jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: G H Nayana | P. Vimala
Source: International Journal of Reconfigurable and Embedded Systems (IJRES) (article, 2021-03-01)
Field: Materials Science — Materials Chemistry

Monolayer and bilayer graphene field effect transistor using Verilog-A Monolayer and bilayer graphene field effect transistor modeling is presented in this paper. The transport model incorporated, works well for both drift diffusive and ballistic conditions. The validity of the model was checked for various device dimensions and bias voltages. Performance parameters affecting operation of graphene field effect transistor in various region of operation are optimized. Model was developed to verify transfer characteristics for monolayer and bilayer graphene field effect transistor. Results obtained prove the ambipolar property in Graphene. MATLAB is used for numerical modeling for systematic performance evaluation of parameters in graphene. The tool used to simulate the characteristics is cadence Verilog-A which describe analog component structure. Ambipolar diffusion ; Monolayer ; Graphene ; Materials science ; Transistor ; Field-effect transistor ; Bilayer graphene ; Bilayer ; Optoelectronics ; Voltage ; Nanotechnology ; Electrical engineering ; Physics ; Chemistry ; Engineering ; Membrane ; Plasma Graphene research and applications ; Radiation Effects in Electronics ; Carbon Nanotubes in Composites
Authors: Zuqin Wang | Ting Ran | Fang Xu | Chang Wen | Shukai Song | Yang Zhou | Hongming Chen | Xiaoyun Lu
Source: Chemical Communications (article, 2021-01-01)
Field: Chemistry — Organic Chemistry

Deep learning-driven scaffold hopping in the discovery of Akt kinase inhibitors Scaffold hopping has been widely used in drug discovery and is a topic of high interest. Here a deep conditional transformer neural network, SyntaLinker, was applied for the scaffold hopping of a phase III clinical Akt inhibitor, AZD5363. A number of novel scaffolds were generated and compound 1a as a proof-of-concept was synthesized and validated by biochemical assay. Further structure-based optimization of 1a led to a novel Akt inhibitor with high potency (Akt1 IC<sub>50</sub> = 88 nM) and <i>in vitro</i> antitumor activities. Protein kinase B ; AKT1 ; Scaffold ; Drug discovery ; Chemistry ; Kinase ; Phosphorylation ; Computer science ; Biochemistry Synthesis and biological activity ; Computational Drug Discovery Methods ; Quinazolinone synthesis and applications
Authors: Shivaprasad Gadag | Reema Narayan | Chetan Hasmukh Mehta | A. Jerald Suresh | Usha Y. Nayak
Source: Indian Journal of Pharmaceutical Education and Research (article, 2021-11-09)
Field: Chemistry — Analytical Chemistry

Development and Validation of a Rapid and Sensitive Stability-indicating RP-HPLC Method for Resveratrol Quantification in Pharmaceutical Formulation Background: Trans-resveratrol (RVT) is a phytoconstituent belonging to the family of polyphenols, extensively studied for its numerous health benefits. However, its susceptibility for photolytic, oxidative, and hydrolytic degradation, hinders the quantification of RVT present in different formulations. In the present study, a novel, precise, simple, reproducible, accurate, and stability indicating reversed-phase high performance liquid chromatography (RP-HPLC) method was developed and validated using quality by design for the quantification of RVT in pharmaceutical formulation. Force degradation studies were carried out, and the intrinsic stability of RVT was assessed using the proposed method. Materials and Methods: Chromatographic separation of RVT was obtained on Phenomenex Kinetex C 18 (2504.6 mm, 5 , 100 ) stationary phase with isocratic elution using 0.2% v/v trifluoroacetic acid (TFA) in HPLC grade water and acetonitrile (ACN) in the ratio 75:25% v/v. A flow rate of 1.0 ml/min was maintained for pumping the mobile phase, and the eluent was detected at a wavelength of 306 nm. Results: RVT was found to elute at a retention time (t R ) of 6.96 0.08 min. The method was linear in the range of 0.1 g/ml to 2.0 g/ml concentration with correlation coefficient 0.9998. The % recovery was found to be 100.16 to 101.73, % RSD of six replicate standards was found to be 0.58. The excipients present in the formulation did not show any interference in the analysis of RVT, indicating the specificity of the developed method. Conclusion: The proposed method can be applied for the quantification of RVT in a pharmaceutical formulation, dietary supplements, and bulk drug. Trifluoroacetic acid ; Chromatography ; Chemistry ; High-performance liquid chromatography ; Acetonitrile ; Forced degradation ; Pharmaceutical formulation ; Elution ; Hydrolysis ; Reversed-phase chromatography Chromatography in Natural Products ; Analytical Chemistry and Chromatography ; Sirtuins and Resveratrol in Medicine
Authors: Jianyu Zhang | Lianrui Hu | Kaihua Zhang | Junkai Liu | Xingguang Li | Haoran Wang | Zhaoyu Wang | Herman H. Y. Sung | Ian D. Williams | Zebing Zeng | Jacky W. Y. Lam | Haoke Zhang | Ben Zhong Tang
Source: ChemRxiv (preprint, 2021-04-13)
Field: Materials Science — Materials Chemistry

