett–Teller (BET) method. The distinct specific surface area of MOFs determined the capacity to accommodate and activate ethanol, leading to the varied CTL intensity signals. Therefore, the proposed CTL could be utilized for the rapid and accurate evaluation of the specific surface area for MOFs. It is believed that this CTL strategy showed great possibilities in the structural evaluation for various porous materials. CTL* ; Metal-organic framework ; Adsorption ; Specific surface area ; Catalysis ; Desorption ; Nanotechnology ; Porosity ; Materials science ; BET theory ; Chemistry ; Chemical engineering ; Organic chemistry ; Biochemistry Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Catalytic Processes in Materials Science
Authors: Sébastien Tourlet | Ragousandirane Radjasandirane | Julien Diharce | Alexandre G. de Brevern
Source: BioMedInformatics (article, 2023-05-09)
Field: Materials Science — Materials Chemistry

AlphaFold2 Update and Perspectives Access to the three-dimensional (3D) structural information of macromolecules is of major interest in both fundamental and applied research. Obtaining this experimental data can be complex, time consuming, and costly. Therefore, in silico computational approaches are an alternative of interest, and sometimes present a unique option. In this context, the Protein Structure Prediction method AlphaFold2 represented a revolutionary advance in structural bioinformatics. Named method of the year in 2021, and widely distributed by DeepMind and EBI, it was thought at this time that protein-folding issues had been resolved. However, the reality is slightly more complex. Due to a lack of input experimental data, related to crystallographic challenges, some targets have remained highly challenging or not feasible. This perspective exercise, dedicated to a non-expert audience, discusses and correctly places AlphaFold2 methodology in its context and, above all, highlights its use, limitations, and opportunities. After a review of the interest in the 3D structure and of the previous methods used in the field, AF2 is brought into its historical context. Its spatial interests are detailed before presenting precise quantifications showing some limitations of this approach and finishing with the perspectives in the field. Context (archaeology) ; Computer science ; Field (mathematics) ; Data science ; Perspective (graphical) ; Folding (DSP implementation) ; Artificial intelligence ; Engineering ; Mathematics ; Biology Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Federica Angiolari | Simon Huppert | Fabio Pietrucci | Riccardo Spezia
Source: The Journal of Physical Chemistry Letters (article, 2023-05-30)
Field: Chemistry — Spectroscopy

Environmental and Nuclear Quantum Effects on Double Proton Transfer in the Guanine–Cytosine Base Pair In the present letter, we investigate the double proton transfer (DPT) tautomerization process in guanine-cytosine (GC) DNA base pairs. In particular, we study the influence of the biological environment on the mechanism, the kinetics and thermodynamics of such DPT. To this end, we present a molecular dynamics (MD) study in the tight-binding density functional theory framework, and compare the reactivity of the isolated GC dimer with that of the same dimer embedded in a small DNA structure. The impact of nuclear quantum effects (NQEs) is also evaluated using Path Integral based MD. Results show that in the isolated dimer, the DPT occurs via a concerted mechanism, while in the model biological environment, it turns into a stepwise process going through an intermediate structure. One of the water molecules in the vicinity of the proton transfer sites plays an important role as it changes H-bond pattern during the DPT reaction. The inclusion of NQEs has the effect of speeding up the tautomeric-to-canonical reaction, reflecting the destabilization of both the tautomeric and intermediate forms. Guanine ; Cytosine ; Proton ; Base (topology) ; Base pair ; Transfer (computing) ; Chemistry ; Physics ; DNA ; Quantum mechanics ; Computer science ; Nucleotide ; Biochemistry ; Mathematics Advanced NMR Techniques and Applications ; Muon and positron interactions and applications ; DNA and Nucleic Acid Chemistry
Authors: Musa Muhammed | Mousa Javidani | Majid Heidari | Mohammad Jahazi
Source: Metals (review, 2023-08-14)
Field: Materials Science — Materials Chemistry

