jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yan Ding | Hao Cheng | Z. X. Ye | Ruyi Feng | Tian, Wei | Xie, Peng | Zhang, Juan | Gu, Zhongze
Source: arXiv (Cornell University) (preprint, 2023-12-28)
Field: Materials Science — Materials Chemistry

AdaMR: Adaptable Molecular Representation for Unified Pre-training Strategy We propose Adjustable Molecular Representation (AdaMR), a new large-scale uniform pre-training strategy for small-molecule drugs, as a novel unified pre-training strategy. AdaMR utilizes a granularity-adjustable molecular encoding strategy, which is accomplished through a pre-training job termed molecular canonicalization, setting it apart from recent large-scale molecular models. This adaptability in granularity enriches the model's learning capability at multiple levels and improves its performance in multi-task scenarios. Specifically, the substructure-level molecular representation preserves information about specific atom groups or arrangements, influencing chemical properties and functionalities. This proves advantageous for tasks such as property prediction. Simultaneously, the atomic-level representation, combined with generative molecular canonicalization pre-training tasks, enhances validity, novelty, and uniqueness in generative tasks. All of these features work together to give AdaMR outstanding performance on a range of downstream tasks. We fine-tuned our proposed pre-trained model on six molecular property prediction tasks (MoleculeNet datasets) and two generative tasks (ZINC250K datasets), achieving state-of-the-art (SOTA) results on five out of eight tasks. Encoding (memory) ; Computer science ; Granularity ; Novelty ; Representation (politics) ; Task (project management) ; Process (computing) ; Generative model ; Artificial intelligence ; Property (philosophy) ; Generative grammar ; Theoretical computer science ; Machine learning ; Engineering ; Systems engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Crystallography and molecular interactions
Authors: Zhao Wang | Jingjing Sun | Ruilong Sheng
Source: Medicine Research (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Surface Physicochemical Properties of Polyethylene Glycol-Containing Polymer Nano Systems In the past decades, many polyethylene glycol (PEG)-containing polymers were developed and widely utilized to prepare functionalized nano delivery systems with hydrophilic shielding feature and high body fluid/environmental stability. Notably, some surface physicochemical properties of the PEG-containing polymers largely determined their solution properties and interactions with other biomolecules, which thus subsequently influenced their biological behaviors. In this paper, we summarized recent advances on the surface physicochemical properties of PEG-containing polymer nano systems and their impacts on self-assembly, solution stability, biomolecular interactions, as well as drug delivery. Future research outlooks in this area were also stated and discussed. Polyethylene glycol ; Nano- ; Polymer ; Materials science ; Chemical engineering ; Surface (topology) ; Polymer science ; Nanotechnology ; Polymer chemistry ; Composite material ; Engineering ; Mathematics ; Geometry Polymer Synthesis and Characterization ; Inorganic and Organometallic Chemistry ; Adsorption, diffusion, and thermodynamic properties of materials
Authors: Narender Chinthamu | Vigilson Prem Maryposonia | Rupinder Singh | Priya Kohli | Rajeev Kudari | Khunt Abhay
Source:  (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

An innovative approach in modelling and design of smart washing machine with automatic drying with estimating energy and water consumption using AI The automations in smart appliances play a vital role.The evolution of automation is the adoption of smart machines and appliances for industrial and domestic purposes.This helps to obtain smart home.They are implemented through artificial intelligence with optimization techniques.To replace the convention washing machine, the proposed system is introduced.This is functioned through adopting artificial intelligence to operate automatically through various devices.The smart washing machine is designed through machine learning techniques with sensors.This helps to adopt a newer way in washing that helps to reduce energy consumption through estimating the power utility.This is accompanied with automatic drying techniques.The system is completely automatic to perform the washing process.It is enhanced through internet of things to enable the two way communication system.The smart meter is used to record the energy consumption.The efficiency and performance parameter are higher when compared to conventional washing machines.Thus the proposed system enhances automation in washing machines with automatic drying and estimates the amount of energy consumption. Energy consumption ; Water consumption ; Computer science ; Energy (signal processing) ; Process engineering ; Consumption (sociology) ; Automotive engineering ; Waste management ; Engineering ; Electrical engineering ; Mathematics Textile materials and evaluations
Authors: Stefano Martina | Santiago Hernández-Gómez | Stefano Gherardini | Filippo Caruso | Nicole Fabbri
Source: arXiv (Cornell University) (preprint, 2023-01-12)
Field: Materials Science — Materials Chemistry

