jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Danping Tian | Ruipeng Hao | Xiaoming Zhang | Hu Shi | Yuwei Wang | Linfeng Liang | Haichao Liu | Hengquan Yang
Source: Nature Communications (article, 2023-06-03)
Field: Chemistry — Inorganic Chemistry

Multi-compartmental MOF microreactors derived from Pickering double emulsions for chemo-enzymatic cascade catalysis Bioinspired multi-compartment architectures are desired in synthetic biology and metabolic engineering, as credited by their cell-like structures and intrinsic ability of assembling catalytic species for spatiotemporal control over cascade reactions like in living systems. Herein, we describe a general Pickering double emulsion-directed interfacial synthesis method for the fabrication of multicompartmental MOF microreactors. This approach employs multiple liquid-liquid interfaces as a controllable platform for the self-completing growth of dense MOF layers, enabling the microreactor with tailor-made inner architectures and selective permeability. Importantly, simultaneous encapsulation of incompatible functionalities, including hydrophilic enzyme and hydrophobic molecular catalyst, can be realized in a single MOF microreactor for operating chemo-enzymatic cascade reactions. As exemplified by the Grubb' catalyst/CALB lipase driven olefin metathesis/ transesterification cascade reaction and glucose oxidase (GOx)/Fe-porphyrin catalyzed oxidation reaction, the multicompartmental microreactor exhibits 2.24-5.81 folds enhancement in cascade reaction efficiency in comparison to the homogeneous counterparts or physical mixture of individual analogues, due to the restrained mutual inactivation and substrate channelling effects. Our study prompts further design of multicompartment systems and the development of artificial cells capable of complex cellular transformations. Microreactor ; Cascade ; Pickering emulsion ; Enzyme catalysis ; Catalysis ; Chemistry ; Cascade reaction ; Enzyme ; Chemical engineering ; Nanotechnology ; Combinatorial chemistry ; Materials science ; Organic chemistry ; Nanoparticle ; Chromatography Metal-Organic Frameworks: Synthesis and Applications ; Nanocluster Synthesis and Applications ; Pickering emulsions and particle stabilization
Authors: Niamh Bayliss | Bernhard V. K. J. Schmidt
Source: Progress in Polymer Science (article, 2023-10-18)
Field: Chemistry — Organic Chemistry

Hydrophilic polymers: Current trends and visions for the future Hydrophilic polymers are a major class of polymers in polymer science. They are found in broad range of applications from superabsorbers to drug-delivery. In recent years, a plethora of impactful developments in hydrophilic polymers have been reported. The present review gives an overview over these developments with a focus on frequently studied polymer types, aqueous multi-phase systems, hydrophilic block copolymer self-assembly and hydrophilic polymer particles. We cover fundamental work and concepts but also present work with high relevance for application. Finally, we give an outlook towards current challenges and future developments of the field. The further development of hydrophilic polymer is of great importance for a broad range of applications and will have a significant impact on biomedicine and every-day life. Polymer ; Nanotechnology ; Vision ; Materials science ; Drug delivery ; Polymer science Advanced Polymer Synthesis and Characterization ; Hydrogels: synthesis, properties, applications ; Surfactants and Colloidal Systems
Authors: Dooyoung Kim | Vinh Q. Dang | Thomas S. Teets
Source: Chemical Science (article, 2023-11-23)
Field: Chemistry — Organic Chemistry

