jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hannah Dewey | Ashley Lamb | Januka Budhathoki-Uprety
Source: Nanoscale (review, 2024-01-01)
Field: Materials Science — Materials Chemistry

Recent advances on applications of single-walled carbon nanotubes as cutting-edge optical nanosensors for biosensing technologies Single-walled carbon nanotubes (SWCNTs) possess outstanding photophysical properties which has garnered interest towards utilizing these materials for biosensing and imaging applications. The near-infrared (NIR) fluorescence within the tissue transparent region along with their photostability and sizes in the nanoscale make SWCNTs valued candidates for the development of optical sensors. In this review, we discuss recent advances in the development and the applications of SWCNT-based nano-biosensors. An overview of SWCNT's structural and photophysical properties, sensor development, and sensing mechanisms are described. Examples of SWCNT-based optical nanosensors for detection of disease biomarkers, pathogens (bacteria and viruses), plant stressors, and environmental contaminants including heavy metals and disinfectants are provided. Molecular detection in biofluids, <i>in vitro</i>, and <i>in vivo</i> (small animal models and plants) are highlighted, and sensor integration into portable substrates for implantable and wearable sensing devices has been discussed. Recent advancements, which include high throughput assays and the use of machine learning models to predict more sensitive and robust sensing outcomes are discussed. Current limitations and future perspectives on translation of SWCNT optical probes into clinical practices have been provided. Nanosensor ; Carbon nanotube ; Biosensor ; Nanotechnology ; Materials science ; Enhanced Data Rates for GSM Evolution ; Computer science ; Telecommunications Carbon Nanotubes in Composites ; Mechanical and Optical Resonators ; Molecular Communication and Nanonetworks
Authors: Yubo Gao | Zhicheng Zhu | Zhen Chen | Meng Guo | Yiqing Zhang | Lina Wang | Zhiling Zhu
Source: Biomaterials Science (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Machine learning in nanozymes: from design to application Nanozymes, a distinctive class of nanomaterials endowed with enzyme-like activity and kinetics akin to enzyme-catalysed reactions, present several advantages over natural enzymes, including cost-effectiveness, heightened stability, and adjustable activity. However, the conventional trial-and-error methodology for developing novel nanozymes encounters growing challenges as research progresses. The advent of artificial intelligence (AI), particularly machine learning (ML), has ushered in innovative design approaches for researchers in this domain. This review delves into the burgeoning role of ML in nanozyme research, elucidating the advancements achieved through ML applications. The review explores successful instances of ML in nanozyme design and implementation, providing a comprehensive overview of the evolving landscape. A roadmap for ML-assisted nanozyme research is outlined, offering a universal guideline for research in this field. In the end, the review concludes with an analysis of challenges encountered and anticipates future directions for ML in nanozyme research. The synthesis of knowledge in this review aims to foster a cross-disciplinary study, propelling the revolutionary field forward. Chemistry ; Kinetics ; Biochemical engineering ; Enzyme ; Nanotechnology ; Computer science ; Biochemistry ; Materials science ; Engineering ; Physics Advanced Nanomaterials in Catalysis ; Advanced biosensing and bioanalysis techniques ; Electrochemical sensors and biosensors
Authors: Sandor Balog | Mauro Sousa de Almeida | Patricia Taladriz‐Blanco | Barbara Rothen‐Rutishauser | Alke Petri‐Fink
Source: Current Opinion in Biotechnology (article, 2024-04-05)
Field: Chemistry — Physical and Theoretical Chemistry

Does the surface charge of the nanoparticles drive nanoparticle–cell membrane interactions? Nanoparticle ; Nanotechnology ; Internalization ; Surface charge ; Characterization (materials science) ; Cell membrane ; Membrane ; Chemistry ; Materials science ; Biophysics ; Cell ; Biology Electrostatics and Colloid Interactions ; Nanoparticles: synthesis and applications ; Electrochemical Analysis and Applications
Authors: Ruiyang Li | Kamal Hussain | Michael E. Liao | Kenny Huynh | Md Shafkat Bin Hoque | Spencer Wyant | Yee Rui Koh | Zhihao Xu | Yekan Wang | Dorian Luccioni | Zhe Cheng | Jingjing Shi | Eungkyu Lee | Samuel Graham | Asegun Henry | Patrick E. Hopkins | Mark S. Goorsky | Muhammad Asif Khan | Tengfei Luo
Source: ACS Applied Materials & Interfaces (article, 2024-02-05)
Field: Materials Science — Materials Chemistry