How to Manipulate Through-Space Conjugation and Clusterolumi-nescence of Simple AIEgens with Isolated Phenyl Rings? &lt;a&gt;Apart from the traditional through-bond conjugation (TBC), through-space conjugation (TSC) is gradually proved as another important interaction in photophysical processes, especially for the recent observation of clusteroluminescence from nonconjugated molecules. &lt;/a&gt;Herein, &lt;a&gt;simple and nonconjugated triphenylmethane (TPM) and its derivatives with electron-donating and electron-withdrawing groups were synthesized&lt;/a&gt;, and their photophysical properties were systematically studied. &lt;a&gt;TPM was characterized with visible clusteroluminescence due to the intramolecular TSC. Experimental and theoretical results showed that the introduction of electron-donating groups into TPM could &lt;/a&gt;&lt;a&gt;red-shift &lt;/a&gt;the wavelength and increase the efficiency of clusteroluminescence simultaneously, due to the increased electronic density and stabilization of TSC. However, TPM derivatives with electron-withdrawing groups showed inefficient or even quenched clusteroluminescence caused by the vigorous excited-state intramolecular motion and intermolecular photoinduced electron transfer process. This work provides a reliable strategy to manipulate TSC and clusteroluminescence. Intramolecular force ; Intermolecular force ; Photochemistry ; Chemistry ; Electron transfer ; Molecule ; Excited state ; Stereochemistry ; Organic chemistry ; Atomic physics ; Physics Luminescence and Fluorescent Materials ; Radical Photochemical Reactions ; Fluorine in Organic Chemistry
Authors: Karolis Norvaiša | Sophie Maguire | Claire Donohoe | John E. O’Brien | Brendan Twamley | Lígia C. Gomes‐da‐Silva | Mathias O. Senge
Source: Chemistry - A European Journal (article, 2021-11-18)
Field: Materials Science — Materials Chemistry

Steric Repulsion Induced Conformational Switch in Supramolecular Structures Inspired by the rigidified architecture of 'picket-fence' systems, we propose a strategy utilizing strain to impose intramolecular tension in already peripherally overcrowded structures leading to selective atropisomeric conversion. Employing this approach, tuneable shape-persistent porphyrin conformations were acquired exhibiting distinctive supramolecular nanostructures based on the orientation of the peripheral groups. The intrinsic assemblies driven by non-covalent bonding interactions form supramolecular polymers while encapsulating small molecules in parallel channels or solvent-accessible voids. The developed molecular strain engineering methodologies combined with synthetic approaches have allowed the introduction of the pivalate units creating a highly strained molecular skeleton. Changes in the absorption spectrum indicated the presence of severe steric repulsions between the peripheral groups which were confirmed by single crystal X-ray analysis. To release the steric strain introduced by the peripheral units, thermal equilibration strategies were used to selectively convert the most abundant atropisomer to the desirable minor one. Supramolecular chemistry ; Steric effects ; Porphyrin ; Intramolecular force ; Covalent bond ; Molecule ; Chemistry ; Molecular switch ; Crystallography ; Materials science ; Chemical physics ; Stereochemistry ; Photochemistry ; Crystal structure ; Organic chemistry Porphyrin and Phthalocyanine Chemistry ; Supramolecular Chemistry and Complexes ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Peace Doe | Cynthia Amaning Danquah | Kwasi A. Ohemeng | Ako Ernest Opare | Ahmed O Sharif | Dorcas Akua-Abora | Asamoah Kwame Akuoko | Aaron Kpabitey | Emmanuel Nii‐Boye Quarshie | Oliver Opoku Asante | Elvis Kwadwo Amponsah | Mariyana Mutwaliku | Charlotte Nuro-Brefo | Micheal Ofori
Source: Pharmacognosy Research (article, 2021-12-29)
Field: Chemistry — Organic Chemistry