Improved transition metal photosensitizers to drive advances in photocatalysis To function effectively in a photocatalytic application, a photosensitizer's light absorption, excited-state lifetime, and redox potentials, both in the ground state and excited state, are critically important. The absorption profile is particularly relevant to applications involving solar harvesting, whereas the redox potentials and excited-state lifetimes determine the thermodynamics, kinetics, and quantum yields of photoinduced redox processes. This perspective article focuses on synthetic inorganic and organometallic approaches to optimize these three characteristics of transition-metal based photosensitizers. We include our own work in these areas, which has focused extensively on exceptionally strong cyclometalated iridium photoreductants that enable challenging reductive photoredox transformations on organic substrates, and more recent work which has led to improved solar harvesting in charge-transfer copper(i) chromophores, an emerging class of earth-abundant compounds particularly relevant to solar-energy applications. We also extensively highlight many other complementary strategies for optimizing these parameters and highlight representative examples from the recent literature. It remains a significant challenge to simultaneously optimize all three of these parameters at once, since improvements in one often come at the detriment of the others. These inherent trade-offs and approaches to obviate or circumvent them are discussed throughout. Excited state ; Redox ; Chromophore ; Photocatalysis ; Photochemistry ; Nanotechnology ; Chemistry ; Absorption (acoustics) ; Photosensitizer ; Materials science ; Combinatorial chemistry ; Biochemical engineering ; Catalysis ; Physics ; Organic chemistry ; Atomic physics Radical Photochemical Reactions ; Advanced Photocatalysis Techniques ; Catalytic C–H Functionalization Methods
Authors: Yiran Jiao | Haobo Li | Yan Jiao | Shi‐Zhang Qiao
Source: Journal of the American Chemical Society (article, 2023-07-06)
Field: Materials Science — Materials Chemistry

Activity and Selectivity Roadmap for C–N Electro-Coupling on MXenes Electrochemical coupling between carbon and nitrogen species to generate high-value C-N products, including urea, presents significant economic and environmental potentials for addressing the energy crisis. However, this electrocatalysis process still suffers from limited mechanism understanding due to the complex reaction networks, which restricts the development of electrocatalysts beyond trial-and-error practices. In this work, we aim to improve the understanding of the C-N coupling mechanism. This goal was achieved by constructing the activity and selectivity landscape on 54 MXene surfaces by density functional theory (DFT) calculations. Our results show that the activity of the C-N coupling step is largely determined by the *CO adsorption strength (<i>E</i><sub>ad-CO</sub>), while the selectivity relies more on the co-adsorption strength of *N and *CO (<i>E</i><sub>ad-CO</sub> and <i>E</i><sub>ad-N</sub>). Based on these findings, we propose that an ideal C-N coupling MXene catalyst should satisfy moderate *CO and stable *N adsorption. Through the machine learning-based approach, data-driven formulas for describing the relationship between <i>E</i><sub>ad-CO</sub> and <i>E</i><sub>ad-N</sub> with atomic physical chemistry features were further identified. Based on the identified formula, 162 MXene materials were screened without time-consuming DFT calculations. Several potential catalysts were predicted with good C-N coupling performance, such as Ta<sub>2</sub>W<sub>2</sub>C<sub>3</sub>. The candidate was then verified by DFT calculations. This study has incorporated machine learning methods for the first time to provide an efficient high-throughput screening method for selective C-N coupling electrocatalysts, which could be extended to a wider range of electrocatalytic reactions to facilitate green chemical production. Chemistry ; MXenes ; Selectivity ; Coupling (piping) ; Organic chemistry ; Catalysis MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques ; Ammonia Synthesis and Nitrogen Reduction
Authors: Patinharekandy Prabhathan | Kandammathe Valiyaveedu Sreekanth | Jinghua Teng | Joo Hwan Ko | Young Jin Yoo | Hyeon‐Ho Jeong | Yubin Lee | Shoujun Zhang | Tun Cao | Cosmin‐Constantin Popescu | Brian Mills | Tian Gu | Zhuoran Fang | Rui Chen | Hao Tong | Yi Wang | Qiang He | Yitao Lu | Zhiyuan Liu | Han Yu | Avik Mandal | Yihao Cui | Abbas Sheikh Ansari | Viraj Bhingardive | Myungkoo Kang | Choon Kong Lai | Moritz Merklein | Maximilian J. Müller | Young Min Song | Zhen Tian | Juejun Hu | María Losurdo | Arka Majumdar | Xiangshui Miao | Xiao Chen | Behrad Gholipour | Kathleen Richardson | Benjamin J. Eggleton | Matthias Wuttig | Ranjan Singh
Source: iScience (review, 2023-09-22)
Field: Materials Science — Materials Chemistry