Enhanced Thermal Boundary Conductance across GaN/SiC Interfaces with AlN Transition Layers Heat dissipation plays a crucial role in the performance and reliability of high-power GaN-based electronics. While AlN transition layers are commonly employed in the heteroepitaxial growth of GaN-on-SiC substrates, concerns have been raised about their impact on thermal transport across GaN/SiC interfaces. In this study, we present experimental measurements of the thermal boundary conductance (TBC) across GaN/SiC interfaces with varying thicknesses of the AlN transition layer (ranging from 0 to 73 nm) at different temperatures. Our findings reveal that the addition of an AlN transition layer leads to a notable increase in the TBC of the GaN/SiC interface, particularly at elevated temperatures. Structural characterization techniques are employed to understand the influence of the AlN transition layer on the crystalline quality of the GaN layer and its potential effects on interfacial thermal transport. To gain further insights into the trend of TBC, we conduct molecular dynamics simulations using high-fidelity deep learning-based interatomic potentials, which reproduce the experimentally observed enhancement in TBC even for atomically perfect interfaces. These results suggest that the enhanced TBC facilitated by the AlN intermediate layer could result from a combination of improved crystalline quality at the interface and the "phonon bridge" effect provided by AlN that enhances the overlap between the vibrational spectra of GaN and SiC. Materials science ; Thermal conductivity ; Layer (electronics) ; Phonon ; Optoelectronics ; Wide-bandgap semiconductor ; Molecular dynamics ; Condensed matter physics ; Nanotechnology ; Composite material Thermal properties of materials ; Silicon Carbide Semiconductor Technologies ; Thermal Radiation and Cooling Technologies
Authors: Shanshan Zhu | Zhenwei Zhang | Zhongping Li | Huijuan Yue | Xiaoming Liu
Source: Chem Catalysis (article, 2024-04-09)
Field: Materials Science — Materials Chemistry

Progress and perspective on covalent organic frameworks for photo-catalytic hydrogen peroxide production Hydrogen peroxide ; Catalysis ; Perspective (graphical) ; Covalent bond ; Production (economics) ; Chemistry ; Organic synthesis ; Photochemistry ; Combinatorial chemistry ; Nanotechnology ; Organic chemistry ; Materials science ; Computer science Covalent Organic Framework Applications ; Advanced Photocatalysis Techniques ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Zihan Feng | Yuexin Guo | Yicong Zhang | Aiqin Zhang | Jia Meng | Junfa Yin | Gangyi Shen
Source: Journal of Nanobiotechnology (review, 2024-11-13)
Field: Materials Science — Materials Chemistry

Nanozymes: a bibliometrics review As novel multifunctional materials that merge enzyme-like capabilities with the distinctive traits of nanomaterials, nanozymes have made significant strides in interdisciplinary research areas spanning materials science, bioscience, and beyond. This article, for the first time, employed bibliometric methods to conduct an in-depth statistical analysis of the global nanozymes research and demonstrate research progress, hotspots and trends. Drawing on data from the Web of Science Core Collection database, we comprehensively retrieved the publications from 2004 to 2024. The burgeoning interest in nanozymes research across various nations indicated a growing and widespread trend. This article further systematically elaborated the enzyme-like activities, matrix, multifunctional properties, catalytic mechanisms and various applications of nanozymes, and the field encounters challenges. Despite notable progress, and requires deeper exploration guide the future research directions. This field harbors broad potential for future developments, promising to impact various aspects of technology and society. Bibliometrics ; Computational biology ; Computer science ; Biology ; Library science Advanced Nanomaterials in Catalysis ; Electrochemical sensors and biosensors ; Nanocluster Synthesis and Applications
Authors: Yaohui Xu | Yuting Li | Liangjuan Gao | Yitao Liu | Zhao Ding
Source: Nanomaterials (article, 2024-06-16)
Field: Materials Science — Materials Chemistry