Analgesic, Anti-inflammatory, and Anti-pyretic Activities of Crinum pedunculatum R.Br. Bulb Extracts Background: Crinum pedunculatum R.Br. bulbs are used for the topical management of inflammation by traditional healers in the southern region of Ghana. Objectives: This study aims to assess the analgesic, anti-inflammatory, and anti-pyretic activities of different solvent extracts of Crinum pedunculatum. Methods: The analgesic, anti-inflammatory, and anti-pyretic activities of the bulb extracts of Crinum pedunculatum were determined in rats at doses of 100, 200, and 400 mg/kg. The acetic acid induced writhing test was used to determine the analgesic activity, carrageenan was employed to determine the anti-inflammatory activity, and Brewer's yeast-induced pyrexia was studied to evaluate the extract's anti-pyretic activity. Results: All solvent extracts of Crinum pedunculatum significantly decreased (P < 0.001) the frequency of writhing in rats at all doses with 400 mg/kg of the ethanolic extract showing a 98% inhibition comparable to that obtained with diclofenac sodium at 94%. These extracts also caused the inhibition of the increase in paw diameter induced by the administration of carrageenan with 400 mg/kg of the ethyl acetate extract of Crinum pedunculatum causing a 97% inhibition of paw oedema. All doses (100, 200, and 400 mg/kg) of the methanol extract caused a significant decrease (P < 0.0001) in the temperature of rats induced via the administration of yeast with ethanol and ethyl acetate extracts also showed a significant reduction (P < 0.001) in rectal temperature. Conclusion: These results obtained indicate that the methanolic, ethanolic, and ethyl acetate extracts of Crinum pedunculatum R.Br. possess Traditional medicine ; Analgesic ; Bulb ; Medicine ; Pharmacology ; Biology ; Botany Chemical synthesis and alkaloids
Authors: Pritom J. Bora | Bibhusita Mahanta | K. Kishore | Praveen C. Ramamurthy
Source: Journal of Applied Polymer Science (article, 2021-12-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Data‐driven methodology to realize strong and broadband microwave absorption properties of polymer‐fly ash cenosphere composite Abstract A very efficient microwave absorption characteristic of conducting polymer (polyaniline or PANI) incorporated fly ash cenosphere (FAC), which is a waste of thermal power plant, is revealed in this work with materials data‐driven approach. The different loading (wt%) of PANI‐FAC hybrids to a polymer such as polyvinyl butyral (PVB) results in different reflection loss (RL). However, RL performances do not improve by simply increasing the PANI‐FAC hybrid loading (wt%) to PVB. Herein, PANI‐FAC loading to PVB is optimized through the electromagnetic data‐driven methodology. A remarkable RL ≤ − 40 dB with entire X‐band (8.2–12.4 GHz) absorption bandwidth (RL ≤ −10 dB, RL value −10 dB corresponds to 90% absorption) is predicted for 8.5 wt% PANI‐FAC hybrid loaded PVB‐PANI‐FAC composite. The predicted RL matched with experimental data (minimum RL value −44.5 dB with X‐band absorption bandwidth), confirming the proposed proof of concept of data‐driven methodology to obtain broadband and robust microwave absorption characteristics of polymer‐FAC composites. Materials science ; Cenosphere ; Polyvinyl butyral ; Microwave ; Composite material ; Reflection loss ; Composite number ; Polymer ; Absorption (acoustics) ; Polyaniline ; Fly ash ; Telecommunications ; Computer science Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Dielectric materials and actuators
Authors: Marco De Lucia | Michael Kühn
Source:  (preprint, 2021-03-02)
Field: Materials Science — Materials Chemistry

DecTree v1.0 – Chemistry speedup in reactive transport simulations:purely data-driven and physics-based surrogates Abstract. The computational costs associated with coupled reactive transport simulations are mostly due to the chemical subsystem: replacing it with a pre-trained statistical surrogate is a promising strategy to achieve decisive speedups at the price of small accuracy losses and thus to extend the scale of problems which can be handled. We introduce a hierarchical coupling scheme in which full physics, equation-based geochemical simulations are partially replaced by surrogates. Errors on mass balance resulting from multivariate surrogate predictions effectively assess the accuracy of multivariate regressions at runtime: inaccurate surrogate predictions are rejected and the more expensive equation-based simulations are run instead. Gradient boosting regressors such as xgboost, not requiring data standardization and being able to handle Tweedie distributions, proved to be a suitable emulator. Finally, we devise a surrogate approach based on geochemical knowledge, which overcomes the issue of robustness when encountering previously unseen data, and which can serve as basis for further development of hybrid physics-AI modelling. Speedup ; Robustness (evolution) ; Computer science ; Surrogate model ; Multivariate statistics ; Boosting (machine learning) ; Standardization ; Uncertainty quantification ; Machine learning ; Chemistry ; Parallel computing Machine Learning in Materials Science ; Groundwater flow and contamination studies ; Gaussian Processes and Bayesian Inference
Authors: R. Matthias Geilhufe | Bart Olsthoorn | Alexander V. Balatsky
Source: Nature Physics (article, 2021-01-12)
Field: Materials Science — Materials Chemistry

Shifting computational boundaries for complex organic materials Field (mathematics) ; Complex system ; Artificial neural network ; Computational model ; Organic molecules Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; X-ray Diffraction in Crystallography
Authors: Fang Wu | Dragomir Radev | Li, Stan Z.
Source: arXiv (Cornell University) (preprint, 2021-10-04)
Field: Materials Science — Materials Chemistry

Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs Procuring expressive molecular representations underpins AI-driven molecule design and scientific discovery. The research mainly focuses on atom-level homogeneous molecular graphs, ignoring the rich information in subgraphs or motifs. However, it has been widely accepted that substructures play a dominant role in identifying and determining molecular properties. To address such issues, we formulate heterogeneous molecular graphs (HMGs), and introduce a novel architecture to exploit both molecular motifs and 3D geometry. Precisely, we extract functional groups as motifs for small molecules and employ reinforcement learning to adaptively select quaternary amino acids as motif candidates for proteins. Then HMGs are constructed with both atom-level and motif-level nodes. To better accommodate those HMGs, we introduce a variant of Transformer named Molformer, which adopts a heterogeneous self-attention layer to distinguish the interactions between multi-level nodes. Besides, it is also coupled with a multi-scale mechanism to capture fine-grained local patterns with increasing contextual scales. An attentive farthest point sampling algorithm is also proposed to obtain the molecular representations. We validate Molformer across a broad range of domains, including quantum chemistry, physiology, and biophysics. Extensive experiments show that Molformer outperforms or achieves the comparable performance of several state-of-the-art baselines. Our work provides a promising way to utilize informative motifs from the perspective of multi-level graph construction. Computer science ; Motif (music) ; Exploit ; Transformer ; Homogeneous ; Molecular graph ; Theoretical computer science ; Graph ; Artificial intelligence ; Physics ; Statistical physics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Protein Structure and Dynamics
Authors: Lin Jiang | Rhoda Afriyie Mensah | Solomon Asante‐Okyere | Michael Försth | Qiang Xu | Yao Yevenyo Ziggah | Ágoston Restás | F. Berto | Oisik Das
Source: Fire and Materials (article, 2021-09-19)
Field: Materials Science — Materials Chemistry

Developing an artificial intelligent model for predicting combustion and flammability properties Summary While there have been various attempts in establishing a model that can predict the flammability characteristics of polymers based on their molecular structure, artificial intelligence (AI) presents a promising alternative in tackling this pressing issue. Therefore, a novel approach of adopting AI methods, extreme learning machines (ELMs) and group method of data handling (GMDH) in estimating heat release capacity, total heat release and char yield from thermophysical properties of polymers were addressed. GMDH showed a clear indication of overfitting whereby the models generated excellent training results but could not provide similar performance during testing. The superior generalisation performance of ELM during testing makes it the standout method. ELM produced HRC predictions having R and RRMSE of 0.86 and 0.405 for training, 0.94 and 0.356 for testing. For THR estimates from ELM, the R and RRMSE scores were 0.9 and 0.195 for training, 0.93 and 0.131 for testing. While char yield ELM model generated 0.88 and 0.795 for training, 0.93 and 0.383 for testing. The potential of ELM was demonstrated as it estimated the flammability parameters of 105 polymers having little or no empirical test results. Flammability ; Overfitting ; Char ; Combustion ; Extreme learning machine ; Yield (engineering) ; Training set ; Machine learning ; Test data ; Ignition system ; Environmental science ; Artificial intelligence ; Computer science ; Engineering ; Materials science ; Chemistry ; Composite material ; Artificial neural network ; Aerospace engineering Thermal and Kinetic Analysis ; Fire dynamics and safety research ; Fuel Cells and Related Materials
Authors: Musen Zhou | Jingqi Wang | Jose Garcia | Yu Liu | Jianzhong Wu
Source: Industrial & Engineering Chemistry Research (article, 2021-11-13)
Field: Chemistry — Inorganic Chemistry

