jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fan Wang | Menghan Tian | Baolei Liu | Zelin Lu | Yao Wang | Ze Zheng | Jiaqi Song | Xiaolan Zhong
Source: Research Square (preprint, 2024-03-04)
Field: Materials Science — Polymers and Plastics

Miniaturized on-chip spectrometer enabled by electrochromic modulation Abstract Miniaturized on-chip spectrometers with small footprints, lightweight, and low cost are in great demand for portable optical sensing, lab-on-chip systems, and so on. Such miniaturized spectrometers are usually based on engineered spectral response units and then reconstruct unknown spectra with algorithms. However, due to the limited footprints of computational on-chip spectrometers, the recovered spectral resolution is limited by the number of integrated spectral response units/filters. Thus, it is challenging to improve the spectral resolution without increasing the number of used filters. Here we present a computational on-chip spectrometer using electrochromic filters that can be electrochemically modulated to increase the efficient sampling number for higher spectral resolution. These filters are directly integrated on top of the photodetector pixels, and the spectral modulation of the filters results from redox reactions during the dual injection of ions and electrons into the electrochromic material. We experimentally demonstrate that the spectral resolution of the proposed spectrometer can be effectively improved as the number of applied voltages increases. The average difference of the peak wavelengths between the reconstructed and the reference spectra decreases from 14.48 nm to 2.57 nm. We also demonstrate the proposed spectrometer can be worked with only four or two filter units, assisted by electrochromic modulation. This strategy suggests a new way to enhance the performance of miniaturized spectrometers with tunable spectral filters for high resolution, low-cost, and portable spectral sensing, and would also inspire the exploration of other stimulus responses such as photochromic and force-chromic, etc, on computational spectrometers. Electrochromism ; Modulation (music) ; Spectrometer ; Chip ; Electrochromic devices ; Optoelectronics ; Materials science ; Electronic engineering ; Computer science ; Chemistry ; Telecommunications ; Physics ; Optics ; Engineering ; Electrode Transition Metal Oxide Nanomaterials ; Advanced Memory and Neural Computing ; Photonic and Optical Devices
Authors: William M. Jacobs | W. Benjamin Rogers
Source: arXiv (Cornell University) (preprint, 2024-09-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Assembly of Complex Colloidal Systems Using DNA Nearly thirty years after its inception, the field of DNA-programmed colloidal self-assembly has begun to realize its initial promise. In this review, we summarize recent developments in designing effective interactions and understanding the dynamic self-assembly pathways of DNA-coated nanoparticles and microparticles, as well as how these advances have propelled tremendous progress in crystal engineering. We also highlight exciting new directions showing that new classes of subunits combining nanoparticles with DNA origami can be used to engineer novel multicomponent assemblies, including structures with self-limiting, finite sizes. We conclude by providing an outlook on how recent theoretical advances focusing on the kinetics of self-assembly could usher in new materials-design opportunities, like the possibility of retrieving multiple distinct target structures from a single suspension or accessing new classes of materials that are stabilized by energy dissipation, mimicking self-assembly in living systems. Colloid ; DNA ; Computer science ; Nanotechnology ; Business ; Materials science ; Biology ; Engineering ; Chemical engineering ; Genetics Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Diatoms and Algae Research
Authors: Bisma Maulana Aryaputra | Auliya Eka Safitri | Dayana Khalda Razita | Sri Setyani | Alifia Zhafirah Mulfiana
Source: Journal of Chemical Engineering Research Progress (article, 2024-12-27)
Field: Materials Science — Materials Chemistry