Advances and Prospects of Nanomaterials for Solid-State Hydrogen Storage Hydrogen energy, known for its high energy density, environmental friendliness, and renewability, stands out as a promising alternative to fossil fuels. However, its broader application is limited by the challenge of efficient and safe storage. In this context, solid-state hydrogen storage using nanomaterials has emerged as a viable solution to the drawbacks of traditional storage methods. This comprehensive review delves into the recent advancements in nanomaterials for solid-state hydrogen storage, elucidating the fundamental principles and mechanisms, highlighting significant material systems, and exploring the strategies of surface and interface engineering alongside catalytic enhancement. We also address the primary challenges and provide future perspectives on the development of nanomaterial-based hydrogen storage technologies. Key discussions include the role of nanomaterial size effects, surface modifications, nanocomposites, and nanocatalysts in optimizing storage performance. Hydrogen storage ; Nanomaterials ; Nanotechnology ; Context (archaeology) ; Nanomaterial-based catalyst ; Energy storage ; Materials science ; Hydrogen ; Nanoparticle ; Chemistry ; Physics Hydrogen Storage and Materials ; Hybrid Renewable Energy Systems ; Ammonia Synthesis and Nitrogen Reduction
Authors: Ray Miyazaki | Kendra S. Belthle | Harun Tüysüz | Lucas Foppa | Matthias Scheffler
Source: Journal of the American Chemical Society (article, 2024-02-20)
Field: Materials Science — Materials Chemistry

Materials Genes of CO<sub>2</sub> Hydrogenation on Supported Cobalt Catalysts: An Artificial Intelligence Approach Integrating Theoretical and Experimental Data Designing materials for catalysis is challenging because the performance is governed by an intricate interplay of various multiscale phenomena, such as the chemical reactions on surfaces and the materials' restructuring during the catalytic process. In the case of supported catalysts, the role of the support material can be also crucial. Here, we address this intricacy challenge by a symbolic-regression artificial intelligence (AI) approach. We identify the key physicochemical parameters correlated with the measured performance, out of many offered candidate parameters characterizing the materials, reaction environment, and possibly relevant underlying phenomena. Importantly, these parameters are obtained by both experiments and ab initio simulations. The identified key parameters might be called "materials genes", in analogy to genes in biology: they correlate with the property or function of interest, but the explicit physical relationship is not (necessarily) known. To demonstrate the approach, we investigate the CO<sub>2</sub> hydrogenation catalyzed by cobalt nanoparticles supported on silica. Crucially, the silica support is modified with the additive metals magnesium, calcium, titanium, aluminum, or zirconium, which results in six materials with significantly different performances. These systems mimic hydrothermal vents, which might have produced the first organic molecules on Earth. The key parameters correlated with the CH<sub>3</sub>OH selectivity reflect the reducibility of cobalt species, the adsorption strength of reaction intermediates, and the chemical nature of the additive metal. By using an AI model trained on basic elemental properties of the additive metals (e.g., ionization potential) as physicochemical parameters, new additives are suggested. The predicted CH<sub>3</sub>OH selectivity of cobalt catalysts supported on silica modified with vanadium and zinc is confirmed by new experiments. Chemistry ; Cobalt ; Catalysis ; Organic chemistry Machine Learning in Materials Science ; Catalysts for Methane Reforming ; Catalytic Processes in Materials Science
Authors: Md. Shahinoor Alam | Mohammad Asaduzzaman Chowdhury | Md. Arefin Kowser | Md. Saiful Islam | Md. Moynul Islam | Tasmina Khandaker
Source: Engineering Reports (article, 2024-06-09)
Field: Materials Science — Materials Chemistry

