jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pankaj Kumar | Saurabh Kabra | Jacqueline M. Cole
Source: Scientific Data (article, 2024-11-23)
Field: Materials Science — Materials Chemistry

A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young's modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain. Strain (injury) ; Stress (linguistics) ; Database ; Computer science ; Information retrieval ; Biology ; Philosophy Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Material Properties and Failure Mechanisms
Authors: Kiran Kumar Vunnam | Naresh Kumar Katari | Nagalakshmi Jeedimalla | Rambabu Gundla | Jayaprakash Kanijam Raghupathi
Source: Applied Research (article, 2024-10-13)
Field: Chemistry — Organic Chemistry

Design, Synthesis, and Biological Evaluation of Novel Heterocyclic Derivatives of 2,4‐Thiazolidine Dione as Anti‐Cancer Agents ABSTRACT This study explores the development of novel 2,4‐thiazolidinedione derivatives as potential anticancer agents. We report the synthesis of 15 novel analogs utilizing a strategic approach focused on intermediate diversification. Key intermediates, (Z)‐5‐([1,1′‐biphenyl]‐4‐ylmethylene)thiazolidine‐2,4‐dione 5a and (Z)‐5‐(benzo[1,3]dioxol‐5‐ylmethylene)thiazolidine‐2,4‐dione 5b , were synthesized via Knoevenagel condensation and acetal formation reactions, respectively. Subsequent N‐alkylation reactions provided a platform for introducing diverse functionalities and exploring structure–activity relationships to optimize the medicinal chemistry profile of these novel compounds. The synthesized compounds were tested against various human cancer cell lines, including for breast (MCF‐7, MDA‐MB‐453), lung (A549), and prostate (PC‐3) cancers, using an MTT assay. Compounds 8c and 10g emerged as particularly promising, exhibiting activity against all tested cell lines with IC 50 values between 3.41 ± 0.51 and 40 μM. These compounds also induced apoptosis, suggesting that they inhibit cell proliferation through this cell death pathway. Moreover, relative molecular docking studies provided evidence that compound 8c likely functions by intercalating with DNA. Thiazolidine ; Combinatorial chemistry ; Chemistry ; Stereochemistry ; Computational biology ; Biology Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Quinazolinone synthesis and applications
Authors: Krzysztof Wieczerzak | Fedor F. Klimashin | Amit Sharma | Stefanie Altenried | Katharina Maniura‐Weber | Qun Ren | Johann Michler
Source: ACS Applied Materials & Interfaces (article, 2024-10-25)
Field: Materials Science — Materials Chemistry

Developing a High-Throughput Platform for the Discovery of Sustainable Antibacterial Materials Healthcare-associated infections (HCAIs) pose a significant global health challenge, exacerbated by the rising threat of antimicrobial resistance (AMR). This study introduces a high-throughput platform designed to identify sustainable antibacterial surfaces, exemplified by a copper-silver-zirconium (CuAgZr) alloy library. Utilizing combinatorial synthesis and advanced characterization techniques, material libraries (MatLibs) are generated and evaluated to rapidly screen diverse alloy compositions. The results demonstrate the ability to reproducibly create alloys with significant antimicrobial properties and high hardness, making them suitable for biomedical applications. The study highlights the critical role of compositional precision in developing materials that balance mechanical strength with antibacterial efficacy. Additionally, this approach ensures significant cost-effectiveness, facilitating the identification of economically viable alloy compositions. This research underscores the potential of high-throughput materials science to expedite the discovery of sustainable solutions for reducing HCAIs and addressing AMR, signaling a leap forward in sustainable healthcare material development. Materials science ; Throughput ; Nanotechnology ; Drug discovery ; Systems engineering ; Computer science ; Biology ; Bioinformatics ; Engineering ; Telecommunications Nanoparticles: synthesis and applications ; Chemistry and Chemical Engineering ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Sanket N. Aher | S Sonawane | Pawan R. Sonawane | Khemchand R. Surana | Sunil K. Mahajan | Dhananjay M. Patil | Pramod Nanasaheb Katkade
Source: Biosciences Biotechnology Research Asia (article, 2024-07-01)
Field: Chemistry — Organic Chemistry

