jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yu‐Chuan Lin | Riccardo Torsi | Rehan Younas | Christopher L. Hinkle | Albert F. Rigosi | Heather M. Hill | Kunyan Zhang | Shengxi Huang | Christopher E. Shuck | Chen Chen | Yu-Hsiu Lin | Daniel Maldonado‐Lopez | José L. Mendoza-Cortés | John Ferrier | Swastik Kar | Nadire Nayir | Siavash Rajabpour | Adri C. T. van Duin | Xiwen Liu | Deep Jariwala | Jie Jiang | Jian Shi | Wouter Mortelmans | Rafael Jaramillo | J. M. J. Lopes | Roman Engel‐Herbert | Anthony Trofe | Tetyana Ignatova | Seng Huat Lee | Zhiqiang Mao | Leticia Damian | Yuanxi Wang | Megan A. Steves | Kenneth L. Knappenberger | Zhengtianye Wang | Stephanie Law | George Bepete | Da Zhou | Jiangxiazi Lin | Mathias S. Scheurer | J. I. A. Li | Pengjie Wang | Guo Yu | Sanfeng Wu | Deji Akinwande | Joan M. Redwing | Mauricio Terrones | Joshua A. Robinson
Source: ACS Nano (review, 2023-05-23)
Field: Materials Science — Materials Chemistry

Recent Advances in 2D Material Theory, Synthesis, Properties, and Applications Two-dimensional (2D) material research is rapidly evolving to broaden the spectrum of emergent 2D systems. Here, we review recent advances in the theory, synthesis, characterization, device, and quantum physics of 2D materials and their heterostructures. First, we shed insight into modeling of defects and intercalants, focusing on their formation pathways and strategic functionalities. We also review machine learning for synthesis and sensing applications of 2D materials. In addition, we highlight important development in the synthesis, processing, and characterization of various 2D materials (e.g., MXnenes, magnetic compounds, epitaxial layers, low-symmetry crystals, etc.) and discuss oxidation and strain gradient engineering in 2D materials. Next, we discuss the optical and phonon properties of 2D materials controlled by material inhomogeneity and give examples of multidimensional imaging and biosensing equipped with machine learning analysis based on 2D platforms. We then provide updates on mix-dimensional heterostructures using 2D building blocks for next-generation logic/memory devices and the quantum anomalous Hall devices of high-quality magnetic topological insulators, followed by advances in small twist-angle homojunctions and their exciting quantum transport. Finally, we provide the perspectives and future work on several topics mentioned in this review. Characterization (materials science) ; Heterojunction ; Nanotechnology ; Materials science ; Topological insulator ; Quantum ; Quantum dot ; Computer science ; Engineering physics ; Physics ; Optoelectronics ; Condensed matter physics 2D Materials and Applications ; MXene and MAX Phase Materials ; Graphene research and applications
Authors: Shile Wang | Yanyu Chen | Jiancheng Guo | Qinqin Huang
Source: International Journal of Molecular Sciences (review, 2023-01-31)
Field: Materials Science — Biomaterials

Liposomes for Tumor Targeted Therapy: A Review Liposomes, the most widely studied nano-drug carriers in drug delivery, are sphere-shaped vesicles consisting of one or more phospholipid bilayers. Compared with traditional drug delivery systems, liposomes exhibit prominent properties that include targeted delivery, high biocompatibility, biodegradability, easy functionalization, low toxicity, improvements in the sustained release of the drug it carries and improved therapeutic indices. In the wake of the rapid development of nanotechnology, the studies of liposome composition have become increasingly extensive. The molecular diversity of liposome composition, which includes long-circulating PEGylated liposomes, ligand-functionalized liposomes, stimuli-responsive liposomes, and advanced cell membrane-coated biomimetic nanocarriers, endows their drug delivery with unique physiological functions. This review describes the composition, types and preparation methods of liposomes, and discusses their targeting strategies in cancer therapy. Liposome ; Nanocarriers ; Drug delivery ; Drug ; Pharmacology ; Biocompatibility ; Targeted drug delivery ; Nanotechnology ; Drug carrier ; Chemistry ; Medicine ; Materials science Nanoparticle-Based Drug Delivery ; RNA Interference and Gene Delivery ; Nanoplatforms for cancer theranostics
Authors: Zhe Li | Fangning Liu | Chuanxia Chen | Yuanyuan Jiang | Pengjuan Ni | Ningning Song | Yang Hu | Shibo Xi | Minmin Liang | Yizhong Lu
Source: Nano Letters (article, 2023-02-03)
Field: Materials Science — Materials Chemistry

Regulating the N Coordination Environment of Co Single-Atom Nanozymes for Highly Efficient Oxidase Mimics Single-atom catalysts with well-defined atomic structures and precisely regulated coordination environments have been recognized as potential substitutes for natural metalloenzymes. Inspired by the metal coordination structure of natural enzymes, we show here that the oxidase-like activity of single-atom Co catalysts greatly depends on their local N coordination around the Co catalytic sites. We synthesized a series of Co single-atom catalysts with different nitrogen coordination numbers (Co-N<sub><i>x</i></sub>(C), <i>x</i> = 2, 3, and 4) and demonstrated that the oxidase-like activity of single-atom Co catalysts could be effectively tailored by fine-tuning the N coordination. Among the studied single-atom Co catalysts, the Co-N<sub>3</sub>(C) with three-coordinate N atoms shows the optimum oxygen adsorption structure and robust reactive oxygen species (ROS) generation, thus presenting the preferable oxidase-like catalytic activity. This work facilitates the future development of rational nanozyme designs for targeting reactions at the atomic level. Chemistry ; Atom (system on chip) ; Coordination complex ; Nanotechnology ; Crystallography ; Materials science ; Metal ; Computer science ; Organic chemistry Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Nanocluster Synthesis and Applications
Authors: Richard Tran | Janice Lan | Muhammed Shuaibi | Brandon M. Wood | Siddharth Goyal | Abhishek Das | Javier Heras‐Domingo | Adeesh Kolluru | Ammar Rizvi | Nima Shoghi | Anuroop Sriram | Félix Therrien | Jehad Abed | Oleksandr Voznyy | Edward H. Sargent | Zachary W. Ulissi | C. Lawrence Zitnick
Source: ACS Catalysis (article, 2023-02-16)
Field: Materials Science — Materials Chemistry

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts The development of machine learning models for electrocatalysts requires a broad set of training data to enable their use across a wide variety of materials. One class of materials that currently lacks sufficient training data is oxides, which are critical for the development of Oxygen Evolution Reaction (OER) catalysts. To address this, we developed the Open Catalyst 2022 (OC22) dataset, consisting of 62,331 Density Functional Theory (DFT) relaxations (∼9,854,504 single point calculations) across a range of oxide materials, coverages, and adsorbates. We define generalized total energy tasks that enable property prediction beyond adsorption energies; we test baseline performance of several graph neural networks; and we provide predefined dataset splits to establish clear benchmarks for future efforts. In the most general task, GemNet-OC sees a ∼36% improvement in energy predictions when combining the chemically dissimilar Open Catalyst 2020 Data set (OC20) and OC22 datasets via fine-tuning. Similarly, we achieved a ∼19% improvement in total energy predictions on OC20 and a ∼9% improvement in force predictions in OC22 when using joint training. We demonstrate the practical utility of a top performing model by capturing literature adsorption energies and important OER scaling relationships. We expect OC22 to provide an important benchmark for models seeking to incorporate intricate long-range electrostatic and magnetic interactions in oxide surfaces. Data set and baseline models are open sourced, and a public leaderboard is available to encourage continued community developments on the total energy tasks and data. Benchmark (surveying) ; Baseline (sea) ; Computer science ; Scaling ; Range (aeronautics) ; Oxide ; Set (abstract data type) ; Machine learning ; Materials science ; Mathematics Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Advanced Photocatalysis Techniques
Authors: Mariia A. Kuzina | Dmitrii D. Kartsev | Alexander V. Stratonovich | Pavel A. Levkin
Source: Advanced Functional Materials (article, 2023-04-02)
Field: Materials Science — Polymers and Plastics

Organogels versus Hydrogels: Advantages, Challenges, and Applications Abstract Organogels are an important class of gels, and are comparable to hydrogels owing to their properties as liquid‐infused soft materials. Despite the extensive choice of liquid media and compatible networks that can provide a broader range of properties, relatively few studies are reported in this area. This review presents the applicability of organogels concerning their choice of components, unique properties, and applications. Their distinctive features compared to other gels are discussed, including multi‐stimuli responses, affinity to a broad range of substances, thermal and environmental stability, electronic and ionic conductivity, and actuation. The active role of solvents is highlighted in the versatility of organogel properties. To differentiate between organogels and other gels, these are classified as gels filled with different organic liquids, including highly polar organic solvents and binary solvent systems. Most promising applications of organogels as sophisticated multifunctional materials are discussed in light of their unique features. Materials science ; Self-healing hydrogels ; Ionic liquid ; Solvent ; Soft materials ; Nanotechnology ; Polar ; Organic solvent ; Thermal stability ; Chemical engineering ; Organic chemistry ; Polymer chemistry ; Chemistry Polymer composites and self-healing ; Hydrogels: synthesis, properties, applications ; Surfactants and Colloidal Systems
Authors: Zehao Zhao | Yuchang Qing | Luo Kong | Hailong Xu | Xiaomeng Fan | Jijun Yun | Limin Zhang | Hongjing Wu
Source: Advanced Materials (review, 2023-10-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advancements in Microwave Absorption Motivated by Interdisciplinary Research Microwave absorption materials (MAMs) are originally developed for military purposes, but have since evolved into versatile materials with promising applications in modern technologies, including household use. Despite significant progress in bench-side research over the past decade, MAMs remain limited in their scope and have yet to be widely adopted. This review explores the history of MAMs from first-generation coatings to second-generation functional absorbers, identifies bottlenecks hindering their maturation. It also presents potential solutions such as exploring broader spatial scales, advanced characterization, introducing liquid media, utilizing novel toolbox (machine learning, ML), and proximity of lab to end-user. Additionally, it meticulously presents compelling applications of MAMs in medicine, mechanics, energy, optics, and sensing, which go beyond absorption efficiency, along with their current development status and prospects. This interdisciplinary research direction differs from previous research which primarily focused on meeting traditional requirements (i.e., thin, lightweight, wide, and strong), and can be defined as the next generation of smart absorbers. Ultimately, the effective utilization of ubiquitous electromagnetic (EM) waves, aided by third-generation MAMs, should be better aligned with future expectations. Toolbox ; Scope (computer science) ; Computer science ; Nanotechnology ; Absorption (acoustics) ; Materials science ; Systems engineering ; Biochemical engineering ; Process engineering ; Engineering Electromagnetic wave absorption materials ; Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies
Authors: Fengchao Yu | Guo Ci Teo | Andy T. Kong | Klemens Fröhlich | Ginny Xiaohe Li | Vadim Demichev | Alexey I. Nesvizhskii
Source: Nature Communications (article, 2023-07-12)
Field: Chemistry — Spectroscopy

Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry (MS) has been increasingly used in quantitative proteomics studies. Here, we present a fast and sensitive approach for direct peptide identification from DIA data, MSFragger-DIA, which leverages the unmatched speed of the fragment ion indexing-based search engine MSFragger. Different from most existing methods, MSFragger-DIA conducts a database search of the DIA tandem mass (MS/MS) spectra prior to spectral feature detection and peak tracing across the LC dimension. To streamline the analysis of DIA data and enable easy reproducibility, we integrate MSFragger-DIA into the FragPipe computational platform for seamless support of peptide identification and spectral library building from DIA, data-dependent acquisition (DDA), or both data types combined. We compare MSFragger-DIA with other DIA tools, such as DIA-Umpire based workflow in FragPipe, Spectronaut, DIA-NN library-free, and MaxDIA. We demonstrate the fast, sensitive, and accurate performance of MSFragger-DIA across a variety of sample types and data acquisition schemes, including single-cell proteomics, phosphoproteomics, and large-scale tumor proteome profiling studies. Computer science ; Proteomics ; Workflow ; Proteome ; Data acquisition ; Tandem mass spectrometry ; Profiling (computer programming) ; Mass spectrometry ; Phosphoproteomics ; Identification (biology) ; Data mining ; Bioinformatics ; Chemistry ; Database ; Chromatography ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Yungyeong Lee | Cyrille Boyer | Min Sang Kwon
Source: Chemical Society Reviews (review, 2023-01-01)
Field: Chemistry — Organic Chemistry

Photocontrolled RAFT polymerization: past, present, and future In this review, we provide a brief history, progress, and applications, and discuss the remaining challenges of photocontrolled reversible addition-fragmentation chain transfer (RAFT) polymerization (<i>i.e.</i>, photoinduced electron/energy transfer-RAFT (PET-RAFT), photoiniferter, and photomediated cationic RAFT polymerization). Among these, visible-light-driven RAFT polymerization has attracted particular attention in recent years due to its benefits, including low energy consumption and the safe reaction procedure. Moreover, the incorporation of visible-light photocatalysis in the polymerization has conferred attractive features, such as spatiotemporal control and oxygen tolerance; however, a clear understanding of the reaction mechanism has not been completely provided. We also present recent research efforts to elucidate the polymerization mechanisms with the aid of quantum chemical calculations combined with experimental evidence. This review offers an insight into the better design of polymerization systems for desired applications and helps realize the full potential of photocontrolled RAFT polymerization in both academic- and industrial-scale applications. Raft ; Reversible addition−fragmentation chain-transfer polymerization ; Polymerization ; Chemistry ; Chain transfer ; Radical polymerization ; Organic chemistry ; Polymer Advanced Polymer Synthesis and Characterization ; Photopolymerization techniques and applications ; Luminescence and Fluorescent Materials
Authors: Yue Liu | Zhengwei Yang | Zhenyao Yu | Zitu Liu | Dahui Liu | Hailong Lin | Ming‐Qing Li | Shuchang Ma | Maxim Avdeev | Siqi Shi
Source: Journal of Materiomics (article, 2023-05-25)
Field: Materials Science — Materials Chemistry

Generative artificial intelligence and its applications in materials science: Current situation and future perspectives Generative Artificial Intelligence (GAI) is attracting the increasing attention of materials community for its excellent capability of generating required contents. With the introduction of Prompt paradigm and reinforcement learning from human feedback (RLHF), GAI shifts from the task-specific to general pattern gradually, enabling to tackle multiple complicated tasks involved in resolving the structure-activity relationships. Here, we review the development status of GAI comprehensively and analyze pros and cons of various generative models in the view of methodology. The applications of task-specific generative models involving materials inverse design and data augmentation are also dissected. Taking ChatGPT as an example, we explore the potential applications of general GAI in generating multiple materials content, solving differential equation as well as querying materials FAQs. Furthermore, we summarize six challenges encountered for the use of GAI in materials science and provide the corresponding solutions. This work paves the way for providing effective and explainable materials data generation and analysis approaches to accelerate the materials research and development. Generative grammar ; Computer science ; Task (project management) ; Generative model ; Artificial intelligence ; Data science ; Management science ; Systems engineering ; Engineering Machine Learning in Materials Science ; Ferroelectric and Negative Capacitance Devices ; Advanced Memory and Neural Computing
Authors: Yiqian Du | Zhikai Yan | Wenbin You | Qiaoqiao Men | Guanyu Chen | Xiaowei Lv | Yuyang Wu | Kaicheng Luo | Biao Zhao | Jincang Zhang | Renchao Che
Source: Advanced Functional Materials (article, 2023-05-22)
Field: Materials Science — Materials Chemistry

Balancing MXene Surface Termination and Interlayer Spacing Enables Superior Microwave Absorption Abstract Surface chemistry and interlayer engineering determines the electrical properties of 2D MXene. However, it remains challenging to regulate the surface and interfacial chemistry of MXene simultaneously. Herein, simultaneous modulation of Ti 3 C 2 T x MXene surface termination and layer spacing by alkali treatment are achieved. The electrical and electromagnetic properties of Ti 3 C 2 T x are investigated in detail with respect to KOH and ammonia concentration dependence. A high concentration of KOH caused the Ti 3 C 2 T x layer spacing to expand to 13.7 Å and the surface O/F ratio to increase to 33.84. Because of its weaker ionization effect, ammonia provides finer tuning compared to the drastic intercalation of KOH with a thorough sweeping of the F‐containing groups. Ti 3 C 2 T x is enriched with conductive ‐OH termination after ammonia treatment, which achieves an effective balance with the increased interlayer resistance. Therefore, NH 3 H 2 O‐Ti 3 C 2 T x achieves broad‐band impedance matching and exhibits an efficient microwave loss of −49.1 dB at a low thickness of 1.7 mm, with an effective frequency bandwidth of 3.9 GHz. The results herein optimize the electrical properties of Ti 3 C 2 T x using surface and interfacial chemistry to achieve broad microwave absorption, providing a framework for enhancing the electromagnetic wave loss of intrinsic MXene. Materials science ; Microwave ; Intercalation (chemistry) ; Ammonia ; Absorption (acoustics) ; Electrical conductor ; Electrical resistivity and conductivity ; Analytical Chemistry (journal) ; Optoelectronics ; Chemical engineering ; Inorganic chemistry ; Composite material ; Organic chemistry ; Chemistry MXene and MAX Phase Materials ; Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies
Authors: Shweta Dua | Pawan Kumar | Balaram Pani | Amarjeet Kaur | Manoj Kumar Khanna | Geeta Bhatt
Source: RSC Advances (review, 2023-01-01)
Field: Materials Science — Materials Chemistry

Stability of carbon quantum dots: a critical review Carbon quantum dots (CQDs) are fluorescent carbon nanomaterials with unique optical and structural properties that have drawn extensive attention from researchers in the past few decades. Environmental friendliness, biocompatibility and cost effectiveness of CQDs have made them very renowned in countless applications including solar cells, white light-emitting diodes, bio-imaging, chemical sensing, drug delivery, environmental monitoring, electrocatalysis, photocatalysis and other related areas. This review is explicitly dedicated to the stability of CQDs under different ambient conditions. Stability of CQDs is very important for every possible application and no review has been put forth to date that emphasises it, to the best of our knowledge. This review's primary goal is to make the readers cognizant of the importance of stability, ways to assess it, factors that affect it and proposed ways to enhance the stability for making CQDs suitable for commercial applications. Carbon quantum dots ; Quantum dot ; Stability (learning theory) ; Carbon fibers ; Quantum ; Nanotechnology ; Materials science ; Chemistry ; Physics ; Computer science ; Quantum mechanics ; Composite material ; Composite number Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications ; Quantum Dots Synthesis And Properties
Authors: Hanaa M. Abuzeid | C. Julien | Likun Zhu | Ahmed M. Hashem
Source: Crystals (article, 2023-11-08)
Field: Materials Science — Materials Chemistry

Green Synthesis of Nanoparticles and Their Energy Storage, Environmental, and Biomedical Applications Green synthesis offers a superior alternative to traditional methods for producing metal and metal oxide nanoparticles. This approach is not only benign and safe but also cost-effective, scalable, and straightforward, operating under ambient conditions. Notable metals and metal oxide nanoparticles, such as manganese oxides, iron oxides, silver, and gold, have been produced using various bio-reductants derived from plant extracts. These biological agents not only expedite the reduction process but also stabilize the nanoparticles, serving dual roles as reducing and capping agents. This review presents the green synthesis of nanoparticles (NPs) obtained from biogenic wastes and plant extracts. The green-synthesized nanostructured MnO2 nanoparticles are evaluated as a potential photocatalyst for water treatment and as an electrode material in lithium-ion batteries and supercapacitors. The green-derived iron oxide nanoparticles are examined as promising antioxidant, anti-inflammatory, and anti-diabetic agents. Additionally, this review discusses the green synthesis of precious metal nanoparticles, specifically silver (Ag NPs) and gold (Au NPs), highlighting their potential medical applications in areas like antiviral treatments and cancer therapy. Nanoparticle ; Nanotechnology ; Materials science ; Oxide ; Reducing agent ; Colloidal gold ; Chemistry ; Metallurgy ; Organic chemistry Nanoparticles: synthesis and applications ; Nanomaterials for catalytic reactions ; Graphene and Nanomaterials Applications
Authors: Paulina Wiśniewska | Józef T. Haponiuk | Mohammad Reza Saeb | Navid Rabiee | Sidi A. Bencherif
Source: Chemical Engineering Journal (article, 2023-06-25)
Field: Chemistry — Inorganic Chemistry

Mitigating metal-organic framework (MOF) toxicity for biomedical applications Metal-organic framework ; Nanotechnology ; Drug delivery ; Materials science ; Porosity ; Chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Dendrimers and Hyperbranched Polymers ; Nanoplatforms for cancer theranostics