Advances of MAX phases: Synthesis, characterizations and challenges Abstract MAX phases and their MXene compounds have received significant attention owing to their extensive potential applications. The quality and purity of the MAX phase guarantee the desired quality of the MXene product, which is essential for a variety of applications, including energy storage, catalysis, and electrical devices. Due to the purity, quality, complex structure, and unavailable commercial pure MAX powders, it is frequently required to have sophisticated synthesis and characterization techniques for the expected MAX products. Many researchers entering this field seek a comprehensive approach to the synthesis and characterization of MAX phases. Despite this, a significant portion of existing reviews have overlooked the synthesis and characterization methods specific to MAX phases, particularly when addressing MXenes. Consequently, this review aims to offer a thorough overview of the various synthesis methods and characterization techniques that are often required for MAX phases. In this review, various synthesis techniques, including their advantages and disadvantages, have also been discussed. Characterization techniques, especially x‐ray diffraction (XRD), were found to be quite critical for new researchers. However, the integration of other techniques such as scanning electron microscopy, transmission electron microscopy, x‐ray photoelectron spectroscopy, and infrared analysis enhances and complements the findings obtained through XRD. The review also underscores the challenges associated with MAX phase synthesis and proposes potential solutions, emphasizing the assessment of their suitability across a broad spectrum of applications. Overall, this review serves as a comprehensive resource and guide for researchers engaged in the exploration and application of MAX phases, emphasizing the essential techniques of synthesis and characterization in harnessing their massive potential. Materials science MXene and MAX Phase Materials ; 2D Materials and Applications ; Graphene and Nanomaterials Applications
Authors: Mohammadtaghi Vakili | Petr Koutnı́k | Jan Kohout | Zahra Gholami
Source: Surfaces (review, 2024-08-16)
Field: Materials Science — Metals and Alloys

Analysis, Assessment, and Mitigation of Stress Corrosion Cracking in Austenitic Stainless Steels in the Oil and Gas Sector: A Review This comprehensive review examines the phenomena of stress corrosion cracking (SCC) and chloride-induced stress corrosion cracking (Cl-SCC) in materials commonly used in the oil and gas industry, with a focus on austenitic stainless steels. The study reveals that SCC initiation can occur at temperatures as low as 20 °C, while Cl-SCC propagation rates significantly increase above 60 °C, reaching up to 0.1 mm/day in environments with high chloride concentrations. Experimental methods such as Slow Strain Rate Tests (SSRTs), Small Punch Tests (SPTs), and Constant-Load Tests (CLTs) were employed to quantify the impacts of temperature, chloride concentration, and pH on SCC susceptibility. The results highlight the critical role of these factors in determining the susceptibility of materials to SCC. The review emphasizes the importance of implementing various mitigation strategies to prevent SCC, including the use of corrosion-resistant alloys, protective coatings, cathodic protection, and corrosion inhibitors. Additionally, regular monitoring using advanced sensor technologies capable of detecting early signs of SCC is crucial for preventing the onset of SCC. The study concludes with practical recommendations for enhancing infrastructure resilience through meticulous material selection, comprehensive environmental monitoring, and proactive maintenance strategies, aimed at safeguarding operational integrity and ensuring environmental compliance. The review underscores the significance of considering the interplay between mechanical stresses and corrosive environments in the selection and application of materials in the oil and gas industry. Low pH levels and high temperatures facilitate the rapid progression of SCC, with experimental results indicating that stainless steel forms passive films with more defects under these conditions, reducing corrosion resistance. This interplay highlights the need for a comprehensive understanding of the complex interactions between materials, environments, and mechanical stresses to ensure the long-term integrity of critical infrastructure. Stress corrosion cracking ; Metallurgy ; Materials science ; Austenite ; Cracking ; Corrosion ; Fossil fuel ; Stress (linguistics) ; Forensic engineering ; Engineering ; Composite material ; Waste management ; Microstructure Hydrogen embrittlement and corrosion behaviors in metals ; Fatigue and fracture mechanics ; Material Properties and Failure Mechanisms
Authors: Xiaoting Shan | Ying Cai | Binyu Zhu | Lingli Zhou | Xujie Sun | Xiaoxuan Xu | Qi Yin | Dangge Wang | Yaping Li
Source: Nature Communications (review, 2024-11-18)
Field: Materials Science — Materials Chemistry

