A5091838472- Innovative Microfluidic and Catalytic Techniques Innovation
- Machine Learning in Materials Science
- Asymmetric Hydrogenation and Catalysis
- Catalytic C–H Functionalization Methods
- Advanced Photocatalysis Techniques
- Scientific Computing and Data Management
- Catalytic Alkyne Reactions
- Metal-Organic Frameworks: Synthesis and Applications
- Advanced Chemical Sensor Technologies
- Oxidative Organic Chemistry Reactions
- Electrochemical Analysis and Applications
- Catalytic Cross-Coupling Reactions
- Structural Behavior of Reinforced Concrete
- Carbon dioxide utilization in catalysis
- Catalytic Processes in Materials Science
- Radical Photochemical Reactions
- Organoboron and organosilicon chemistry
- Polyoxometalates: Synthesis and Applications
- Liquid Crystal Research Advancements
- Sulfur-Based Synthesis Techniques
- Organometallic Complex Synthesis and Catalysis
- Mobile Crowdsensing and Crowdsourcing
- Fuel Cells and Related Materials
- Innovative concrete reinforcement materials
- Electric Vehicles and Infrastructure
University of Toronto
2021-2025
Hefei University of Technology
2023-2025
Sichuan University
2025
Dongfeng Motor (China)
2024
Tianjin University of Technology and Education
2024
Northeastern University
2024
Structural Genomics Consortium
2024
Yancheng Institute of Technology
2024
Shanghai Maritime University
2015-2023
University of British Columbia
2016-2021
Contemporary materials discovery requires intricate sequences of synthesis, formulation, and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy enabled delocalized asynchronous design-make-test-analyze cycles. We showcased this approach through the exploration molecular gain for organic solid-state lasers as frontier application in optoelectronics. Distributed robotic synthesis...
Self-driving laboratories (SDLs), which combine automated experimental hardware with computational experiment planning, have emerged as powerful tools for accelerating materials discovery. The intrinsic complexity created by their multitude of components requires an effective orchestration platform to ensure the correct operation diverse setups. Existing frameworks, however, are either tailored specific setups or not been implemented real-world synthesis. To address these issues, we...
Chemistry experimentation is often resource- and labor-intensive. Despite the many benefits incurred by integration of advanced special-purpose lab equipment, aspects are still manually conducted chemists, for example, polishing an electrode in electrochemistry experiments. Traditional automation infrastructure faces challenges when it comes to flexibly adapting new chemistry To address this issue, we propose a human-friendly flexible robotic system, ORGANA, that automates diverse set It...
Conventional materials discovery is a laborious and time-consuming process that can take decades from initial conception of the material to commercialization. Recent developments in acceleration platforms promise accelerate using automation experiments coupled with machine learning. However, most efforts chemistry focus on synthesis compound identification, integrated target property characterization receiving less attention. In this work, an automated platform introduced for molecules as...
Self-driving laboratories (SDLs) are next-generation research and development platforms for closed-loop, autonomous experimentation that combine ideas from artificial intelligence, robotics, high-performance computing. A critical component of SDLs is the decision-making algorithm used to prioritize experiments be performed. This SDL “brain” often relies on optimization strategies guided by machine learning models, such as Bayesian optimization. However, diversity hardware constraints...
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through automation high-throughput experimentation, and autonomization experiment planning execution, SDLs hold potential to greatly accelerate research in chemistry materials discovery. This review article provides in-depth analysis state-of-the-art SDL technology, its applications across various disciplines, implications for research, industry. additionally overview enabling technologies SDLs,...
Automation of electrochemical measurements can accelerate the discovery new electroactive materials.
Contemporary materials discovery requires intricate sequences of synthesis, formulation and characterization that often span multiple locations with specialized expertise or instrumentation. To accelerate these workflows, we present a cloud-based strategy enables delocalized asynchronous design–make–test–analyze cycles. We showcase this approach through the exploration molecular gain for organic solid-state lasers as frontier application in optoelectronics. Distributed robotic synthesis...