Modeling Multicomponent Gas Adsorption in Nanoporous Materials with Two Versions of Nonlocal Classical Density Functional Theory Two versions of nonlocal classical density functional theory (cDFT) have been proposed to predict multicomponent gas adsorption in nanoporous materials by using the Lennard-Jones model for gas mixtures and the universal force field for the adsorbents. With the modified fundamental measure theory to describe short-range repulsions or volume-exclusion effects, one version of cDFT adopts the mean-field approximation for van der Waals attraction (here referred to as cDFT-MFA) as commonly used in porous material characterization, and the other version accounts for long-range correlations through a weighted-density approximation (cDFT-WDA). For a number of gas mixtures in MOF-5 (without sub-pores inaccessible to gas molecules), the adsorption isotherms predicted from cDFT-WDA are quantitatively consistent with results from grand canonical Monte Carlo simulation, while cDFT-MFA systematically underestimates the adsorption due to the neglect of correlation effects. Nevertheless, both versions of cDFT outperform the ideal adsorbed solution theory (IAST) at high pressure. Because IAST predicts mixture adsorption using only single-component data, it fails to capture the selective behavior arising from asymmetric interactions among different chemical species. The cDFT calculations are implemented with massively parallel GPU-accelerated algorithms to achieve rapid yet accurate predictions of multicomponent adsorption isotherms with full atomistic details of the adsorbent materials. This work thus provides a theoretical basis for the computational design of adsorption-based separation processes as well as for screening and data-driven inverse design of nanoporous materials. Nanoporous ; Adsorption ; van der Waals force ; Grand canonical ensemble ; Density functional theory ; Thermodynamics ; Grand potential ; Canonical ensemble ; Chemistry ; Work (physics) ; Inverse ; Range (aeronautics) ; Molecule ; Monte Carlo method ; Materials science ; Computational chemistry ; Physical chemistry ; Physics ; Organic chemistry ; Mathematics Metal-Organic Frameworks: Synthesis and Applications ; Zeolite Catalysis and Synthesis ; Carbon Dioxide Capture Technologies
Authors: Sangmin Lee | Katherine Antonieta Villegas Ramos | Karel Matouš
Source: Mechanics of Materials (article, 2021-06-12)
Field: Materials Science — Materials Chemistry

Numerical study of damage in particulate composites during high-strain rate loading using novel damage model Materials science ; Ellipsoid ; Finite element method ; Solver ; Damage mechanics ; Composite material ; Fracture (geology) ; Peridynamics ; Particulates ; Strain rate ; Microstructure ; Mechanics ; Structural engineering ; Continuum mechanics ; Computer science ; Physics High-Velocity Impact and Material Behavior ; Mechanical Behavior of Composites ; Rock Mechanics and Modeling
Authors: Toshiaki Hanaoka | Masaru Aoyagi | Yusuke Edashige
Source: Catalysts (article, 2021-06-17)
Field: Chemistry — Inorganic Chemistry

n-Butene Synthesis in the Dimethyl Ether-to-Olefin Reaction over Zeolites Zeolite catalysts that could allow the efficient synthesis of n-butene, such as 1-butene, trans-2-butene, and cis-2-butene, in the dimethyl ether (DME)-to-olefin (DTO) reaction were investigated using a fixed-bed flow reactor. The zeolites were characterized by N2 adsorption and desorption, X-ray diffraction (XRD), thermogravimetry (TG), and NH3 temperature-programmed desorption (NH3-TPD). A screening of ten available zeolites indicated that the ferrierite zeolite with NH4+ as the cation showed the highest n-butene yield. The effect of the temperature of calcination as a pretreatment method on the catalytic performance was studied using three zeolites with suitable topologies. The calcination temperature significantly affected DME conversion and n-butene yield. The ferrierite zeolite showed the highest n-butene yield at a calcination temperature of 773 K. Multiple regression analysis was performed to determine the correlation between the six values obtained using N2 adsorption/desorption and NH3-TPD analyses, and the n-butene yield. The contribution rate of the strong acid site alone as an explanatory variable was 69.9%; however, the addition of micropore volume was statistically appropriate, leading to an increase in the contribution rate to 76.1%. Insights into the mechanism of n-butene synthesis in the DTO reaction were obtained using these parameters. Ferrierite ; Zeolite ; Calcination ; Dimethyl ether ; Chemistry ; Olefin fiber ; Catalysis ; Butene ; Yield (engineering) ; 1-Butene ; Desorption ; Adsorption ; Inorganic chemistry ; Organic chemistry ; Materials science ; Ethylene Zeolite Catalysis and Synthesis ; Catalysis and Oxidation Reactions ; Catalytic Processes in Materials Science