Rational strategies for improving the efficiency of design and discovery of nanomedicines The rise of rational strategies in nanomedicine development, such as high-throughput methods and computer-aided techniques, has led to a shift in the design and discovery patterns of nanomedicines from a trial-and-error mode to a rational mode. This transition facilitates the enhancement of efficiency in the preclinical discovery pipeline of nanomaterials, particularly in improving the hit rate of nanomaterials and the optimization efficiency of promising candidates. Herein, we describe a directed evolution mode of nanomedicines driven by data to accelerate the discovery of nanomaterials with high delivery efficiency. Computer-aided design strategies are introduced in detail as one of the cutting-edge directions for the development of nanomedicines. Ultimately, we look forward to expanding the tools for the rational design and discovery of nanomaterials using multidisciplinary approaches. Rational design strategies may potentially boost the delivery efficiency of next-generation nanomedicines. Rational design ; Nanomedicine ; Computer science ; Pipeline (software) ; Nanotechnology ; Drug discovery ; Risk analysis (engineering) ; Bioinformatics ; Medicine ; Materials science Machine Learning in Materials Science ; Advanced biosensing and bioanalysis techniques ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Henrique Teixeira | Catarina Dias | Andreia Silva | J. Ventura
Source: ACS Nano (review, 2024-08-07)
Field: Materials Science — Materials Chemistry

Advances on MXene-Based Memristors for Neuromorphic Computing: A Review on Synthesis, Mechanisms, and Future Directions [Image: see text] Neuromorphic computing seeks to replicate the capabilities of parallel processing, progressive learning, and inference while retaining low power consumption by drawing inspiration from the human brain. By further overcoming the constraints imposed by the traditional von Neumann architecture, this innovative approach has the potential to revolutionize modern computing systems. Memristors have emerged as a solution to implement neuromorphic computing in hardware, with research based on developing functional materials for resistive switching performance enhancement. Recently, two-dimensional MXenes, a family of transition metal carbides, nitrides, and carbonitrides, have begun to be integrated into these devices to achieve synaptic emulation. MXene-based memristors have already demonstrated diverse neuromorphic characteristics while enhancing the stability and reducing power consumption. The possibility of changing the physicochemical properties through modifications of the surface terminations, bandgap, interlayer spacing, and oxidation for each existing MXene makes them very promising. Here, recent advancements in MXene synthesis, device fabrication, and characterization of MXene-based neuromorphic artificial synapses are discussed. Then, we focus on understanding the resistive switching mechanisms and how they connect with theoretical and experimental data, along with the innovations made during the fabrication process. Additionally, we provide an in-depth review of the neuromorphic performance, making a connection with the resistive switching mechanism, along with a compendium of each relevant performance factor for nonvolatile and volatile applications. Finally, we state the remaining challenges in MXene-based devices for artificial synapses and the next steps that could be taken for future development. Neuromorphic engineering ; Memristor ; Nanotechnology ; Computer architecture ; Materials science ; Computer science ; Engineering ; Artificial intelligence ; Electronic engineering ; Artificial neural network MXene and MAX Phase Materials ; Advanced Memory and Neural Computing ; Ferroelectric and Negative Capacitance Devices
Authors: Emma King‐Smith | Simon Berritt | Louise Bernier | Xinjun Hou | Jacquelyn Klug‐McLeod | Jason Mustakis | Neal W. Sach | Joseph W. Tucker | Qingyi Yang | Roger M. Howard | Alpha A. Lee
Source: Nature Chemistry (article, 2024-01-02)
Field: Materials Science — Materials Chemistry

Probing the chemical ‘reactome’ with high-throughput experimentation data High-throughput experimentation (HTE) has the potential to improve our understanding of organic chemistry by systematically interrogating reactivity across diverse chemical spaces. Notable bottlenecks include few publicly available large-scale datasets and the need for facile interpretation of these data's hidden chemical insights. Here we report the development of a high-throughput experimentation analyser, a robust and statistically rigorous framework, which is applicable to any HTE dataset regardless of size, scope or target reaction outcome, which yields interpretable correlations between starting material(s), reagents and outcomes. We improve the HTE data landscape with the disclosure of 39,000+ previously proprietary HTE reactions that cover a breadth of chemistry, including cross-coupling reactions and chiral salt resolutions. The high-throughput experimentation analyser was validated on cross-coupling and hydrogenation datasets, showcasing the elucidation of statistically significant hidden relationships between reaction components and outcomes, as well as highlighting areas of dataset bias and the specific reaction spaces that necessitate further investigation. Chemistry ; Throughput ; Nanotechnology ; Computer science ; Telecommunications Machine Learning in Materials Science ; Innovative Microfluidic and Catalytic Techniques Innovation ; Metabolomics and Mass Spectrometry Studies