Enhancing the Tribological Performance of Tool Steels for Wood-Processing Applications: A Comprehensive Review The stochastic nature of tool wear during wood machining, owing to the dynamic properties of the biological material and its dependence on various factors, has raised significant industrial and research concerns in recent years. Explicitly, the tool wear is a product of the interaction between wood properties (such as hardness, density, and contamination level) and machining parameters (such as cutting speed, feed rate, and rake angle) alongside ambient conditions (such as temperature and humidity). The objective of this review paper is to provide an overview of recent advancements in the field of wood machining. To begin with, it highlights the important role of wood properties and ambient conditions influencing tool wear. Furthermore, the paper examines the various mechanisms involved in the wood-machining process and discusses their cost implications from an industrial perspective. It also covers technological advancements in the characterization of tool wear and explores the relationship between this parameter and other machining variables. It provides critical and analytical discussions on various methods for enhancing tool wear, including heat treatment, cryogenic treatment, thermochemical treatment, coating deposition, and hybrid treatments. Additionally, the paper incorporates statistical analysis to achieve two objectives. Firstly, it aims to identify the most significant wood property that affects tool wear and establish the correlation between this parameter and wood properties. Secondly, it investigates the effect of heat treatment parameters and carbide characteristics on tool wear as well as their correlation. Lastly, the review provides recommendations based on relevant literature for prospective researchers and industrial counterparts in the field. These recommendations aim to guide further exploration and practical applications in the subject matter. Machining ; Tool wear ; Rake angle ; Process engineering ; Mechanical engineering ; Tribology ; Characterization (materials science) ; Materials science ; Computer science ; Engineering ; Nanotechnology Metal Alloys Wear and Properties ; Advanced machining processes and optimization ; Advanced materials and composites
Authors: Jack Penny | Mohammad Arefian | Gunnar N. Schroeder | José A. Bengoechea | Ben C. Collins
Source: PROTEOMICS (article, 2023-03-06)
Field: Chemistry — Spectroscopy

A gas phase fractionation acquisition scheme integrating ion mobility for rapid diaPASEF library generation Data independent acquisition (DIA/SWATH) MS is a primary strategy in quantitative proteomics. diaPASEF is a recent adaptation using trapped ion mobility spectrometry (TIMS) to improve selectivity/sensitivity. Complex DIA spectra are typically analyzed with reference to spectral libraries. The best-established method for generating libraries uses offline fractionation to increase depth of coverage. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow DIA windows that cover different mass ranges of the complete precursor space, have been introduced that performed comparably to deep offline fractionation-based libraries. We investigated whether an analogous GPF-based approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data. We developed a rapid library generation approach using an IM-GPF acquisition scheme in the m/z versus 1/K0 space requiring seven injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation. We found that library generation by IM-GPF outperformed direct library generation from diaPASEF and had performance approaching that of the deep library. This establishes the IM-GPF scheme as a pragmatic approach to rapid library generation for analysis of diaPASEF data. Fractionation ; Ion-mobility spectrometry ; Computer science ; Sample (material) ; Mass spectrometry ; Chemistry ; Chromatography Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Alexander Heiss | Venkat Sai Thatikonda | A. Richter | Lisa-Yvonn Schmitt | Daesung Park | Ulrich Klotz
Source: Materials (article, 2023-04-18)
Field: Materials Science — Biomaterials

Development, Processing and Aging of Novel Zn-Ag-Cu Based Biodegradable Alloys The use of biodegradable materials for implants is a promising strategy to overcome known long-term clinical complications related to permanent implants. Ideally, biodegradable implants support the damaged tissue for a certain period and then degrade, while the physiological function of the surrounding tissue is restored. Although Mg-based alloys nearly ideally lend themselves to biodegradable implants, a few critical shortcomings promoted the development of alternative alloy systems. Due to their reasonably good biocompatibility, moderate corrosion rate without hydrogen evolution and adequate mechanical properties, increasing attention has been paid to Zn alloys. In this work, precipitation-hardening alloys in the system Zn-Ag-Cu were developed relying on thermodynamic calculations. After casting the alloys, their microstructures were refined by thermomechanical treatment. The processing was tracked and directed, respectively, by routine investigations of the microstructure, associated with hardness assessments. Although microstructure refinement increased the hardness, the material proved to be susceptible to aging as the homologous temperature of zinc is at 0.43 T<sub>m</sub>. Besides mechanical performance and corrosion rate, long-term mechanical stability is another crucial factor that must be taken into consideration to ensure the safety of the implant and thus requires a profound understanding of the aging process. Materials science ; Microstructure ; Alloy ; Corrosion ; Biocompatibility ; Metallurgy ; Precipitation ; Precipitation hardening ; Casting Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; Corrosion Behavior and Inhibition
Authors: Qi Chen | Kailai Yang | Liang Meng | Junjie Kang | Xiaoyan Yi | Junxi Wang | Jinmin Li | Zhiqiang Liu
Source: Nano Convergence (review, 2023-08-25)
Field: Materials Science — Materials Chemistry