Insilico Drug Design, Synthesis and Evaluation of Anti-inflammatory Activity Pyrimidine Analogue ABSTRACT: A class of pyrimidine-based molecules was designed for their in silico study, synthesis, and testing for their in vitro anti-inflammatory evaluation. The compounds were tested in an in silico study against anti-inflammatory proteins like FAAH (PDB ID: 4DO3) by using two different software programmes, Ace-dock and Arguslab, and showed promising signs of being a possible drug candidate. In silico toxicity prediction was also done on these compounds. The drug-likeness screening was done to satisfy the Lipinsky rule of five. In our recent investigation, we focused on environment-friendly approaches to synthesising pyrimidine derivatives in the presence of an ethanolic potassium hydroxide solution. The Claisen-Schmidt condensation of acetophenone and various substituted benzaldehydes produces pyrimidine. The pyrimidine derivatives 2a-p and 3a-c were synthesized. The synthesised molecules were screened on the basis of an in silico study, and the molecules were selected and subjected to a check for their in vitro anti-inflammatory activity. A test called the albumin denaturation assay was used to see how much heat-induced protein denaturation could be stopped. The compounds that were synthesised and the standard drug, diclofenac sodium, both stopped protein denaturation at levels ranging from 100 to 500 ppm. Maximum inhibition of 68.59% was observed at the concentration of 100 ppm of compound 2d. Diclofenac sodium showed the maximum inhibition, which was 80.58% at a concentration of 100 ppm. It is concluded that 2d has the potential for further investigation for anti-inflammatory activity. Diclofenac Sodium ; In silico ; Pyrimidine ; Chemistry ; Denaturation (fissile materials) ; In vitro ; Protein Data Bank (RCSB PDB) ; Combinatorial chemistry ; Drug ; Pharmacology ; Biochemistry ; Chromatography ; Nuclear chemistry ; Biology Synthesis and biological activity ; Computational Drug Discovery Methods ; Pharmacological Effects of Natural Compounds
Authors: Mingrui Chen | Carles Batlle | Bryan Escachx | Ramon Costa‐Castelló | Jing Na
Source: Journal of Energy Storage (article, 2024-06-13)
Field: Materials Science — Materials Chemistry

Sensitivity analysis and calibration for a two-dimensional state-space model of metal hydride storage tanks based on experimental data In this paper, a state-space model of a metal hydride tank is formulated and analyzed in detail. Firstly, a three-dimensional state-space model of the metal hydride tank is simplified by assuming that the tank temperature can be measured. Secondly, the model is completed with a pipe model, which allows to compute the input flow from the pipe pressure that can be easily measured. The proposed model solves the problem that the conventional metal hydride tank models usually take the mass flow rate as input and ignore the pressure as system input. Thirdly, the first-order trajectory sensitivity analysis method is adopted to determine the sensitivity of selected unknown parameters. Latter, the particle swarm optimization algorithm is used to estimate the unknown model parameters from experimental data. Finally, a comparison between experimental data and simulation results demonstrates that the proposed model can reflect the dynamic characteristics of the metal hydride tank. • A 2D state-space model is proposed for pipe pressure control input. • The First Trajectory Sensitivity Analysis method for the MH tank model. • Sensitivity analysis is considered under three different operating conditions. • The simplified model is calibrated and validated using experimental data. Sensitivity (control systems) ; Hydride ; Calibration ; Key (lock) ; State-space representation ; State space ; Space (punctuation) ; State (computer science) ; Environmental science ; Computer science ; Metal ; Engineering ; Materials science ; Algorithm ; Statistics ; Mathematics ; Electronic engineering ; Metallurgy ; Operating system Hydrogen Storage and Materials ; Advanced Battery Technologies Research ; Spacecraft and Cryogenic Technologies
Authors: İsmail KARAMAN | Ali Ajder | İsmail Nakir
Source: IEEE Access (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Development of an Industrial Partial Discharge Calibrator and Its Performance Tests In industrial electromechanical manufacturing, ensuring the accuracy of electrical partial discharge measurements is crucial for the reliability and efficiency of electrical power systems. The cornerstone of such precision is a well-designed partial discharge calibrator that strictly aligns with the IEC 60270 standard parameters, including apparent charge, rise time, and pulse repetition frequency. This research delineates the systematic development and subsequent performance evaluations of an innovative industrial partial discharge calibrator. The calibrator uniquely integrates advanced functionality while maintaining cost efficiency, offering an alternative to the current partial discharge calibrator market. Its design allows for a broad spectrum of pulse frequency adjustments, making it adaptable to various apparent charge bandwidths and highlighting its adaptability for high-voltage applications. Building upon the foundational understanding of partial discharge as characterized by standards such as IEC 60270, the study underscores the calibrator’s capacity to elevate the standards of partial discharge measurements within high-voltage equipment. Partial discharge ; Computer science ; Reliability engineering ; Electrical engineering ; Engineering ; Voltage High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrostatic Discharge in Electronics
Authors: Syed Amjad Ali | Numan Emre Gümüş | Muhammad Aasım
Source: Environmental Science and Pollution Research (article, 2024-06-11)
Field: Materials Science — Materials Chemistry

A unified framework of response surface methodology and coalescing of Firefly with random forest algorithm for enhancing nano-phytoremediation efficiency of chromium via in vitro regenerated aquatic macrophyte coontail (Ceratophyllum demersum L.) Nano-phytoremediation is a novel green technique to remove toxic pollutants from the environment. In vitro regenerated Ceratophyllum demersum (L.) plants were exposed to different concentrations of chromium (Cr) and exposure times in the presence of titania nanoparticles (TiO<sub>2</sub>NPs). Response surface methodology was used for multiple statistical analyses like regression analysis and optimizing plots. The supplementation of NPs significantly impacted Cr in water and Cr removal (%), whereas NP × exposure time (T) statistically regulated all output parameters. The Firefly metaheuristic algorithm and the random forest (Firefly-RF) machine learning algorithms were coalesced to optimize hyperparameters, aiming to achieve the highest level of accuracy in predicted models. The R<sup>2</sup> scores were recorded as 0.956 for Cr in water, 0.987 for Cr in the plant, 0.992 for bioconcentration factor (BCF), and 0.957 for Cr removal through the Firefly-RF model. The findings illustrated superior prediction performance from the random forest models when compared to the response surface methodology. The conclusion is drawn that metal-based nanoparticles (NPs) can effectively be utilized for nano-phytoremediation of heavy metals. This study has uncovered a promising outlook for the utilization of nanoparticles in nano-phytoremediation. This study is expected to pave the way for future research on the topic, facilitating further exploration of various nanoparticles and a thorough evaluation of their potential in aquatic ecosystems. Firefly algorithm ; Phytoremediation ; Bioconcentration ; Ceratophyllum demersum ; Random forest ; Response surface methodology ; Chromium ; Environmental science ; Algorithm ; Computer science ; Environmental chemistry ; Machine learning ; Aquatic plant ; Chemistry ; Bioaccumulation ; Biology ; Ecology ; Heavy metals ; Particle swarm optimization ; Macrophyte Nanoparticles: synthesis and applications
Authors: Tom Pan | Chen Dun | Shikai Jin | Mitchell D. Miller | Anastasios Kyrillidis | G.N. Phillips
Source: Structural Dynamics (article, 2024-07-01)
Field: Materials Science — Materials Chemistry

<tt>CrysFormer</tt>: Protein structure determination via Patterson maps, deep learning, and partial structure attention Determining the atomic-level structure of a protein has been a decades-long challenge. However, recent advances in transformers and related neural network architectures have enabled researchers to significantly improve solutions to this problem. These methods use large datasets of sequence information and corresponding known protein template structures, if available. Yet, such methods only focus on sequence information. Other available prior knowledge could also be utilized, such as constructs derived from x-ray crystallography experiments and the known structures of the most common conformations of amino acid residues, which we refer to as partial structures. To the best of our knowledge, we propose the first transformer-based model that directly utilizes experimental protein crystallographic data and partial structure information to calculate electron density maps of proteins. In particular, we use Patterson maps, which can be directly obtained from x-ray crystallography experimental data, thus bypassing the well-known crystallographic phase problem. We demonstrate that our method, CrysFormer, achieves precise predictions on two synthetic datasets of peptide fragments in crystalline forms, one with two residues per unit cell and the other with fifteen. These predictions can then be used to generate accurate atomic models using established crystallographic refinement programs. Computer science ; Protein structure ; Artificial neural network ; Crystal structure ; Crystallography ; Deep learning ; Artificial intelligence ; Algorithm ; Data mining ; Chemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Diogo Dias | Leonor Resina | Frederico Castelo Ferreira | Paola Sanjuan‐Alberte | Teresa Esteves
Source: Materials Advances (article, 2024-01-01)
Field: Materials Science — Biomaterials

Synthesis strategies and cancer therapy applications of PEDOT nanoparticles PEDOT nanoparticles combine controlled drug release, and photothermal ablation due to their electrical and thermal properties. This review delves into their synthesis methods, characterization and potential in targeted cancer therapies. Cancer therapy ; PEDOT:PSS ; Nanotechnology ; Nanoparticle ; Materials science ; Cancer ; Medicine ; Internal medicine Nanoparticle-Based Drug Delivery ; Conducting polymers and applications ; Nanoplatforms for cancer theranostics
Authors: Sophie Hermann | Florian Sammüller | Matthias Schmidt
Source: Journal of Physics A Mathematical and Theoretical (preprint, 2024-04-04)
Field: Materials Science — Materials Chemistry

Noether invariance theory for the equilibrium force structure of soft matter Abstract We give details and derivations for the Noether invariance theory that characterizes the spatial equilibrium structure of inhomogeneous classical many-body systems, as recently proposed and investigated for bulk systems (Sammüller et al 2023 Phys. Rev. Lett. 130 268203). Thereby an intrinsic thermal symmetry against a local shifting transformation on phase space is exploited on the basis of the Noether theorem for invariant variations. We consider the consequences of the shifting that emerge at second order in the displacement field that parameterizes the transformation. In a natural way the standard two-body density distribution is generated. Its second spatial derivative is thereby balanced by two further and different two-body correlation functions, which respectively introduce thermally averaged force correlations and force gradients in a systematic and microscopically sharp way into the framework. Separate exact self and distinct sum rules express this balance. We exemplify the validity of the theory on the basis of computer simulations for the Lennard–Jones gas, liquid, and crystal, the Weeks–Chandler–Andersen fluid, monatomic Molinero–Moore water at ambient conditions, a three-body-interacting colloidal gel former, the Yukawa and soft-sphere dipolar fluids, and for isotropic and nematic phases of Gay–Berne particles. We describe explicitly the derivation of the sum rules based on Noether’s theorem and also give more elementary proofs based on partial phase space integration following Yvon’s theorem. Noether's theorem ; Soft matter ; Mathematical economics ; Physics ; Classical mechanics ; Mathematics ; Statistical physics ; Theoretical physics ; Mathematical physics ; Engineering ; Lagrangian Material Dynamics and Properties ; Advanced Thermodynamics and Statistical Mechanics ; Theoretical and Computational Physics
Authors: Mariko Kojima | Satoshi Abe | Tadaomi Furuta | Kunio Hirata | Xinchen Yao | Ayako Kobayashi | Ririko Kobayashi | Takafumi Ueno
Source: Proceedings of the National Academy of Sciences (article, 2024-06-11)
Field: Materials Science — Materials Chemistry

High-throughput structure determination of an intrinsically disordered protein using cell-free protein crystallization Intrinsically disordered proteins (IDPs) play a crucial role in various biological phenomena, dynamically changing their conformations in response to external environmental cues. To gain a deeper understanding of these proteins, it is essential to identify the determinants that fix their structures at the atomic level. Here, we developed a pipeline for rapid crystal structure analysis of IDP using a cell-free protein crystallization (CFPC) method. Through this approach, we successfully demonstrated the determination of the structure of an IDP to uncover the key determinants that stabilize its conformation. Specifically, we focused on the 11-residue fragment of c-Myc, which forms an α-helix through dimerization with a binding partner protein. This fragment was strategically recombined with an in-cell crystallizing protein and was expressed in a cell-free system. The resulting crystal structures of the c-Myc fragment were successfully determined at a resolution of 1.92 Å and we confirmed that they are identical to the structures of the complex with the native binding partner protein. This indicates that the environment of the scaffold crystal can fix the structure of c-Myc. Significantly, these crystals were obtained directly from a small reaction mixture (30 µL) incubated for only 72 h. Analysis of eight crystal structures derived from 22 mutants revealed two hydrophobic residues as the key determinants responsible for stabilizing the α-helical structure. These findings underscore the power of our CFPC screening method as a valuable tool for determining the structures of challenging target proteins and elucidating the essential molecular interactions that govern their stability. Crystallization ; Protein crystallization ; Crystallography ; Protein structure ; Chemistry ; Biophysics ; Crystal structure ; Residue (chemistry) ; Mutant ; Biochemistry ; Biology ; Gene Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Enming Shi | Xu Zhong | Tian Wang | Xiaoguang Li | Chunguang Bu | Xingang Zhao
Source: Frontiers in Neuroscience (article, 2024-01-31)
Field: Materials Science — Materials Chemistry

Adaptive control for shape memory alloy actuated systems with applications to human–robot interaction Introduction Shape memory alloy (SMA) actuators are attractive options for robotic applications due to their salient features. So far, achieving precise control of SMA actuators and applying them to human-robot interaction scenarios remains a challenge. Methods This paper proposes a novel approach to deal with the control problem of a SMA actuator. Departing from conventional mechanism models, we attempt to describe this nonlinear plant using a gray-box model, in which only the input current and the output displacement are measured. The control scheme consists of the model parameters updating and the control law calculation. The adaptation algorithm is founded on the multi-innovation concept and incorporates a dead-zone weighted factor, aiming to concurrently reduce computational complexities and enhance robustness properties. The control law is based on a PI controller, the gains of which are designed by the pole assignment technique. Theoretical analysis proves that the closed-loop performance can be ensured under mild conditions. Results The experiments are first conducted through the Beckhoff controller. The comparative results suggest that the proposed adaptive PI control strategy exhibits broad applicability, particularly under load variations. Subsequently, the SMA actuator is designed and incorporated into the hand rehabilitation robot. System position tracking experiments and passive rehabilitation training experiments for various gestures are then conducted. The experimental outcomes demonstrate that the hand rehabilitation robot, utilizing the SMA actuator, achieves higher position tracking accuracy and a more stable system under the adaptive control strategy proposed in this paper. Simultaneously, it successfully accommodates hand rehabilitation movements for multiple gestures. Discussion The adaptive controller proposed in this paper takes into account both the computational complexity of the model and the accuracy of the control results, Experimental results not only demonstrate the practicality and reliability of the controller but also attest to its potential application in human-machine interaction within the field of neural rehabilitation. SMA* ; Actuator ; Computer science ; Robustness (evolution) ; Control theory (sociology) ; Exoskeleton ; Robot ; Controller (irrigation) ; Control engineering ; Nonlinear system ; Adaptive control ; Artificial intelligence ; Simulation ; Engineering ; Control (management) ; Algorithm Shape Memory Alloy Transformations ; Soft Robotics and Applications ; Prosthetics and Rehabilitation Robotics