Deep learning enhanced noise spectroscopy of a spin qubit environment The undesired interaction of a quantum system with its environment generally leads to a coherence decay of superposition states in time. A precise knowledge of the spectral content of the noise induced by the environment is crucial to protect qubit coherence and optimize its employment in quantum device applications. We experimentally show that the use of neural networks can highly increase the accuracy of noise spectroscopy, by reconstructing the power spectral density that characterizes an ensemble of carbon impurities around a nitrogen-vacancy (NV) center in diamond. Neural networks are trained over spin coherence functions of the NV center subjected to different Carr-Purcell sequences, typically used for dynamical decoupling (DD). As a result, we determine that deep learning models can be more accurate than standard DD noise-spectroscopy techniques, by requiring at the same time a much smaller number of DD sequences. Qubit ; Coherence (philosophical gambling strategy) ; Dynamical decoupling ; Superposition principle ; Coherence time ; Spectroscopy ; Noise (video) ; Curse of dimensionality ; Physics ; Spectral density ; Artificial neural network ; Statistical physics ; Quantum ; Quantum mechanics ; Computer science ; Artificial intelligence ; Telecommunications Diamond and Carbon-based Materials Research ; Force Microscopy Techniques and Applications ; Atomic and Subatomic Physics Research
Authors: Estíbaliz M. Ramírez | Chumín Wang
Source:  (article, 2023-08-15)
Field: Materials Science — Materials Chemistry

Silicio poroso en teranóstico humano El teranóstico (terapia y diagnóstico) es un nuevo concepto que busca integrar la detección, rectificación y liberación de medicamentos en un solo microdispositivo. Este artículo presenta los avances recientes del silicio poroso aplicados al área biomédica. Estas aplicaciones van desde sensores de fluidos biológicos, microsuministro de medicamentos, inmunoterapia de cáncer, hasta la regeneración de tejido cutáneo. Physics ; Computer science Silicon Nanostructures and Photoluminescence ; Occupational and environmental lung diseases ; Aluminum toxicity and tolerance in plants and animals
Authors: Mrs Anuja | Tawlare | Mr Pranjal Ranjan | Mr Abu | Safwan Shaikh | Mr Sanyyam Jain | Mr Shinde | Shinde Maruti | Haoyu Hu1 | Zihao Zhang2
Source: International Research Journal of Modernization in Engineering Technology and Science (article, 2023-02-28)
Field: Chemistry — Analytical Chemistry

FOOD IMAGE RECOGNITION AND CALORIE PREDICTION USING DEEP LEARNING APPROACH In this paper, we propose a food recognition system that when feed with the right amount of data can help a user monitor his/her day to day intake of calories.The user inputs an image from the gallery or mobile phone camera.Our Work is to first determine the Category of food and after predicting the category of Food(Fruit or Vegetable) Our System determining the Category of that Image(Either the Image is in the Category of Food or Vegetable) After Determining these Things We are predicting the Calorie of that Food as well.In This Our Work is totally based on the deep learning Algorithms.Deep learning and is used to recognize the image and based on The image it will Identify the Category.Our System Comprises with several segmentation and image parameters as well.If a system informs the nutritional information of a food item and classify it as healthy or non-healthy to the user, then people are able to identify their daily intake of calorie Value of their food items. Artificial intelligence ; Deep learning ; Calorie ; Computer science ; Pattern recognition (psychology) ; Computer vision ; Medicine ; Internal medicine Spectroscopy and Chemometric Analyses
Authors: Vigen G. Barkhudaryan
Source: International Journal of Chemical Engineering and Materials (article, 2023-10-03)
Field: Chemistry — Organic Chemistry