Roadmap for phase change materials in photonics and beyond Phase Change Materials (PCMs) have demonstrated tremendous potential as a platform for achieving diverse functionalities in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum, ranging from terahertz to visible frequencies. This comprehensive roadmap reviews the material and device aspects of PCMs, and their diverse applications in active and reconfigurable micro-nanophotonic devices across the electromagnetic spectrum. It discusses various device configurations and optimization techniques, including deep learning-based metasurface design. The integration of PCMs with Photonic Integrated Circuits and advanced electric-driven PCMs are explored. PCMs hold great promise for multifunctional device development, including applications in non-volatile memory, optical data storage, photonics, energy harvesting, biomedical technology, neuromorphic computing, thermal management, and flexible electronics. Photonics ; Nanophotonics ; Neuromorphic engineering ; Electronics ; Terahertz radiation ; Electromagnetic spectrum ; Energy harvesting ; Nanotechnology ; Materials science ; Computer science ; Metamaterial ; Engineering physics ; Optoelectronics ; Electrical engineering ; Engineering ; Energy (signal processing) ; Physics ; Optics Phase-change materials and chalcogenides ; Metamaterials and Metasurfaces Applications ; Advanced Memory and Neural Computing
Authors: Cas van der Oord | Matthias Sachs | Dávid Péter Kovács | Christoph Ortner | Gábor Cśanyi
Source: npj Computational Materials (article, 2023-09-13)
Field: Materials Science — Materials Chemistry

Hyperactive learning for data-driven interatomic potentials Data-driven interatomic potentials have emerged as a powerful tool for approximating ab initio potential energy surfaces. The most time-consuming step in creating these interatomic potentials is typically the generation of a suitable training database. To aid this process hyperactive learning (HAL), an accelerated active learning scheme, is presented as a method for rapid automated training database assembly. HAL adds a biasing term to a physically motivated sampler (e.g. molecular dynamics) driving atomic structures towards uncertainty in turn generating unseen or valuable training configurations. The proposed HAL framework is used to develop atomic cluster expansion (ACE) interatomic potentials for the AlSi10 alloy and polyethylene glycol (PEG) polymer starting from roughly a dozen initial configurations. The HAL generated ACE potentials are shown to be able to determine macroscopic properties, such as melting temperature and density, with close to experimental accuracy. Interatomic potential ; Ab initio ; Molecular dynamics ; Polyethylene glycol ; Cluster (spacecraft) ; Process (computing) ; Statistical physics ; Materials science ; Computer science ; Chemical physics ; Molecular physics ; Chemistry ; Physics ; Computational chemistry ; Quantum mechanics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Crystallography and molecular interactions
Authors: Muhammad Yasir Khalid | Zia Ullah Arif | Reza Noroozi | Mokarram Hossain | Seeram Ramakrishna | Rehan Umer
Source: International Journal of Biological Macromolecules (review, 2023-08-11)
Field: Materials Science — Biomaterials

3D/4D printing of cellulose nanocrystals-based biomaterials: Additives for sustainable applications Cellulose nanocrystals (CNCs) have gained significant attraction from both industrial and academic sectors, thanks to their biodegradability, non-toxicity, and renewability with remarkable mechanical characteristics. Desirable mechanical characteristics of CNCs include high stiffness, high strength, excellent flexibility, and large surface-to-volume ratio. Additionally, the mechanical properties of CNCs can be tailored through chemical modifications for high-end applications including tissue engineering, actuating, and biomedical. Modern manufacturing methods including 3D/4D printing are highly advantageous for developing sophisticated and intricate geometries. This review highlights the major developments of additive manufactured CNCs, which promote sustainable solutions across a wide range of applications. Additionally, this contribution also presents current challenges and future research directions of CNC-based composites developed through 3D/4D printing techniques for myriad engineering sectors including tissue engineering, wound healing, wearable electronics, robotics, and anti-counterfeiting applications. Overall, this review will greatly help research scientists from chemistry, materials, biomedicine, and other disciplines to comprehend the underlying principles, mechanical properties, and applications of additively manufactured CNC-based structures. Nanotechnology ; Materials science ; 3D printing ; Flexibility (engineering) ; Mechanical strength ; Cellulose ; Tissue engineering ; Mechanical engineering ; Engineering ; Composite material ; Chemical engineering ; Biomedical engineering Advanced Cellulose Research Studies ; Additive Manufacturing and 3D Printing Technologies ; Electrospun Nanofibers in Biomedical Applications
Authors: Danial Khatamsaz | Brent Vela | Prashant Singh | D. D. Johnson | Douglas Allaire | Raymundo Arróyave
Source: npj Computational Materials (article, 2023-04-01)
Field: Materials Science — Materials Chemistry