Lattice modulation strategies for 2D material assisted epitaxial growth As an emerging single crystals growth technique, the 2D-material-assisted epitaxy shows excellent advantages in flexible and transferable structure fabrication, dissimilar materials integration, and matter assembly, which offers opportunities for novel optoelectronics and electronics development and opens a pathway for the next-generation integrated system fabrication. Studying and understanding the lattice modulation mechanism in 2D-material-assisted epitaxy could greatly benefit its practical application and further development. In this review, we overview the tremendous experimental and theoretical findings in varied 2D-material-assisted epitaxy. The lattice guidance mechanism and corresponding epitaxial relationship construction strategy in remote epitaxy, van der Waals epitaxy, and quasi van der Waals epitaxy are discussed, respectively. Besides, the possible application scenarios and future development directions of 2D-material-assisted epitaxy are also given. We believe the discussions and perspectives exhibited here could help to provide insight into the essence of the 2D-material-assisted epitaxy and motivate novel structure design and offer solutions to heterogeneous integration via the 2D-material-assisted epitaxy method. Epitaxy ; Materials science ; Nanotechnology ; van der Waals force ; Fabrication ; Molecular beam epitaxy ; Lattice (music) ; Optoelectronics ; Engineering physics ; Chemistry ; Physics 2D Materials and Applications ; MXene and MAX Phase Materials ; Electronic and Structural Properties of Oxides
Authors: Ying Pan | Mengfan Wu | Mingjiao Shi | Peizheng Shi | Ningbin Zhao | Yangguang Zhu | Hassan Karimi‐Maleh | Chen Ye | Cheng‐Te Lin | Li Fu
Source: Sensors (review, 2023-10-23)
Field: Chemistry — Electrochemistry

An Overview to Molecularly Imprinted Electrochemical Sensors for the Detection of Bisphenol A Bisphenol A (BPA) is an industrial chemical used extensively in plastics and resins. However, its endocrine-disrupting properties pose risks to human health and the environment. Thus, accurate and rapid detection of BPA is crucial for exposure monitoring and risk mitigation. Molecularly imprinted electrochemical sensors (MIES) have emerged as a promising tool for BPA detection due to their high selectivity, sensitivity, affordability, and portability. This review provides a comprehensive overview of recent advances in MIES for BPA detection. We discuss the operating principles, fabrication strategies, materials, and methods used in MIES. Key findings show that MIES demonstrate detection limits comparable or superior to conventional methods like HPLC and GC-MS. Selectivity studies reveal excellent discrimination between BPA and structural analogs. Recent innovations in nanomaterials, novel monomers, and fabrication techniques have enhanced sensitivity, selectivity, and stability. However, limitations exist in reproducibility, selectivity, and stability. While challenges remain, MIES provide a low-cost portable detection method suitable for on-site BPA monitoring in diverse sectors. Further optimization of sensor fabrication and characterization will enable the immense potential of MIES for field-based BPA detection. Molecularly imprinted polymer ; Software portability ; Bisphenol A ; Nanotechnology ; Computer science ; Selectivity ; Biochemical engineering ; Chemistry ; Materials science ; Engineering Electrochemical Analysis and Applications ; Analytical chemistry methods development ; Advanced biosensing and bioanalysis techniques
Authors: Devi Stuart‐Fox | Leslie Ng | Leonie Barner | Andrew T. D. Bennett | Sean J. Blamires | Mark A. Elgar | Alistair R. Evans | Amanda M. Franklin | Katja Hölttä‐Otto | James A. Hutchison | Fernando Jativa | Anna-Lee Jessop | Jennifer L. Kelley | Janet McGaw | Jun Mei | Mohammad Mirkhalaf | Mustafa Musameh | Chiara Neto | Andrea J. O’Connor | Tim Schork | Gerd E. Schröder‐Turk | Nicolas H. Voelcker | Anna Wang | Gregory S. Watson | Jolanta A. Watson | Lukas Wesemann | Wallace W. H. Wong
Source: Communications Materials (article, 2023-10-04)
Field: Materials Science — Biomaterials

Challenges and opportunities for innovation in bioinformed sustainable materials Abstract Nature provides a rich source of information for the design of novel materials; yet there remain significant challenges in the design and manufacture of materials that replicate the form, function, and sustainability of biological solutions. Here, we identify key challenges and promising approaches to the development of materials informed by biology. These challenges fall into two main areas; the first relates to harnessing biological information for materials innovation, including key differences between biological and synthetic materials, and the relationship between structure and function. We propose an approach to materials innovation that capitalizes on biodiversity, together with high-throughput characterization of biological material architectures and properties, linked to environmental and ecological context. The second area relates to the design and manufacture of bioinformed materials, including the physical scale of material architectures and manufacturing scale up. We suggest ways to address these challenges and promising prospects for a bioinformed approach to materials innovation. Context (archaeology) ; Sustainability ; Biological materials ; Function (biology) ; Scale (ratio) ; Nanotechnology ; Computer science ; Key (lock) ; Biochemical engineering ; Data science ; Engineering ; Knowledge management ; Ecology ; Materials science ; Biology Diatoms and Algae Research ; Cephalopods and Marine Biology ; Calcium Carbonate Crystallization and Inhibition
Authors: Kaynan Maresch | Luiz Fernando Freitas-Gutierres | Aécio L. Oliveira | AQUILES SACCOL BORIN | Ghendy Cardoso | Juliano S. Damiani | André M. de Morais | Cristian H. Correa | Erick F. Martins
Source: Energies (article, 2023-08-17)
Field: Materials Science — Materials Chemistry