Enhancing the Yield and Mass Production of Vinyl Chloride Production from Ethylene and Chloride through EDC Vapor Recovery in Direct Chlorination Process Vinyl chloride (C2H3Cl) is produced using ethylene (C2H4) and chlorine (Cl) as primary raw materials. In Indonesia, the demand for raw materials to produce plastics, especially PVC, continues to grow each year. The chosen method is the direct chlorination of ethylene, resulting in the production of 1,2-dichloroethane (EDC). The process involves two conversion reactors, the CRV-100 and CRV-101. The CRV-100 reactor produces EDC vapor and some EDC compounds. However, these compounds are often not recovered and are released into the atmosphere. To increase efficiency and yield the process by recycling maximize the reactants, the EDC feedstock is replenished by recycling the top product from the CRV-100 reactor. After cooling and separation, liquid EDC is recovered and reintroduced, increasing vinyl chloride production, resulting the purity has increased from 93.93% to 97.14%, the total mass production rises from 2232.8919 kg/h to 5477.0938 kg/h before optimization, representing a 145.29% yield, reflecting a significant improvement in production efficiency. Copyright © 2025 by Authors, Published by Universitas Diponegoro and BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0). Yield (engineering) ; Ethylene ; Chloride ; Production (economics) ; Chemistry ; Vinyl chloride ; Process (computing) ; Organic chemistry ; Pulp and paper industry ; Materials science ; Catalysis ; Engineering ; Computer science ; Metallurgy Catalytic Processes in Materials Science ; Extraction and Separation Processes ; Catalysis and Oxidation Reactions
Authors: Jiulin Xia
Source: Scalable Computing Practice and Experience (article, 2024-04-12)
Field: Chemistry — Analytical Chemistry

Construction of an Intelligent Identification Model for Drugs in Near Infrared Spectroscopy and Research on Drog Classification based on Improved Deep Algorithm Near-infrared spectroscopy has important applications in drug and food identification. Combining machine learning with near-infrared spectroscopy to achieve intelligent identification of drugs has become a research hotspot in recent years. To solve the problem of machine learning’s inefficiency in classifying small-scale data, a drug identification model based on near-infrared spectroscopy combined with a random fading depth belief network is proposed. Aiming at the problem that the training time of the machine learning algorithm is too long, the extreme learning machine is used to replace the back propagation algorithm to optimize the stack sparse auto-encoder network. Additionally, the stack sparse auto-encoder algorithm based on extreme learning machine algorithm is constructed. The study found that the precision of the Dropout Deep Belief Network model was 99.12%, which was higher than the other three models. Additionally, the area under the curve value of the Dropout Deep Belief Network model was 0.87, which was 0.04 higher than the binary whale optimization algorithm model, 0.26 higher than the factor decomposition machine and depth neural network model, and 0.05 higher than the random forest network model. The sparse auto-encoder algorithm based on the extreme learning machine algorithm achieved a precision of 99.72%. The study proposes two algorithm models that can effectively identify drugs using near-infrared spectroscopy. This has a positive impact on the medical industry and the safety of patients' lives and health. Computer science ; Artificial intelligence ; Extreme learning machine ; Algorithm ; Machine learning ; Autoencoder ; Sparse approximation ; Dropout (neural networks) ; Random forest ; Deep learning ; Artificial neural network Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Arthur Clini de Souza | Stéphane Lanteri | Hugo E. Hernández‐Figueroa | Marco Abbarchi | David Grosso | Badre Kerzabi | Mahmoud Elsawy
Source:  (article, 2024-06-18)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inverse design of bright, dielectric metasurfaces color filters based on back-propagation and multi-valued artificial neural networks The present work showcases an innovative optimization methodology based on deep learning that combines Multi- Valued Artificial Neural Networks and back-propagation optimization. The methodology addresses the inherent limitations of conventional approaches when employed in isolation. We applied the proposed methodology to design structural color filters that surpasses the sRGB gamut while preserving fabrication constraints. Gamut ; Computer science ; Artificial neural network ; Backpropagation ; Inverse ; Artificial intelligence ; Deep learning ; Electronic engineering ; Engineering ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Photonic Crystals and Applications
Authors: Fan Zhang | Hua Hao | Minghe Cao | Zhonghua Yao | Shuai Fu | Hanxing Liu
Source: Crystals (article, 2024-01-19)
Field: Materials Science — Materials Chemistry

Piezoelectric Properties and Thermal Stability of Pb(Yb1/2Nb1/2)O3-BiScO3-PbTiO3 Ternary Ceramics Piezoelectric ceramics with excellent piezoelectric properties and a high Curie temperature are important for numerous electromechanical devices in a broad range of temperature environments. In this work, the relaxor ferroelectric Pb(Yb1/2Nb1/2)O3 end member was selected to be introduced into a BiScO3-PbTiO3 high-temperature piezoelectric ceramic to reduce the dielectric loss and improve the piezoelectric properties while slightly reducing the Curie temperature. The phase structure and dielectric, ferroelectric and piezoelectric properties of 0.025Pb(Yb1/2Nb1/2)O3-(0.975−x)BiScO3-xPbTiO3 (0.60 ≤ x ≤ 0.63) ceramics were systematically analyzed, and the best electrical properties were observed in the morphotropic phase boundary region x = 0.61 with d33 = 370 pC/N, kp = 44%, Pr = 33.9 μC/cm2. Importantly, no significant depolarization was observed in the x = 0.61 ceramic from room temperature to 290 °C, demonstrating its good thermal stability and potential applications in a wide range of temperature environments. Materials science ; Curie temperature ; Piezoelectricity ; Phase boundary ; Dielectric ; Ferroelectricity ; Ceramic ; Atmospheric temperature range ; Thermal stability ; Ternary operation ; Composite material ; Dielectric loss ; Phase (matter) ; Condensed matter physics ; Optoelectronics ; Thermodynamics ; Ferromagnetism ; Chemistry Ferroelectric and Piezoelectric Materials ; Dielectric materials and actuators ; Acoustic Wave Resonator Technologies
Authors: Yicheng Yang
Source: BIO Web of Conferences (article, 2024-01-01)
Field: Materials Science — Biomaterials

Overview of the Current State of Research on Metamaterials in Biomedicine This paper reviews the wide range of applications and current research status of metamaterials in the biomedical field, demonstrating their great potential in enhancing diagnostic accuracy, promoting tissue regeneration, and treating diseases. This paper reviews the wide range of applications and current research status of metamaterials in the biomedical field, demonstrating their great potential in enhancing diagnostic accuracy, promoting tissue regeneration, and treating diseases. performance of traditional materials, metamaterials have made remarkable progress in the biomedical field by virtue of their unique physical properties and high designability. In the case of terahertz metamaterials, precise detection of biomolecules and tissues has been achieved by combining their high sensitivity with their high designability. In the case of terahertz metamaterials, precise detection of biomolecules and tissues has been achieved by combining their high sensitivity with the high penetrability of biological tissues. Mechanical metamaterials, on the other hand, promote the sensitivity enhancement of flexible strain sensors and the advancement of tissue engineering by simulating the mechanical behavior of biological tissues. In addition, multifunctional metamaterials such as light-driven, thermally-driven, magnetic, chiral, and electrically-driven have opened up new possibilities in the biotechnology industry. In addition, multifunctional metamaterials such as light-driven, thermally-driven, magnetic, chiral, and electrically-driven have opened up new possibilities in the biomedical field. Despite the challenges of biocompatibility and control of material degradation rate, metamaterials are still promising for applications in disease diagnosis, treatment, and drug discovery. Future research should focus on improving material biocompatibility, developing advanced manufacturing technologies, promoting personalized medicine, and strengthening Future research should focus on improving material biocompatibility, developing advanced manufacturing technologies, promoting personalized medicine, and strengthening interdisciplinary collaborations to further explore the potential of metamaterials in biomedicine. Metamaterial ; Nanotechnology ; Materials science ; Biomolecule ; Computer science ; Optoelectronics Silk-based biomaterials and applications ; Polydiacetylene-based materials and applications ; Advanced Materials and Mechanics
Authors: Nannar AR
Source: Pharmaceutical Drug Regulatory Affairs Journal (article, 2024-01-29)
Field: Materials Science — Biomaterials

Novel Advancements in Mouth Dissolving Film Technology Mouth dissolving film (MDF) technology has emerged as an innovative drug delivery platform offering rapid drug absorption and enhanced patient compliance. This comprehensive review explores recent advancements in MDF technology, focusing on formulation strategies, manufacturing techniques, and applications in pharmaceutical and nutraceuticals industries. Dissolution ; Materials science ; Nanotechnology ; Chemical engineering ; Engineering Nanocomposite Films for Food Packaging ; Electrospun Nanofibers in Biomedical Applications ; Biopolymer Synthesis and Applications
Authors: Dmitriy D. Matyushin | Anastasia Yu. Sholokhova
Source: Сорбционные и хроматографические процессы (article, 2024-10-21)
Field: Chemistry — Spectroscopy

Эмпирические уравнения для прогнозирования газохроматографических индексов удерживания для неподвижной фазы DB-35MS На данный момент большинство работ по прогнозированию индексов удерживания по структуре молекулы посвящены стандартным неподвижным фазам: полидиметилсилоксану, 5%-фенил-метилполисилоксану и полиэтиленгликолю. Информация об индексах удерживания на этих неподвижных фазах содержится в базе данных NIST, соответственно, доступен большой набор данных для обучения и возможно применение глубокого обучения. Это позволяет создать точные и универсальные модели для прогнозирования индексов удерживания. Однако другие неподвижные фазы также активно применяются в исследованиях при хромато-масс-спектрометрической идентификации компонентов сложных смесей. Создание алгоритмов прогнозирования индексов удерживания для этих неподвижных фаз также могло бы иметь большое значение. В данной работе рассматривается задача прогнозирования индексов удерживания для неподвижной фазы DB-35MS (35%-фенил-полидиметилсилоксан). Рассмотрен набор данных об удерживании 52 летучих органических соединений, содержащихся в бутонах сирени, для этой неподвижной фазы. Предложены эмпирические уравнения, в которые входят: вычисленный с помощью глубокого обучения индекс удерживания для неподвижной фазы DB-5 (5%-фенил-метилполисилоксан) и ряд молекулярных дескрипторов, рассчитанных с помощью фреймворка RDKit. Показано, что использование сложных топологических молекулярных дескрипторов, а так же величин рассчитанных с помощью методов квантовой химии, не дает сильного повышения точности по сравнению с наиболее простыми целочисленными молекулярными дескрипторами, такими как число связей, подверженных внутреннему вращению. В то же время применение индексов удерживания для неподвижной фазы DB-5, спрогнозированных с помощью глубокого обучения, в качестве молекулярного дескриптора, приводит к сильнейшему уменьшению ошибки прогнозирования по сравнению с применением только обычных молекулярных дескрипторов. Если вместо индексов удерживания, спрогнозированных для неподвижной фазы DB-5, использовать индексы удерживания, спрогнозированные для неподвижной фазы DB-624, то также можно достигнуть относительно высокой точности прогноза. В работе представлены линейные уравнения, которые могут быть использованы на практике для вычисления индексов удерживания летучих соединений растительного происхождения, содержащих углерод, водород и кислород, для неподвижной фазы DB-35MS и аналогичных неподвижных фаз. Представлено также менее точное, но более универсальное уравнение, содержащее в себе только спрогнозированный с помощью глубокого обучения индекс удерживания для неподвижной фазы DB-5 в качестве молекулярного дескриптора. Достигнутые значения среднеквадратичной ошибки, средней абсолютной ошибки и медианной абсолютной ошибки составили 28.9, 19.3 и 11.8 единиц соответственно. Medicine Molecular spectroscopy and chirality ; Computational Drug Discovery Methods ; Advanced Chemical Physics Studies
Authors: Christine A. Morcos | Nesreen S. Haiba | Rafik W. Bassily | Marwa M. Abu‐Serie | Amira F. El‐Yazbi | Omar Soliman | Sherine N. Khattab | Mohamed Teleb
Source: Journal of Enzyme Inhibition and Medicinal Chemistry (article, 2024-11-08)
Field: Chemistry — Organic Chemistry