Electrochemical techniques are pivotal for material discovery and renewable energy; however, often the extensive chemical spaces to be explored require high-throughput experimentation (HTE) ensure timely results, which costly both instrument materials/consumables. While self-driving laboratories (SDL) promise efficient exploration, most contemporary implementations demand significant time, economic investment, expertise. This study introduces an open cost-effective autonomous electrochemical...
A novel mass spectrometric method for probing the flash chemistry of electrogenerated reactive intermediates was developed based on rapid collision mixing electrosprayed microdroplets by using a theta-glass capillary. The two individual microchannels capillary are asymmetrically or symmetrically fabricated with carbon bipolar electrode to produce in situ. Microdroplets containing newly formed collide those invoked reactants at sub-10 microsecond level, making it powerful tool exploring their...
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through automation experimental workflows, along with autonomization experiment planning, SDLs hold potential to greatly accelerate research in chemistry and materials discovery. This review article provides in-depth analysis state-of-the-art SDL technology, its applications across various disciplines, implications for research, industry. additionally overview enabling technologies SDLs, including...
This study develops a Zero-Inflated Negative Binomial (ZINB) regression model to evaluate the factors influencing loss of human life in shipping accidents using ten years' ship accident data South China Sea. The ZINB results show that expected is higher for collision, fire/explosion, contact, grounding, hull damage, machinery damage/failure and capsizing occurring adverse weather conditions during night periods. Sinking can cause highest compared all other types. There are fewer fatalities...
A highly regio- and stereoselective hydrochlorination/cyclization of enynes has been reported by FeCl3 catalysis. variety undergo this cyclization transformation with acetic chloride as the chlorine source H2O providing protons via a cationic pathway. This protocol provides cheap, simple, stereospecific, effective to afford heterocyclic alkenyl compounds Z isomers high yields (≤98%) regioselectivity.
The classical organic dyes anthracene, acridine, and phenazine, as building blocks in the construction of three covalent frameworks (COFs), are presented for comprehensive comparison studies. Employing a sophisticated atomic-level skeleton-editing strategy through precise adjustment nitrogen content enables regulation intrinsic properties across macro- to micro-scales, encompassing color, morphology, thermal stability, charge separation, transfer dynamics, energy level position,...
The Suzuki-Miyaura cross-coupling reaction is plagued by protodeboronation, an undesirable side with water that consumes the boronic acid derivatives required for reaction. Meticulous mechanistic studies have previously established protodeboronation to be highly sensitive nature of reagent and conditions. Particularly, presence bases, which are essential coupling, known catalyze protodeboronation. However, catalyzed palladium-phosphine complexes, benchmark catalyst system cross-coupling, has...
We have recently demonstrated the ability of using self-driving laboratories for AI-driven searches new emitters organic solid-state lasing devices. Our past workflow featured solubility challenges such large molecular moieties. In this next-generation study, we returned to drawing board explore a family compounds that were much solution processable and composed set electronic cores would give broader color response. Out 252 potential candidates, selectively performed comprehensive study...
Plasma-driven conversion of CH4 and CO2 into CH3COOH presents a sustainable pathway for greenhouse gas utilization, but the improvement selectivity remains bottleneck. Here, we present catalyst with atomically dispersed Cu species on SAPO-34 zeolites (based CHA topology), synergistically enhancing plasma-catalytic CH3COOH. Through simple impregnation method, obtain Cu1@SAPO-34 single atom catalysts where atoms (Cu SAs) are anchored to form unique tri-coordinated Cu1-O3 sites that exhibit...
Automation of electrochemical measurements can accelerate the discovery new electroactive materials. One hurdles to automated measurement is pretreatment electrodes because mechanical polishing usually conducted manually. Here we investigate automation using a robotic arm. We demonstrate station with moving pad and evaluate effect different motions. Our automatic method improved corroded electrodes, found motions was not significant. This research step toward automating electrochemistry...