Bayesian optimization with active learning of design constraints using an entropy-based approach Abstract The design of alloys for use in gas turbine engine blades is a complex task that involves balancing multiple objectives and constraints. Candidate alloys must be ductile at room temperature and retain their yield strength at high temperatures, as well as possess low density, high thermal conductivity, narrow solidification range, high solidus temperature, and a small linear thermal expansion coefficient. Traditional Integrated Computational Materials Engineering (ICME) methods are not sufficient for exploring combinatorially-vast alloy design spaces, optimizing for multiple objectives, nor ensuring that multiple constraints are met. In this work, we propose an approach for solving a constrained multi-objective materials design problem over a large composition space, specifically focusing on the Mo-Nb-Ti-V-W system as a representative Multi-Principal Element Alloy (MPEA) for potential use in next-generation gas turbine blades. Our approach is able to learn and adapt to unknown constraints in the design space, making decisions about the best course of action at each stage of the process. As a result, we identify 21 Pareto-optimal alloys that satisfy all constraints. Our proposed framework is significantly more efficient and faster than a brute force approach. Bayesian optimization ; Pareto principle ; Computer science ; Multi-objective optimization ; Mathematical optimization ; Principle of maximum entropy ; Engineering design process ; Process engineering ; Mechanical engineering ; Mathematics ; Engineering ; Artificial intelligence Machine Learning in Materials Science ; Titanium Alloys Microstructure and Properties ; Additive Manufacturing Materials and Processes
Authors: Zhijie Chen | Kent O. Kirlikovali | Le Shi | Omar K. Farha
Source: Materials Horizons (review, 2023-01-01)
Field: Chemistry — Inorganic Chemistry

Rational design of stable functional metal–organic frameworks Functional porous metal-organic frameworks (MOFs) have been explored for a number of potential applications in catalysis, chemical sensing, water capture, gas storage, and separation. MOFs are among the most promising candidates to address challenges facing our society related to energy and environment, but the successful implementation of functional porous MOF materials are contingent on their stability; therefore, the rational design of stable MOFs plays an important role towards the development of functional porous MOFs. In this Focus article, we summarize progress in the rational design and synthesis of stable MOFs with controllable pores and functionalities. The implementation of reticular chemistry allows for the rational top-down design of stable porous MOFs with targeted topological networks and pore structures from the pre-selected building blocks. We highlight the reticular synthesis and applications of stable MOFs: (1) MOFs based on high valent metal ions (<i>e.g.</i>, Al<sup>3+</sup>, Cr<sup>3+</sup>, Fe<sup>3+</sup>, Ti<sup>4+</sup> and Zr<sup>4+</sup>) and carboxylate ligands; (2) MOFs based on low valent metal ions (<i>e.g.</i>, Ni<sup>2+</sup>, Cu<sup>2+</sup>, and Zn<sup>2+</sup>) and azolate linkers. We envision that the synthetic strategies, including modulated synthesis and post-synthetic modification, can potentially be extended to other more complex systems like metal-phosphonate framework materials. Rational design ; Metal-organic framework ; Reticular connective tissue ; Nanotechnology ; Catalysis ; Materials science ; Combinatorial chemistry ; Chemical engineering ; Chemistry ; Organic chemistry ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Zeolite Catalysis and Synthesis
Authors: S. Li | Feng Wang | Yanrong Wang | Jia Yang | Xinyuan Wang | Xueying Zhan | Jun He | Zhenxing Wang
Source: Advanced Materials (review, 2023-06-26)
Field: Materials Science — Materials Chemistry