Advanced Diagnostic Approach for High-Voltage Insulators: Analyzing Partial Discharges through Zero-Crossing Rate and Fundamental Frequency Estimation of Acoustic Raw Data Acoustic inspection is a valuable technique that can detect early stage defects in equipment, thereby facilitating predictive maintenance. In recent times, ultrasonic sensors have made detecting partial discharges through acoustic sensing increasingly feasible. However, interpreting the acoustic signals can pose challenges, as it requires extensive expertise and knowledge of equipment configuration. To address this issue, a technique based on zero-crossing rate and fundamental frequency estimation has been proposed to standardize insulator diagnosis. In an experiment involving a database of 72 raw acoustic signals with frequencies ranging from 0 to 128 kHz, various types of pollution and defects were introduced to a chain of insulators. By employing the proposed technique, the occurrence of partial discharges can be detected and classified according to type, such as corona or surface discharges. This advanced approach to diagnosis simplifies the process while providing valuable insights into the severity of observed phenomena in the field. Partial discharge ; Acoustics ; Computer science ; Ultrasonic sensor ; Process (computing) ; Ranging ; Zero crossing ; Insulator (electricity) ; Voltage ; Engineering ; Electrical engineering ; Telecommunications ; Physics High voltage insulation and dielectric phenomena ; Non-Destructive Testing Techniques ; Power Transformer Diagnostics and Insulation
Authors: Akinbode A. Adedeji | Abuchi G. Okeke | Ahmed Rady
Source: Sustainability (article, 2023-05-29)
Field: Chemistry — Analytical Chemistry

Utilization of FTIR and Machine Learning for Evaluating Gluten-Free Bread Contaminated with Wheat Flour In this study, Fourier-transform infrared (FTIR) spectroscopy coupled with machine learning (ML) approaches were applied to detect and quantify wheat flour (WF) contamination in gluten-free cornbread. Samples of corn flour (CF) were contaminated with WF in the range of 0–10% with a 0.5% increment. The flour samples were baked into bread using basic bread formulation and ground into a fine particle size for homogeneity, and FTIR spectra of the ground samples were obtained and standardized before modeling. For constructing the classification model, majority voting-based ensemble learning (stack of k-nearest neighbor [KNN], random forest, and support vector classifier) was implemented to detect and quantify WF in the cornbread samples. KNN regressor was determined to be the best predictive model to quantify wheat contaminants based on the majority-vote ensemble. The optimal classification model for the test set showed an F1 score, true positive rate (TPR), and false negative rate (FNR) of 1.0, 1.0, and 0.0, respectively. For the quantification models, the coefficient of determination and root mean square error for the prediction set (R2P and RMSEP) were 0.99 and 0.34, respectively. These results show the feasibility of utilizing FTIR along with supervised learning algorithms for the rapid offline evaluation of wheat flour contamination in gluten-free products. Mathematics ; Fourier transform infrared spectroscopy ; Gluten ; Support vector machine ; Contamination ; Wheat flour ; Artificial intelligence ; Food science ; Chemistry ; Computer science ; Engineering Spectroscopy and Chemometric Analyses ; Food composition and properties ; Meat and Animal Product Quality
Authors: Chen Niu | Mario Phaneuf | Tianke Qiu | Puyan Mojabi
Source: IEEE Open Journal of Antennas and Propagation (article, 2023-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Deep Learning-Based Approach to Design Metasurfaces From Desired Far-Field Specifications A deep learning neural network model in conjunction with a method to incorporate auxiliary surface waves is developed for the macroscopic design of transmitting metasurfaces. The main input to the neural network model is the user-defined desired far-field specifications. This network is used to calculate the required tangential electromagnetic fields on the metasurface. These fields will then be augmented by incorporating auxiliary surface waves along the metasurface for power redistribution to satisfy the requirement for having lossless and passive metasurfaces. The designs will then be evaluated using full-wave simulations of metasurfaces with three-layer unit cell topology in both 2D and 3D scenarios. Near and far field ; Computer science ; Field (mathematics) ; Artificial intelligence ; Systems engineering ; Engineering ; Physics ; Optics ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis