jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Akshansh Mishra | Vijaykumar S. Jatti | Vaishnavi More | Anish Dasgupta | Devarrishi Dixit | Eyob Messele Sefene
Source: arXiv (Cornell University) (preprint, 2023-11-06)
Field: Materials Science — Materials Chemistry

Performance Prediction of Data-Driven Knowledge summarization of High Entropy Alloys (HEAs) literature implementing Natural Language Processing algorithms The ability to interpret spoken language is connected to natural language processing. It involves teaching the AI how words relate to one another, how they are meant to be used, and in what settings. The goal of natural language processing (NLP) is to get a machine intelligence to process words the same way a human brain does. This enables machine intelligence to interpret, arrange, and comprehend textual data by processing the natural language. The technology can comprehend what is communicated, whether it be through speech or writing because AI pro-cesses language more quickly than humans can. In the present study, five NLP algorithms, namely, Geneism, Sumy, Luhn, Latent Semantic Analysis (LSA), and Kull-back-Liebler (KL) al-gorithm, are implemented for the first time for the knowledge summarization purpose of the High Entropy Alloys (HEAs). The performance prediction of these algorithms is made by using the BLEU score and ROUGE score. The results showed that the Luhn algorithm has the highest accuracy score for the knowledge summarization tasks compared to the other used algorithms. Automatic summarization ; Computer science ; Natural language processing ; Artificial intelligence ; Natural language ; Principle of maximum entropy ; Latent semantic analysis ; Process (computing) ; Programming language Machine Learning in Materials Science
Authors: Ilya Pichugin | Dmitrii Kruglov | Ekaterina V. Ilgisonis | Elena A. Ponomarenko
Source: Research Square (preprint, 2023-05-17)
Field: Chemistry — Spectroscopy

MOLE: Multi-Omics Learning to Extrapolate Proteome Expression Abstract Background Complex multi-omics data requires interpretation on different levels of molecular biology processes. However, genomics and transcriptomics methods are more sensitive than proteomic methods because of PCR reaction and ability to multiply molecules to level enough for a successful detection. This forms the gap between thousands of genes with known RNA expression and hundreds of detected proteins. Results To predict a protein abundance by known RNA level in the sample we have used a 10-channels input convolutional model to store label-free LC-MS/MS data, amino acids sequence and database annotations in one tensor. The solution was designed as an extrapolating tool for online public web-usage as only light-weighted deep neural architectures with fast inference were used. The validation set was once created by 20% of proteins in used datasets. Validation results for the healthy human tissues dataset showed 0.58 R 2 coefficient of determination and 0.71 Spearman correlation for all samples and up to 0.67 R 2 per tissue. For the tumor cell lines dataset 0.54 R 2 coefficient of determination and 0.71 Spearman correlation for all validation samples and up to 0.62 R 2 per cell line. Conclusion The solution allows a researcher to use any annotation collections and modifiable amino acids sequence to extrapolate protein abundances with known RNA quantity in the sample. A one model – many datasets pipeline with comparable metrics was implemented. Proteome ; Pipeline (software) ; Computational biology ; Genomics ; Correlation ; Computer science ; Inference ; Annotation ; Sample (material) ; Transcriptome ; Proteomics ; Artificial intelligence ; Biology ; Bioinformatics ; Chemistry ; Gene expression ; Gene ; Mathematics ; Chromatography ; Genetics ; Genome Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Gene expression and cancer classification
Authors: Zheren Wang | Yingzhi Sun | Kevin Cruse | Yan Zeng | Yuxing Fei | Zexuan Liu | Junyi Shangguan | Young‐Woon Byeon | KyuJung Jun | Tanjin He | Wenhao Sun | Gerbrand Ceder
Source: Research Square (preprint, 2023-01-10)
Field: Materials Science — Materials Chemistry

Optimal thermodynamic conditions to minimize kinetic byproducts in aqueous materials synthesis Kinetic energy ; Aqueous solution ; Thermodynamics ; Chemistry ; Chemical engineering ; Materials science ; Physical chemistry ; Engineering ; Physics ; Classical mechanics Machine Learning in Materials Science ; Crystallization and Solubility Studies ; Process Optimization and Integration
Authors: Zhiyuan Liu | Sihang Li | Yanchen Luo | Fei Hao | Yixin Cao | Kenji Kawaguchi | Xiang Wang | Tat‐Seng Chua
Source: arXiv (Cornell University) (preprint, 2023-10-19)
Field: Materials Science — Materials Chemistry

MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter Language Models (LMs) have demonstrated impressive molecule understanding ability on various 1D text-related tasks. However, they inherently lack 2D graph perception - a critical ability of human professionals in comprehending molecules' topological structures. To bridge this gap, we propose MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. MolCA enables an LM (e.g., Galactica) to understand both text- and graph-based molecular contents via the cross-modal projector. Specifically, the cross-modal projector is implemented as a Q-Former to connect a graph encoder's representation space and an LM's text space. Further, MolCA employs a uni-modal adapter (i.e., LoRA) for the LM's efficient adaptation to downstream tasks. Unlike previous studies that couple an LM with a graph encoder via cross-modal contrastive learning, MolCA retains the LM's ability of open-ended text generation and augments it with 2D graph information. To showcase its effectiveness, we extensively benchmark MolCA on tasks of molecule captioning, IUPAC name prediction, and molecule-text retrieval, on which MolCA significantly outperforms the baselines. Our codes and checkpoints can be found at https://github.com/acharkq/MolCA. Computer science ; Adapter (computing) ; Modal ; Graph ; Theoretical computer science ; Encoder ; Natural language processing ; Artificial intelligence ; Chemistry ; Computer hardware Machine Learning in Materials Science ; Topic Modeling ; Computational Drug Discovery Methods
Authors: Sarah Ayoub | Jolanta B. Lagowski
Source: Preprints.org (preprint, 2023-02-16)
Field: Chemistry — Inorganic Chemistry

The Most Stable Structure of PTB7-Th: DFT Conformational Analysis PTB7-Th is an important donor copolymer used in construction of many organic devices and other industrial applications. In this work, we investigate the structure and energetics of PTB7-Th. We employ density functional theory (DFT) (B3LYP), dispersion corrected DFT (B3LYP-D3) and long-range corrected DFT (CAM-B3LYP, LC-BLYP, and &amp;omega;B97xD) to analyze the conformational structures and their corresponding energies to determine the lowest energy state of PTB7-Th. The role of the alkane side chains is carefully investigated. Our findings indicate that, when branched ethylhexyl side chains are present, the lowest energy structure of PTB7-Th has fluorine in the same plane and the same side as the double bonded oxygen in the TT-CF part of the monomer and S-C-C-S dihedral angles along the chain backbone are cis-like having values in the range of 20-30 degrees in most cases. Without these side chains the polymer, not unexpectedly, has many near conformational degeneracies. Dihedral angle ; Density functional theory ; Side chain ; Materials science ; Monomer ; Dispersion (optics) ; Polymer ; Chemistry ; Computational chemistry ; Molecule ; Organic chemistry ; Physics Inorganic Fluorides and Related Compounds ; Organoboron and organosilicon chemistry ; Various Chemistry Research Topics
Authors: Shungui DENG | C. Zhang
Source: Journal of Inorganic Materials (article, 2023-11-13)
Field: Materials Science — Materials Chemistry

MXene Multifunctional Inks: a New Perspective toward Printable Energy-related Electronic Devices Advanced ink printing techniques, such as printing and coating, have overcome the limitations of traditional manufacturing methods, allowing for rapid prototyping of films and electronic devices with sophisticated structures and specific functions. These techniques hold enormous potential in wearable smart identification, energy storage, electromagnetic shielding and absorption, touch display, and so on. The key to printing advanced energy and electronic devices lies in the development of cutting-edge functional inks and their corresponding printing technologies. MXene, a family of two-dimensional compounds composed of transition metal carbides, nitrides, or carbonitrides, was discovered in 2011. MXene exhibits remarkable physical and chemical properties, including high conductivity, pronounced hydrophilicity, and diverse surface chemistry, which has garnered significant attention within the research community and made it particularly suitable as inks in printing applications. Conducting research on the printing behavior and mechanisms of MXene inks is crucial not only for achieving high-precision patterns but also for establishing a solid foundation for manufacturing techniques that can precisely create multiscale, multimaterial and multifunctional films, and electronic devices. This article begins with a brief discussion of MXene flakes' synthesis and colloidal stability, followed by a detailed examination of its rheological characteristics, printable ink formulation, and printing methods. Additional, special attention is given to the latest advances of MXene ink in energy, health, and sensing applications. The perspective concludes with a summary of current research challenges and future directions in this area, offering new perspectives and insights for researchers. Materials science ; Nanotechnology ; Inkwell ; 3D printing ; Coating ; Printed electronics ; Wearable technology ; Electronics ; Wearable computer ; Computer science ; Composite material ; Electrical engineering ; Embedded system ; Engineering MXene and MAX Phase Materials ; Advanced Memory and Neural Computing ; Advanced Sensor and Energy Harvesting Materials
Authors: Xinyi Zhou | Paul Chao | Luke Sloan | Huai-Hsun Lien | Allen H. Hunter | Amit Misra | Ashwin J. Shahani
Source: arXiv (Cornell University) (preprint, 2023-04-07)
Field: Materials Science — Materials Chemistry

Three-dimensional morphology of an ultrafine Al-Si eutectic produced via laser rapid solidification Al-Si alloys processed by laser rapid solidification yield eutectic microstructures with ultrafine and interconnected fibers. Such fibrous structures have long been thought to bear resemblance to those formed in impurity-doped alloys upon conventional casting. Here, we show that any similarity is purely superficial. By harnessing high-throughput characterization and computer vision techniques, we perform a three-dimensional analysis of the branching behavior of the ultrafine eutectic and compare it against an impurity-modified eutectic as well as a random fractal (as a benchmark). Differences in the branching statistics point to different microstructural origins of the impurity- and quench-modified eutectic. Our quantitative approach is not limited to the data presented here but can be used to extract abstract information from other volumetric datasets, without customization. Eutectic system ; Materials science ; Morphology (biology) ; Laser ; Metallurgy ; Microstructure ; Optics ; Geology ; Physics Solidification and crystal growth phenomena ; Additive Manufacturing Materials and Processes ; Silicon and Solar Cell Technologies
Authors: Maria Biosca | Daniel Tarr | Òscar Pàmies | Montserrat Diéguez
Source: European Journal of Organic Chemistry (article, 2023-07-07)
Field: Chemistry — Organic Chemistry

The Evolution of Phosphite‐Oxazoline Ligands for the Pd‐Allylic Substitution and Their Application in Building Chiral Molecules Abstract Pd‐catalyzed asymmetric allylic substitution (AAS) is a highly effective method for producing chiral molecules with alkene‐substituted frameworks which can be further derivatized. However, its stereochemical outcome is affected by the steric requirements of the substrate and only a narrow set of nucleophiles yield excellent enantioselectivities. In this regard, phosphite‐oxazolines have emerged as strong candidates to be privileged ligands for this process, providing results that surpass most of the previously published studies. They have provided high enantiocontrol when used in the Pd‐AAS of several hindered and unhindered substrates, using a wide range of C‐, O‐, and N‐nucleophiles. In this concept, we review and discuss the current progress made in the design of tailor‐made phosphite‐oxazoline ligand libraries for the Pd‐AAS of a broad range of substrates and nucleophiles and its application in the construction of chiral complex molecules. Oxazoline ; Chemistry ; Nucleophile ; Allylic rearrangement ; Steric effects ; Ligand (biochemistry) ; Combinatorial chemistry ; Alkene ; Molecule ; Palladium ; Substitution reaction ; Enantioselective synthesis ; Substrate (aquarium) ; Yield (engineering) ; Catalysis ; Stereochemistry ; Medicinal chemistry ; Organic chemistry Asymmetric Synthesis and Catalysis ; Asymmetric Hydrogenation and Catalysis ; Catalytic C–H Functionalization Methods
Authors: Chun-I Wang | Charlie Maier | Nicholas E. Jackson
Source: ChemRxiv (preprint, 2023-12-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Accessing the Electronic Structure of Liquid Crystalline Semiconductors with Bottom-Up Electronic Coarse-Graining Understanding the relationship between multiscale morphology and electronic structure is a grand challenge for semiconducting soft materials. Computational studies aimed at characterizing these multiscale relationships require the complex integration of quantum-chemical (QC) calculations, all-atom and coarse-grained (CG) molecular dynamics simulations, and back-mapping approaches. However, the integration and scalability of these methods pose substantial computational challenges that limit their application to the requisite length scales of soft material morphologies. Here, we demonstrate the bottom-up electronic coarse-graining (ECG) of morphology-dependent electronic structure in the liquid-crystalline (LC) semiconductor, 2-(4-methoxyphenyl)-7-octyl-benzothienobenzothiophene (BTBT). ECG is applied to construct density functional theory (DFT)-accurate valence band Hamiltonians of the isotropic and nematic LC phases using only the CG representation of BTBT. By bypassing the atomistic resolution and its prohibitive computational costs, ECG enables the first calculations of the morphology dependence of the electronic structure of charge carriers across LC phases at the ~20 nm length scale, with robust statistical sampling. These simulations uncover a complex interplay of localized and delocalized charge carriers in the isotropic and nematic LC phases while highlighting the important role of statistical sampling in the electronic structure of soft materials. Importantly, to push towards electronic predictions at truly mesoscopic length scales, we assess the theoretical feasibility of developing field-based ECG models. The fully CG approach to electronic property predictions in LC semiconductors opens a new computational direction for designing electronic processes in soft materials at their characteristic length scales. Electronic structure ; Mesoscopic physics ; Materials science ; Multiscale modeling ; Statistical physics ; Delocalized electron ; Semiconductor ; Granularity ; Density functional theory ; Organic semiconductor ; Chemical physics ; Nanotechnology ; Condensed matter physics ; Computer science ; Physics ; Chemistry ; Computational chemistry ; Quantum mechanics ; Optoelectronics Liquid Crystal Research Advancements ; Block Copolymer Self-Assembly ; Quantum Dots Synthesis And Properties
Authors: John R. Castro-Suárez | Joaquín Hernández‐Fernández
Source: Journal of Southwest Jiaotong University (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

QUANTIFICATION OF A VITAL NUCLEATING AGENT FOR IMPROVING THE RECOVERY RATE OF RECYCLED ETHYLENE-PROPYLENE IMPACT COPOLYMER PLASTICS USING VIBRATIONAL SPECTROSCOPY AND MULTIVARIATE ANALYSIS The potential of mid-infrared (MIR) spectroscopy as a tool for quantifying the presence of nucleating additives in copolymers has been evaluated. This study focused on the analysis of the Millad NX8000 additive in an ethylene-propylene copolymer using MIR vibrational spectroscopy. The spectral range evaluated was 400 cm -1 - 4000 cm -1 . Univariate and multivariate analyses of the spectral data were performed to evaluate MIR spectroscopy as an analytical technique for the vibrational quantification of additives in copolymers. The results showed that it could be used to build analytical methodologies for the identification and quantification of selected chemical targets, with a highly linear response for concentrations up to ~ 4000 ppm. Four vibrational bands were evaluated in the Millad NX800 absorbance spectrum to determine the figures of merit from the linear regressions. The lowest concentration of additive that could be detected (LOD) was determined to be 241 ppm, and the value for the quantification limit (LOQ) was 804 ppm. Multivariate analysis (MVA) using PLS was applied to the spectral information. The root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), coefficient of determination from cross-validation (R 2 -CV), and coefficient of determination from prediction (R 2 -Pred) were calculated and used as indicators of the quality of the obtained spectral correlations. The results suggest that MIR spectroscopy could be a useful tool for the quantitative analysis of copolymers with nucleating additives such as Millad NX8000. Keywords: Polypropylene, Copolymer, Multivariate Data Analysis, Partial Least Square Regression, Fourier Transform Infrared Spectroscopy, Limit of Detection, Millad DOI： https://doi.org/10.35741/issn.0258-2724.58.5.40 Copolymer ; Spectroscopy ; Materials science ; Multivariate statistics ; Univariate ; Fourier transform infrared spectroscopy ; Analytical Chemistry (journal) ; Infrared spectroscopy ; Polypropylene ; Absorbance ; Chemistry ; Polymer ; Mathematics ; Chromatography ; Organic chemistry ; Statistics ; Composite material ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Roya Boodaghi Malidarre | İskender Akkurt | Abdul Vahap Korkmaz | İsmail Ekmekçi
Source: Research Square (preprint, 2023-02-21)
Field: Materials Science — Materials Chemistry

Examining the HAP+ Fe2O3 Response in the Magnetic Field, Radiation Protection and Mechanical Properties Abstract HAP (Hydroxyapatite) bio-composite has been used extensively to repair and replace bone and teeth tissues in the human body. However, because of the poor mechanical features of HAP bio-composites, significant enhancements in the strength and toughness of pure HAP have been achieved by the insertion of various alloys and materials into HAP. Accordingly, the present study evaluates the radiation shielding and mechanical features of the Fe 2 O 3 -reinforced HAP composite as an implant for 0.0, 2.5, 5.0, and 7.5 wt.% Fe 2 O 3 . Also, the composite response in a magnetic field has been investigated. Employing FLUKA Monte Carlo Code, radiation shielding factors are obtained. In addition, the mechanical characteristics of the studied composites are evaluated using the theoretical method. Findings reveal that increasing the Fe 2 O 3 contents in HAP bio-composite enhances the preferred samples’ radiation shielding and mechanical qualities. Furthermore, in the absence of a magnetic field, the particles' spatial map exhibits symmetric behavior along the x-axis, however, a different trend is observed in the presence of a magnetic field with a value of B x =5 microT. Electromagnetic shielding ; Composite number ; Materials science ; Composite material ; Radiation shielding ; Irradiation ; Radiation ; Toughness ; Fracture toughness ; Magnetic field ; Optics ; Physics ; Nuclear physics Radiation Shielding Materials Analysis ; Graphite, nuclear technology, radiation studies ; Bone Tissue Engineering Materials
Authors: Hisao Taira | Daisuke Miyashiro | Kazuo Umemura
Source: Molecules (article, 2023-03-17)
Field: Materials Science — Materials Chemistry

Numerical Analysis for Light Absorption Spectra of the Base of DNA-Wrapped Single-Walled Carbon Nanotubes This study numerically demonstrates the light absorption spectra of each base of DNA-wrapped single-walled carbon nanotubes (SWCNTs). Previous experimental and theoretical studies show that the optical properties of these composites are different from the bare SWCNTs. In this work, we investigated the bases of DNA that influence optical properties. To obtain stable molecular states for studying optical properties, molecular dynamics calculations were performed. Additionally, light absorption spectra in the ultraviolet-to-near-infrared region of one type of base-wrapped (e.g., adenine-, thymine-, cytosine-, or guanine-wrapped) SWCNTs were investigated by utilizing the semi-empirical molecular orbital theory using SCIGRESS commercial software. This method can significantly reduce the calculation time compared to the ab initio molecular orbital method, making the handling of composites of bases and SWCNTs possible. We found that the largest peaks appear at a wavelength of around 300 nm for all the composites. Furthermore, we found that the light absorption spectra above 570 nm are strongly influenced by adenine and cytosine. Thus, our computational results provide insight into the optical properties and the effects of base-SWCNTs that are difficult to investigate experimentally under the influence of solvents and various molecules. Carbon nanotube ; Thymine ; Absorption (acoustics) ; Cytosine ; Materials science ; Ab initio ; Guanine ; Molecular orbital ; Nucleobase ; Absorption spectroscopy ; Spectral line ; Base (topology) ; Molecule ; Molecular physics ; Chemical physics ; Computational chemistry ; Nanotechnology ; Chemistry ; DNA ; Optics ; Composite material ; Physics ; Organic chemistry Carbon Nanotubes in Composites ; Fullerene Chemistry and Applications ; Graphene research and applications
Authors: Odwa Mbanga | Ewa Cukrowska | Mary Gulumian
Source: Research Square (preprint, 2023-01-16)
Field: Materials Science — Materials Chemistry

A comparative study of the biodurability and persistence of gold, silver and titanium dioxide nanoparticles using the continuous flow through system Dissolution ; Nanoparticle ; Titanium dioxide ; Persistence (discontinuity) ; Silver nanoparticle ; Nanotechnology ; Colloidal gold ; Chemical engineering ; Materials science ; Chemistry ; Metallurgy ; Geology ; Engineering Nanoparticles: synthesis and applications ; Healthcare and Environmental Waste Management ; Air Quality and Health Impacts