Effect of Oligomers and Polymers of Ethylene Glycols on Micellar Characteristics of Aqueous Solutions of Sodium Pentadectyl Sulfonate The influence of oligomers and polymers of ethylene glycols with a different molecular mass on the structural transformations of aqueous solutions of surfactant, sodium pentadecylsulfonate, studied by viscometry and light scattering methods depending on their content in the system. It established that ethylene glycol with a molecular mass of 2,000 and 40,000 does not affect the structure of the system. For ethylene glycol with a molecular mass of 4,000, 6,000, and 20,000, a clearly expressed complex course of the dependence of the intrinsic viscosity of the micelle system on the polymer content was established. It assumed that with the changes in the concentration of ethylene glycols in the system, micelles are compacted due to a change in the balance of hydrophobic-hydrophilic interactions. In parallel with the change in apparent micelle masses and asymmetry coefficients determined by the light scattering method, the intrinsic viscosity also changes depending on the system's composition. The practical application of this research is that it allows the performance properties of sodium pentadecyl sulfonate (SPDS) to be adjusted, thereby expanding and improving its applications. Aqueous solution ; Micelle ; Viscometer ; Polymer ; Ethylene glycol ; Chemistry ; Sulfonate ; Intrinsic viscosity ; Molecular mass ; Pulmonary surfactant ; Molar mass ; Polymer chemistry ; Viscosity ; Dynamic light scattering ; Chemical engineering ; Sodium ; Organic chemistry ; Materials science Surfactants and Colloidal Systems ; Environmental Chemistry and Analysis ; Thermodynamic properties of mixtures
Authors: Pranav Kumar | Taniya Mandal | Swapnamay Mondal
Source: arXiv (Cornell University) (preprint, 2023-06-26)
Field: Materials Science — Materials Chemistry

Black holes and the loss landscape in machine learning Understanding the loss landscape is an important problem in machine learning. One key feature of the loss function, common to many neural network architectures, is the presence of exponentially many low lying local minima. Physical systems with similar energy landscapes may provide useful insights. In this work, we point out that black holes naturally give rise to such landscapes, owing to the existence of black hole entropy. For definiteness, we consider 1/8 BPS black holes in $\mathcal{N} = 8$ string theory. These provide an infinite family of potential landscapes arising in the microscopic descriptions of corresponding black holes. The counting of minima amounts to black hole microstate counting. Moreover, the exact numbers of the minima for these landscapes are a priori known from dualities in string theory. Some of the minima are connected by paths of low loss values, resembling mode connectivity. We estimate the number of runs needed to find all the solutions. Initial explorations suggest that Stochastic Gradient Descent can find a significant fraction of the minima. Maxima and minima ; Energy landscape ; Statistical physics ; String theory ; String (physics) ; Physics ; Mathematics ; Theoretical physics ; Mathematical analysis Machine Learning in Materials Science ; Neural Networks and Applications ; Advanced Electron Microscopy Techniques and Applications
Authors: Yu.G. Tarasich | Hanna Soloshenko
Source: PROBLEMS IN PROGRAMMING (article, 2023-12-01)
Field: Chemistry — Physical and Theoretical Chemistry

