jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Văn Quí Nguyễn | Thị Tuyết Minh Lê | Phát Tài Võ | Anh-Tuan Pham | Tú Uyên Châu | Mạnh Khương Nguyễn | Đắc Khoa Nguyễn | Thị Phi Oanh Nguyễn
Source: Can Tho University Journal of Science (article, 2024-03-04)
Field: Materials Science — Materials Chemistry

Tuyển chọn chất mang để tồn trữ vi khuẩn Comamonas sp. PAN1.12 có khả năng hấp thu sodium tripolyphosphate Nghiên cứu được thực hiện nhằm tuyển chọn chất mang thích hợp để tồn trữ vi khuẩn hấp thu sodium tripolyphosphate Comamonas sp. PAN1.12 phân lập từ hệ thống xử lý nước thải chế biến thủy sản. Mười một chất mang được khảo sát gồm bã mía, bã cà phê, bột talc, cám, rơm, mạt cưa được sử dụng riêng lẻ và phối trộn năm loại chất mang với bột talc theo tỉ lệ 1:1. Bột talc và hỗn hợp mạt cưa với bột talc có bổ sung 1% carboxymethyl cellulose, 1,5% CaCO3 và chủng 100×106 CFU/g có khả năng duy trì mật số (&gt;106 CFU/g) và hấp thu sodium tripolyphosphate (tương đương 67%) của vi khuẩn Comamonas sp. PAN1.12 sau một tháng tồn trữ. Nồng độ chất bổ trợ carboxymethyl cellulose và mật số vi khuẩn chủng vào ban đầu có ảnh hưởng đến mật số vi khuẩn nhưng không ảnh hưởng đến khả năng hấp thu sodium tripolyphosphate của vi khuẩn PAN1.12. Chemistry ; Medicinal chemistry ; Nuclear chemistry ; Sodium ; Organic chemistry Polyoxometalates: Synthesis and Applications
Authors: Minggao Feng | Chengxi Zhao | Graeme M. Day | Xenophon Evangelopoulos | Andrew I. Cooper
Source: ChemRxiv (preprint, 2024-12-18)
Field: Materials Science — Materials Chemistry

A Universal Foundation Model for Transfer Learning in Molecular Crystals The physical and chemical properties of molecular crystals are a combined function of molecular structure and the molecular crystal packing. Specific crystal packings can enable applications such as pharmaceuticals, organic electronics, and porous materials for gas storage. However, to design such materials, we need to predict both crystal structure and the resulting physical properties, and this is expensive using traditional computational methods. Machine-learned interatomic potential methods offer major accelerations here, but molecular crystal structure prediction remains challenging due to the weak intermolecular interactions that dictate crystal packing. Moreover, machine-learned interatomic potentials do not accelerate the prediction of all physical properties for molecular crystals. Here we present Molecular Crystal Representation from Transformers (MCRT), a transformer-based model for molecular crystal property prediction that is pre-trained on more than 700,000 experimental structures extracted from the Cambridge Structural Database (CSD). MCRT employs four different pre-training tasks to extract both local and global representations from the crystals using multimodal features to encode crystal structure and geometry. MCRT has the potential to serve as a universal foundation model for predicting a range of properties for molecular crystals, achieving state-of-the-art results even when fine-tuned on small-scale datasets. We demonstrate MCRT’s practical utility in both crystal property prediction and crystal structure prediction. We also show that model predictions can be interpreted by using attention scores. Foundation (evidence) ; Transfer of learning ; Computer science ; Materials science ; Artificial intelligence ; Political science ; Law Machine Learning in Materials Science
Authors: Minggao Feng | Chengxi Zhao | Graeme M. Day | Xenophon Evangelopoulos | Andrew I. Cooper
Source: ChemRxiv (preprint, 2024-12-22)
Field: Materials Science — Materials Chemistry

A Universal Foundation Model for Transfer Learning in Molecular Crystals The physical and chemical properties of molecular crystals are a combined function of molecular structure and the molecular crystal packing. Specific crystal packings can enable applications such as pharmaceuticals, organic electronics, and porous materials for gas storage. However, to design such materials, we need to predict both crystal structure and the resulting physical properties, and this is expensive using traditional computational methods. Machine-learned interatomic potential methods offer major accelerations here, but molecular crystal structure prediction remains challenging due to the weak intermolecular interactions that dictate crystal packing. Moreover, machine-learned interatomic potentials do not accelerate the prediction of all physical properties for molecular crystals. Here we present Molecular Crystal Representation from Transformers (MCRT), a transformer-based model for molecular crystal property prediction that is pre-trained on more than 700,000 experimental structures extracted from the Cambridge Structural Database (CSD). MCRT employs four different pre-training tasks to extract both local and global representations from the crystals using multimodal features to encode crystal structure and geometry. MCRT has the potential to serve as a universal foundation model for predicting a range of properties for molecular crystals, achieving state-of-the-art results even when fine-tuned on small-scale datasets. We demonstrate MCRT’s practical utility in both crystal property prediction and crystal structure prediction. We also show that model predictions can be interpreted by using attention scores. Foundation (evidence) ; Transfer of learning ; Computer science ; Artificial intelligence ; Political science ; Law Machine Learning in Materials Science
Authors: Ivan Tambovtsev | Yorick L. A. Schmerwitz | Levi, Gianluca | Darina D. Darmoroz | Pavel V. Nesterov | Tetiana Orlova | Hannes Jónsson
Source: arXiv (Cornell University) (preprint, 2024-05-28)
Field: Materials Science — Materials Chemistry

Fine Tuning of the Rotational Rate of Light-Driven, Second Generation Molecular Motors by Fluorine Substitutions The relaxation time of several second generation molecular motors is analysed by calculating the minimum energy path between the metastable and stable states and evaluating the transition rate within harmonic transition state theory based on energetics obtained from density functional theory. Comparison with published experimental data shows remarkably good agreement and demonstrates the predictive capability of the theoretical approach. While previous measurements by Feringa and coworkers [Chem.\,Eur.\,J.\,(2017) 23, 6643] have shown that a replacement of the stereogenic hydrogen by a fluorine atom increases the relaxation time because of destabilization of the transition state for the thermal helix inversion, we find that a replacement of CH$_3$ by a CF$_3$ group at the same site shortens the relaxation time because of elevated energy of the metastable state without a significant shift in the transition state energy. Since these two fluorine substitutions have an opposite effect on the relaxation time, the two combined can provide a way to fine tune the rotational speed of a molecular motor. Fluorine ; Molecular motor ; Work (physics) ; Materials science ; Chemistry ; Physics ; Nanotechnology ; Organic chemistry ; Quantum mechanics Diamond and Carbon-based Materials Research ; Atomic and Subatomic Physics Research ; Mechanical and Optical Resonators
Authors: Khiem Le | Zhichun Guo | Kaiwen Dong | Xiaobao Huang | Bozhao Nan | Roshni G. Iyer | Zhang, Xiangliang | Olaf Wiest | Wei J. Wang | Ting Hua | Nitesh V. Chawla
Source: Open MIND (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

MolX: Enhancing Large Language Models for Molecular Understanding With A Multi-Modal Extension Large Language Models (LLMs) with their strong task-handling capabilities have shown remarkable advancements across a spectrum of fields, moving beyond natural language understanding. However, their proficiency within the chemistry domain remains restricted, especially in solving molecule-related tasks. This challenge is attributed to their inherent limitations in comprehending molecules using only common textual representations, i.e. SMILES strings. In this study, we seek to enhance the ability of LLMs to comprehend molecules by equipping them with a multi-modal external module, termed MolX. Instead of directly using SMILES strings to represent a molecule, we utilize specific encoders to extract fine-grained features from both SMILES string and 2D molecular graph representations for feeding into an LLM. A hand-crafted molecular fingerprint is incorporated to leverage its embedded domain knowledge. To establish an alignment between MolX and the LLM's textual input space, the model in which the LLM is frozen, is pre-trained with a strategy including a diverse set of tasks. Experimental evaluations show that our proposed method outperforms baselines across downstream molecule-related tasks ranging from molecule-to-text translation to molecular property prediction, with and without fine-tuning the LLM, while only introducing a small number of trainable parameters-0.53% and 0.82%, respectively. Leverage (statistics) ; String (physics) ; Set (abstract data type) ; Domain (mathematical analysis) ; Property (philosophy) ; Encoder ; Natural language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Topic Modeling
Authors: Hongli Chen | Ding Wei | Huihui Wang | Shangwei Huangfu | Yuecheng Jiang | Xianqiang Yu | Biao Jiang
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Chemistry — Organic Chemistry

Fine-Tuning Phenoxy Silyl Scaffolds for the Development of Glutathione-Responsive Prodrugs and Antibody−Drug Conjugates Prodrug ; Conjugate ; Silylation ; Glutathione ; Chemistry ; Drug ; Drug development ; Antibody ; Combinatorial chemistry ; Pharmacology ; Biochemistry ; Medicine ; Enzyme ; Catalysis ; Immunology Chemical Synthesis and Reactions ; Click Chemistry and Applications ; Chemical Synthesis and Analysis
Authors: Hongli Chen | Ding Wei | Huihui Wang | Shangwei Huangfu | Yuecheng Jiang | Xianqiang Yu | Biao Jiang
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Chemistry — Organic Chemistry

Fine-Tuning Phenoxy Silyl Scaffolds for the Development of Glutathione-Responsive Prodrugs and Antibody−Drug Conjugates Prodrug ; Silylation ; Conjugate ; Glutathione ; Chemistry ; Drug ; Antibody ; Combinatorial chemistry ; Pharmacology ; Biochemistry ; Medicine ; Catalysis ; Immunology ; Enzyme ; Mathematics Chemical Synthesis and Reactions ; Click Chemistry and Applications ; Chemical Synthesis and Analysis
Authors: Jianai Chen | Mingjiao Sun | Yujie Dong | Weijun Li | Fen Er Chen
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Dual-Response Signal Under Mechanical Stimulation: Alkyl Substituent Effect on the Fine-Tuning of Molecular Packing Substituent ; Alkyl ; Dual (grammatical number) ; Stimulation ; SIGNAL (programming language) ; Chemistry ; Materials science ; Computer science ; Stereochemistry ; Psychology ; Organic chemistry ; Neuroscience Luminescence and Fluorescent Materials ; Molecular Sensors and Ion Detection ; Supramolecular Chemistry and Complexes
Authors: Nijad Ishak | Pavel Galář | R. Mekkat | Mathieu Grandcolas | Miroslav Šoóš
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Fine-Tuning Photoluminescence and Photocatalysis: Exploring the Effects of Carbon Quantum Dots Synthesis and Purification on G-C3n4 Photocatalysis ; Photoluminescence ; Carbon quantum dots ; Quantum dot ; Materials science ; Carbon fibers ; Nanotechnology ; Optoelectronics ; Chemical engineering ; Chemistry ; Catalysis ; Composite material ; Engineering ; Organic chemistry Carbon and Quantum Dots Applications ; Gas Sensing Nanomaterials and Sensors ; Electrochemical sensors and biosensors
Authors: Yan Mao | Jinghan Yang | Rui Ruan | Taiyou Xu | Xin Xiao | Jun Hu | Peiyi Wang
Source:  (preprint, 2024-07-16)
Field: Chemistry — Spectroscopy

A Smart Supramolecular Strategy Fine-Tunes the Molecular Aggregation Behavior to Overcome the Aggregation-Caused Quenching (ACQ) Barrier in Precise Bioimaging of Active Analytes Fluorescent molecular probes are commonly used to detect active substances. However, in variable living microenvironmental systems, most of conventional aromatic fluorescent probes often suffer from aggregation-caused quenching (ACQ) due to π-π stacking, which severely limit their selectivity and sensitivity. To tackle this challenge, a predictable supramolecular strategy, which offers significant spatial effects to prevent fluorophore’s intermolecular π-π stacking at the molecular level, was proposed to design fluorescent probes. Herein, supramolecular probe RAA@Q[8] was successfully integrated by loading an adamantane-modified Rhodamine derivative (RAA) into cucurbit[8]uril (Q[8]) via the host-guest recognition principle. Intriguingly, the original highly clustered RAA-agminated spheroids become discrete supramolecular organic framework octahedrons (RAA@Q[8]), suggesting that the molecular aggregation behavior is well-modulated. This encouraging result is important for precise detection of plant signaling molecules such as salicylic acid (SA) in various environments. Experimental investigations found that RAA@Q[8] was 2.2-fold more sensitive than RAA for detecting SA, with high selectivity and anti-interference, and a low detection limit of 3.0×10 -8 M. Importantly, in complicated living microenvironments, RAA@Q[8] achieved a precise recognition and imaging of SA on pea sprouts and HEK-293 cells. This study offers a guidance for future development of host-guest supramolecular fluorescent probes that are opposite to the intractable ACQ obstacle. Supramolecular chemistry ; Stacking ; Fluorescence ; Fluorophore ; Chemistry ; Quenching (fluorescence) ; Adamantane ; Intermolecular force ; Biophysics ; Rhodamine ; Detection limit ; Molecular recognition ; Nanotechnology ; Combinatorial chemistry ; Molecule ; Materials science ; Organic chemistry ; Chromatography ; Biology Molecular Sensors and Ion Detection ; Supramolecular Self-Assembly in Materials ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Yuping Shi | Katharina Landfester | Stephen Morris
Source: Advanced Science (article, 2024-11-01)
Field: Chemistry — Organic Chemistry

Fine‐Tuning the Microstructure and Photophysical Characteristics of Fluorescent Conjugated Copolymers Using Photoalignment and Liquid‐Crystal Ordering (Adv. Sci. 41/2024) Patterning Polymer Chain Orientation Bringing long‐range structural ordering into otherwise disordered polymer semiconductors is long‐sought for bio‐inspired organic systems and light confinement. In article number 2407117, Yuping Shi and co‐workers developed a photoalignment technique to inscribe high‐resolution bespoke chain‐orientation patterns in large‐area extended polymer crystals that exhibit unity order parameters and remarkably anisotropic excitation energy transfer and emission. [Image: see text] Fluorescence ; Conjugated system ; Microstructure ; Copolymer ; Materials science ; Chemical engineering ; Crystal (programming language) ; Photochemistry ; Nanotechnology ; Polymer ; Optics ; Composite material ; Chemistry ; Computer science ; Physics Advanced Polymer Synthesis and Characterization
Authors: Yunling Liu | Wen Li | Borong Zhang | Zhaohui Shi | Lirong Zhang | Zhiyong Chang
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Fine-Tuning Porosity of In-Mofs with Ncb Topology Based on Reticular Chemistry for One-Step Purification C2h4 from Ternary C2h6/C2h4/C2h2 Mixtures Ternary operation ; Porosity ; Reticular connective tissue ; Topology (electrical circuits) ; Materials science ; Chemical engineering ; Computer science ; Composite material ; Engineering ; Electrical engineering Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science ; Zeolite Catalysis and Synthesis
Authors: Tsun‐Kong Sham | Jiatang Chen | Y. Zou Finfrock
Source:  (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

X-Rays Shine Light on Fuel Cell Catalysts Understanding the electronic behaviour of fuel cell catalysts can be difficult using standard experimental techniques, although this knowledge is critical to their fine-tuning and optimisation. Dr Jiatang Chen at the University of Western Ontario works with colleagues to use the cutting-edge valence-to-core X-ray emission spectroscopy method to determine the precise electronic effects of altering the amounts of platinum and nickel in platinum-nickel catalysts used in fuel cells. Their research demonstrates the potential application of this technique to analysing battery materials, catalysts, and even cancer drug molecules. Fuel cells ; Catalysis ; Environmental science ; Materials science ; Chemistry ; Chemical engineering ; Engineering ; Organic chemistry Machine Learning in Materials Science
Authors: Sergi Burguera | Antonio Bauzá
Source: Molecules (article, 2024-11-27)
Field: Chemistry — Physical and Theoretical Chemistry

Unconventional C—Hlg···H–C (Hlg = Cl, Br, and I) Interactions Involving Organic Halides: A Theoretical Study In this study, unconventional C-Hlg···H-C (Hlg = Cl, Br, and I) interactions involving sp, sp<sup>2</sup>, and sp<sup>3</sup> organic halides were investigated at the RI-MP2/aug-cc-pVQZ level of theory. Energy Decomposition Analyses (EDA) and Natural Bonding Orbital (NBO) studies showed that these intermolecular contacts are mainly supported by orbital and dispersion contributions, which counteracted the unfavorable/slightly favorable electrostatics due to the halogen-hydrogen σ-hole facing. In addition, the Bader's Quantum Theory of Atoms in Molecules (QTAIM) and the Noncovalent Interaction plot (NCIplot) visual index methodologies were used to further characterize the interactions discussed herein. We expect that the results reported herein will be useful in the fields of supramolecular chemistry, crystal engineering, and rational drug design, where the fine tuning of noncovalent interactions is crucial to achieve molecular recognition or a specific solid-state architecture. Natural bond orbital ; Chemistry ; Non-covalent interactions ; Atoms in molecules ; Intermolecular force ; Computational chemistry ; Supramolecular chemistry ; Chemical physics ; Hydrogen bond ; Electrostatics ; Molecule ; Physical chemistry ; Density functional theory ; Crystallography ; Crystal structure ; Organic chemistry Crystallography and molecular interactions ; Inorganic Fluorides and Related Compounds ; Crystal structures of chemical compounds
Authors: E. A. Fursov | Anton Yu. Shabalin | Nicolay Yu. Adonin
Source: Polymer Science Series B (article, 2024-04-01)
Field: Chemistry — Organic Chemistry

The Effect of Electron Deficiency of the N-aryl Fragment on the Catalytic Properties of Titanium Phenoxy-Imine Complexes in the Ethylene Polymerization A series of novel post-metallocene titanium complexes bearing polyfluorinated phenoxy-imines with para-substituents of varying electron-withdrawing (–NO2, –F) or electron-donating (–OMe, –OEt, ‒OiPr, –OPh) properties in N-phenyl fragments were synthesized and used as ethylene polymerization catalysts. Upon activation with modified methylaluminoxane these complexes produce highly crystalline ultra-high molecular weight polyethylene. The resulting catalysts were investigated in terms of the impact of the mesomeric effect of the introduced substituent and the electron unsaturation of the N-aryl fragment on the catalytic activity and molecular weight of the polyethylene produced. A nonmonotonic character of the dependences of the activity of the catalyst and the molecular weight of the synthesized polymers on the electrophilicity of the titanium atom was found. An unexpected increase in polymerization activity was also found in the OAlk series upon the transition from OMe to larger groups. To explain these effects, possible reasons were considered clarifying the details of the studied process. The obtained results demonstrate that fine tuning of electronic features of the phenoxy-imine ligand by altering the para-substituents of N-aryl fragments is a powerful tool for control the activity of titanium catalysts as well as properties of the resulting polymers. Imine ; Aryl ; Catalysis ; Titanium ; Polymerization ; Ethylene ; Polymer chemistry ; Chemistry ; Organic chemistry ; Polymer Organometallic Complex Synthesis and Catalysis ; Carbon dioxide utilization in catalysis ; Catalytic Alkyne Reactions
Authors: Taniyuki Furuyama
Source: Journal of Synthetic Organic Chemistry Japan (article, 2024-10-01)
Field: Chemistry — Organic Chemistry