Van der Waals Ferroelectrics: Theories, Materials, and Device Applications In recent years, an increasing number of 2D van der Waals (vdW) materials are theory-predicted or laboratory-validated to possess in-plane (IP) and/or out-of-plane (OOP) spontaneous ferroelectric polarization. Due to their dangling-bond-free surfaces, interlayer charge coupling, robust polarization, tunable energy band structures, and compatibility with silicon-based technologies, vdW ferroelectric materials exhibit great promise in ferroelectric memories, neuromorphic computing, nanogenerators, photovoltaic devices, spintronic devices, and so on. Here, the very recent advances in the field of vdW ferroelectrics (FEs) are reviewed. First, theories of ferroelectricity are briefly discussed. Then, a comprehensive summary of the non-stacking vdW ferroelectric materials is provided based on their crystal structures and the emerging sliding ferroelectrics. In addition, their potential applications in various branches/frontier fields are enumerated, with a focus on artificial intelligence. Finally, the challenges and development prospects of vdW ferroelectrics are discussed. Ferroelectricity ; Materials science ; van der Waals force ; Nanotechnology ; Neuromorphic engineering ; Spintronics ; Dangling bond ; Polarization (electrochemistry) ; Engineering physics ; Condensed matter physics ; Silicon ; Optoelectronics ; Dielectric ; Ferromagnetism ; Computer science ; Physics ; Quantum mechanics Ferroelectric and Piezoelectric Materials ; Advanced Sensor and Energy Harvesting Materials ; 2D Materials and Applications
Authors: Arthur Viodé | Patrick van Zalm | Kinga K. Smolen | Benoit Fatou | David K. Stevenson | Meenakshi Jha | Ofer Levy | Judith A. Steen | Hanno Steen | On behalf of the IMPACC Network
Source: Science Advances (article, 2023-03-31)
Field: Chemistry — Spectroscopy

A simple, time- and cost-effective, high-throughput depletion strategy for deep plasma proteomics We introduce a cost-effective, robust high-throughput-compatible plasma depletion method enabling in-depth profiling of plasma that detects >1300 proteins per run with a throughput of 60 samples per day. The method has been fully validated by processing >3000 samples with no apparent batch effect at a cost for the depletion step of ~$2.5 per sample. Throughput ; Computer science ; Profiling (computer programming) ; Telecommunications Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Benjamin Mahieu | El Mostafa Qannari | Benoît Jaillais
Source: Chemometrics and Intelligent Laboratory Systems (article, 2023-09-12)
Field: Chemistry — Analytical Chemistry

Extension and significance testing of Variable Importance in Projection (VIP) indices in Partial Least Squares regression and Principal Components Analysis Partial least squares regression ; Mathematics ; Feature selection ; Extension (predicate logic) ; Context (archaeology) ; Variable (mathematics) ; Statistics ; Principal component analysis ; Regression analysis ; Projection (relational algebra) ; Variables ; Computer science ; Algorithm ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Sensory Analysis and Statistical Methods ; Advanced Chemical Sensor Technologies
Authors: Claudia Ctortecka | David Hartlmayr | Anjali Seth | Sasha Mendjan | Guilhem Tourniaire | Namrata D. Udeshi | Steven A. Carr | Karl Mechtler
Source: Molecular & Cellular Proteomics (article, 2023-10-14)
Field: Chemistry — Spectroscopy

An Automated Nanowell-Array Workflow for Quantitative Multiplexed Single-Cell Proteomics Sample Preparation at High Sensitivity Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lags. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation including multiplexed labeling up to 16-plex with high sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE, reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1500 protein groups per TMT10-plex with reduced or eliminated need for a carrier proteome. We evaluated the effect of wider precursor isolation windows at single-cell input levels and found that using 2 Da isolation windows increased overall sensitivity without significantly impacting interference. Using the dedicated mass spectrometry acquisition strategies detailed here, we identified on average close to 2000 proteins per TMT10-plex across 170 multiplexed single cells that readily distinguished human cell types. Overall, our workflow combines highly efficient sample preparation, chromatographic and ion mobility-based filtering, rapid wide-window data-dependent acquisition analysis, and intelligent data analysis for optimal multiplexed single-cell proteomics. This versatile and automated proteoCHIP-based sample preparation approach is sufficiently sensitive to drive biological applications of single-cell proteomics and can be readily adopted by proteomics laboratories. Proteomics ; Proteome ; Sample preparation ; Mass spectrometry ; Multiplexing ; Single-cell analysis ; Computer science ; Workflow ; Sample (material) ; Quantitative proteomics ; Microfluidics ; Chromatography ; Chemistry ; Computational biology ; Nanotechnology ; Cell ; Materials science ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Single-cell and spatial transcriptomics