Structure optimization and molecular dynamics studies of new tumor-selective <i>s</i> -triazines targeting DNA and MMP-10/13 for halting colorectal and secondary liver cancers A series of triazole-tethered triazines bearing pharmacophoric features of DNA-targeting agents and non-hydroxamate MMPs inhibitors were synthesized and screened against HCT-116, Caco-2 cells, and normal colonocytes by MTT assay. <b>7a</b> and <b>7g</b> surpassed doxorubicin against HCT-116 cells regarding potency (IC<sub>50</sub> = 0.87 and 1.41 nM) and safety (SI = 181.93 and 54.41). <b>7g</b> was potent against liver cancer (HepG-2; IC<sub>50</sub> = 65.08 nM), the main metastatic site of CRC with correlation to MMP-13 expression. Both derivatives induced DNA damage at 2.67 and 1.87 nM, disrupted HCT-116 cell cycle and triggered apoptosis by 33.17% compared to doxorubicin (DNA damage at 0.76 nM and 40.21% apoptosis induction). <b>7g</b> surpassed NNGH against MMP-10 (IC<sub>50</sub> = 0.205 μM) and MMP-13 (IC<sub>50</sub> = 0.275 μM) and downregulated HCT-116 VEGF related to CRC progression by 38%. Docking and MDs simulated ligands-receptors binding modes and highlighted SAR. Their ADMET profiles, drug-likeness and possible off-targets were computationally predicted. Colorectal cancer ; Cancer research ; Molecular dynamics ; DNA ; Matrix metalloproteinase ; Chemistry ; Biology ; Biochemistry ; Genetics ; Cancer Synthesis and Characterization of Heterocyclic Compounds ; Click Chemistry and Applications ; Synthesis and biological activity
Authors: Sidra Rana | Sania Shahid | Mohammad S. Iqbal | Adnan Arshad | Dilawar Khan
Source: Heliyon (article, 2024-05-01)
Field: Materials Science — Biomaterials

RETRACTED: A nanoformulation of cisplatin with arabinoxylan having enhanced activity against hepatocellular carcinoma through upregulation of apoptotic and necroptotic pathways Cisplatin is a versatile drug used to treat various types of cancer, but it is associated with high toxicity and resistance problems. Several approaches, including nanotechnology, have been adopted to minimize the toxic effects and to overcome the resistance of cisplatin. Most of the nanoformulations involve the use of synthetic or semisynthetic polymers as drug carriers. In this study arabinoxylan nanoparticles have been investigated as drug reservoirs for intestinal drug delivery. The drug-loaded arabinoxylan nanoparticles (size: ∼1.8 nm, polydispersity index: 0.3 ± 0.04) were prepared and nanoformulation was characterized by various analytical techniques. The nanoformulation was found to be stable (zeta potential: 31.6 ± 1.1 mV). An <i>in vitro</i> cytotoxicity against HepG2 and HEK 293 cell lines was studied. The cell viability analysis showed greater efficacy than the standard cisplatin (IC<sub>50</sub>: cisplatin 2.4, arabinoxylan nanoformulation 1.3 μg mL<sup>-1</sup>). The expression profile of carcinogenic markers revealed a six-fold upregulation of MLKL and 0.9-fold down regulation of KRAS, suggesting the activation of the necroptotic pathway by the drug-loaded nanoparticles. The nanoformulation exhibited a sustained release of cisplatin with a cumulative release of ∼40 % (at pH 7.4) and ∼30 % (at pH 5.5) over a period of 12 h with very low initial burst. The study suggests that the use of the new nanoformulation can significantly reduce the required dose of cisplatin without compromising efficacy and more efficient release at basic pH. Downregulation and upregulation ; Hepatocellular carcinoma ; Cisplatin ; Apoptosis ; Arabinoxylan ; Cancer research ; Chemistry ; Cell biology ; Biology ; Biochemistry ; Medicine ; Internal medicine ; Gene ; Chemotherapy ; Enzyme Nanoparticle-Based Drug Delivery ; Chemotherapy-induced organ toxicity mitigation ; Curcumin's Biomedical Applications
Authors: Vahid Rahmani | Shah Nawaz | David Pennicard | H. Graafsma
Source: Journal of Applied Crystallography (article, 2024-03-26)
Field: Materials Science — Materials Chemistry

Robust image descriptor for machine learning based data reduction in serial crystallography Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as 'hit' and 'miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers. Computer science ; Artificial intelligence ; Preprocessor ; Frame rate ; Feature extraction ; Pipeline (software) ; Pattern recognition (psychology) Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Enzyme Structure and Function