Synthetic Chemistry of Organic Dyes toward Controlled Near-Infrared Light-Mediated Reactions Near-infrared (NIR) light (specifically 700-1000 nm) has garnered significant attention in recent years. Even though 52% of solar energy is infrared light, the utilization of energy in this region remains an area for improvement because most current natural and artificial materials do not interact with it. Organic synthesis provides a wide array of organic molecules. Therefore, developing novel dyes and pigments through synthetic organic chemistry is crucial to optimize the utilization of NIR light. Phthalocyanines and related macrocycles are well-known artificial dyes in modern materials chemistry. We are focusing on novel synthetic methods for phthalocyanines, creating novel phthalocyanine-based NIR chromophores, and developing novel NIR light-mediated molecular transformations using phthalocyanine catalysis. This article presents our recent findings on the chemoselective synthesis of photofunctional materials with intense NIR light interactions. The development of these materials requires precise control of the photoexcited state. Through fine-tuning NIR dyes, we have achieved highly robust photosensitizing agents, NIR light-mediated photodynamic therapy, and NIR light-driven organic reactions. Moreover, novel reaction environments with photofunctional materials can propose new applications for NIR light utilization. These achievements create further opportunities for the flexible application of NIR light. Chemistry ; Infrared ; Photochemistry ; Nanotechnology Radical Photochemical Reactions ; Oxidative Organic Chemistry Reactions ; Sulfur-Based Synthesis Techniques
Authors: Lili Deng | Qian Su | Zengxi Li | Weiguo Cheng
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Materials Chemistry

Flexible Chain Tunning of Metalloporphyrin Ionic Framework: Spatial Microenvironment Construction for Enhancing Urea Alcoholysis Urea ; Ionic bonding ; Chemistry ; Chain (unit) ; Ionic liquid ; Computer science ; Catalysis ; Ion ; Organic chemistry ; Physics Covalent Organic Framework Applications ; Metal-Organic Frameworks: Synthesis and Applications ; Porphyrin and Phthalocyanine Chemistry
Authors: Марат А. Зиганшин | A. S. Morozova | Elena O. Kudryavtseva | S. A. Ziganshina | А. А. Бухараев
Source: SSRN Electronic Journal (preprint, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

New Piezoelectric Materials Based on Phe-Leu and Leu-Phe Dipeptides Piezoelectricity ; Materials science ; Composite material Liquid Crystal Research Advancements ; Polydiacetylene-based materials and applications ; Acoustic Wave Resonator Technologies
Authors: A. S. Morozova | Elena O. Kudryavtseva | S. A. Ziganshina | Nadezhda V. Kurbatova | Марат А. Зиганшин | А. А. Бухараев
Source: Applied Materials Today (article, 2024-12-19)
Field: Materials Science — Biomaterials

New piezoelectric materials based on Phe-Leu and Leu-Phe dipeptides Piezoelectricity ; Materials science ; Composite material Supramolecular Self-Assembly in Materials ; Polydiacetylene-based materials and applications ; Acoustic Wave Resonator Technologies
Authors: Alexander Rosu-Finsen
Source: Nature Reviews Chemistry (review, 2024-06-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Chiral and magnetic butterflies Lanthanide ; Molecule ; Nanotechnology ; Materials science ; Chemical physics ; Computational chemistry ; Chemistry ; Organic chemistry Magnetism in coordination complexes ; Lanthanide and Transition Metal Complexes ; Molecular spectroscopy and chirality