Insertion semantics of quantum interactions The rapid development of the chemical industry and science and new challenges in the field of health care put forward increased demands for the development of the theory of organic and inorganic chemistry, biochemistry and biophysics, the search and implementation of new modelling and analysis methods, and the improvement of technological processes. One of the safe and fast methods of researching the properties and behavior of new materials and tools is the modelling of relevant experiments, in particular, computer molecular modelling based on mathematical models. Modelling the interactions between micro and macromolecules at the quantum level allows us to manipulate the substances’ electronic, magnetic, optical and other characteristics and consider the possibilities of creating new chemical bonds, molecular structures, phase transitions, quantum states, and so on. Accordingly, the main idea of our research is to apply the technology of algebraic modelling and quantum-chemical apparatus for the simulation and verification of experiments in physics, chemistry, and biology areas. The use of formal algebraic methods allows proving properties and finding relevant scenarios for the effective analysis of the behavior of various objects in real-time, considering not individual scenarios but sets of possible behaviors. At this research stage, we have developed a methodology for formalization complex organic and inorganic substances, chemical processes and reactions based on the formalization of the interaction of atoms and molecules at the level of quantum interactions. Computer science ; Field (mathematics) ; Quantum chemistry ; Semantics (computer science) ; Quantum ; Development (topology) ; Theoretical computer science ; Management science ; Biochemical engineering ; Chemistry ; Statistical physics ; Nanotechnology ; Molecule ; Physics ; Materials science ; Quantum mechanics ; Mathematics ; Programming language ; Engineering History and advancements in chemistry ; Computational Drug Discovery Methods
Authors: Máriusz Król
Source: Acta Physica Polonica A (article, 2023-11-01)
Field: Materials Science — Biomaterials

Calorimetric Analysis of Grain Modified Mg-Li Alloy Nowadays calorimetric analysis is a widely used method to study phase transformations occurring in the liquid or solid state in metals and alloys. Information on enthalpy, kinetics and transition characteristics can be obtained with the appropriate configuration of analytical apparatus and establishment of test procedures. In this work, an analysis of the transitions taking place in the grain-modified dual phase α(Mg)+ β(Li) Mg–9Li–1.5Al alloy was carried out on the samples taken from casts. The latent heat of the analysed alloys was captured using the UMSA device. The solidification process has been analysed using cooling curve analysis. The latent heat at a natural cooling rate 0.5°C/s was calculated based on the first derivative of the cooling curve. The released latent heat during crystallisation was estimated by applying the Newtonian technique of baseline. The results confirmed that calorimetric analysis can be successfully applied to study phase transitions in this type of magnesium alloy. The work uses thermal derivative analysis to present the possibility of specifying the latent heat of modified ultralight Mg–Li cast alloys. Latent heat ; Materials science ; Cooling curve ; Thermodynamics ; Alloy ; Thermal analysis ; Enthalpy ; Work (physics) ; Phase (matter) ; Metallurgy ; Thermal ; Chemistry ; Physics Magnesium Alloys: Properties and Applications ; Hydrogen Storage and Materials ; Aluminum Alloy Microstructure Properties
Authors: Sudad Adil Salih | Tariq M. Naife
Source: Al-Khwarizmi Engineering Journal (article, 2023-12-01)
Field: Materials Science — Materials Chemistry

The Remediation of Congo Red-Contaminated Groundwater by using a Permeable Reactive Barrier Through Modified Waterworks Sludge MgAl-LDH This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions. A strong correlation was indicated, with a coefficient of determination (R2) ≥ 0.97, when the model's predictions were compared to experimental values, indicating the accuracy of the model. Continuous transport exhibited earlier breakthrough points when the bed depth decreased and the initial concentration and flow rate increased. Permeable reactive barrier ; Sorbent ; Environmental remediation ; Hydroxide ; Congo red ; Groundwater ; Adsorption ; Groundwater remediation ; Chemistry ; Contamination ; Environmental engineering ; Chemical engineering ; Environmental science ; Materials science ; Environmental chemistry ; Inorganic chemistry ; Geology ; Geotechnical engineering Magnesium Oxide Properties and Applications
Authors: A. A. Smirnova | Maxim D Yablonskiy | Ekaterina I. Marchenko | Vadim Korolev | Nikolai Andreadi | Artem Mitrofanov
Source: arXiv (Cornell University) (preprint, 2023-11-30)
Field: Materials Science — Materials Chemistry

Artificial bees collect diverse conformers of small organic molecules The conformational mobility of organic molecules defined as a variability of practically accessible conformers plays a critical role in determining electronic, chemical, and physical properties within computational methods. At the same time, there is a challenge of identifying compact set of global and local conformers for the comprehensive description of potential energy surface. Here we apply nature-inspired algorithms to resolve this issue. Among all the considered algorithms, the artificial bee colony optimizer exhibits the highest performance in discovering conformers detected both in gas and condensed phases. We hope that our approach enables researchers to make a next step in organic crystal packing studies. Conformational isomerism ; Set (abstract data type) ; Molecule ; Organic molecules ; Potential energy surface ; Chemical physics ; Computer science ; Statistical physics ; Computational chemistry ; Chemistry ; Physics ; Organic chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Molecular spectroscopy and chirality
Authors: Addison Marie Arave
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2023-10-25)
Field: Materials Science — Materials Chemistry

Nuclear Science &amp; Technology March 2023 Highlights 2017 Edition, with exceptions and limitations, through NRC Regulatory Guide 1.87 (Revision 2) in January 2023-The endorsement included new high temperature design evaluation method code cases. Division 5 rules govern the construction of vessels, piping, pumps, valves, supports, core support structures and nonmetallic core components for use in high temperature reactor systems Nuclear science ; Environmental science ; Nuclear engineering ; Engineering Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies
Authors: Nguyn Dng | Nhn | Nguyn Bnh | Nguyn Thnh | Khi S Dng | Xc L | Gi M | Langmuir | Khoa Hc | Hc Hu | Trng i | Qung Bnh | A Jamshidi-Zanjani | M Saeedi | L Li | H Cheng | T Zhou | Q Li | L Lu | C Lin | K Sumathi | S Mahimairaja | R Naidu | B Deng | A Stone | R Anderson | H Lyu | H Zhao | J Tang | Y Gong | Y Huang | Q Wu | N Meunier | P Drogui | C Montan | R Hausler | G Mercier | J-F Blais | S Sahu | P Meshram | B Pandey | V Kumar | T Mankhand | P Religa | A Kowalik | P Gierycz | A Golder | A Samanta | S Ray | L Mandi | S Tiglyene | A Jaouad | N Kuganathan | S Anurakavan | P Abiman | P Iyngaran | E Gkanas | A Chroneos | S Tabesh | F Davar | Loghman-Estarki Mr | S Khan | R Zaidi | S Hassan | I Farooqi | A Azam | S Ding | W Wang | Y Wu | J Gu | Y He | F | W S Un | W Pan | F Wang | N Xu | Y Ren | N Li | J Feng | T Luan | Q Wen | Z Li | Z Beji | A Hanini | L Smiri | J Gavard | K Kacem | F Villain | J Mozaffari | M Nasr | B | J Li | H Yuan | G Li | Y Liu | J Leng | M Naseri | E Saion | H Ahangar | M Hashim
Source: Journal of Science and Technology - HaUI (article, 2023-06-26)
Field: Materials Science — Materials Chemistry

Hấp phụ crom (III) trong dung dịch nước bằng các hạt nano mangan ferrite In the present paper, nanosized manganese ferrite material is synthesized by the hydrothermal method at temperatures of 190C in 12 hours.The size and microstructure of MnFe2O4 were analyzed based on X-ray diffraction (XRD), scanning electron microscopy (SEM).The nitrogen adsorption-desorption was used for determination of surface area (Brunauer -Emmett -Teller (BET)) and porosity of the fabricated material.The adsorption behavior of Cr (III) using a new magnetic adsorbent is investigated.The adsorption characteristic and Cr (III) removal efficiency of the adsorbent have been determined by investigating the influence of operating variables such as dosage of manganese ferrite.The maximum Cr (III) sorption capacity was found to be 22.371mg/g and obtained using 0.08g/100mL MnFe2O4 when pH equals 5, a temperature of 25C, and contact time as 24 hours.The Langmuir, Freundlich and Dubinin -Radushkevich models were used to fit the experimental data and these showed good correlations. Chemistry Magnesium Oxide Properties and Applications