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• Automated carousel-based electrochemical sensing toward microbiological and oncological settings.
  The integration of automation and electrochemical sensing is emerging as an important strategy to accelerate bioanalytical workflows, improve reproducibility, and reduce operator exposure to hazardous biological samples. Self-driving laboratories and automated…
  pubmed de Lima LF, Faustino LC, Mestanza NVB, Nascimento GHMD 等 2026 Sep 22 置信度 0.82
• Artificial intelligence for food innovation.
  Global food systems must deliver nutritious, sustainable foods while sharply reducing environmental impact. Yet, food innovation remains slow, empirical and fragmented. Artificial intelligence (AI) offers a transformative path to link molecular composition to …
  pubmed Datta B, Buehler MJ, Chow Y, Gligorić K 等 2026 Jul 置信度 0.82
• A Modular and Affordable Self-Driving Laboratory for Vision-Guided Optimization of Metal Electrodeposition.
  Metal electrodeposition is a widely used materials synthesis technique; however, industrial applications often require the optimization of complex precursor formulations and electrodeposition parameters, which is typically performed in a slow, inefficient, and…
  pubmed Pence MA, Sgro G, Yang B, Luo L 2026 Jul 22 置信度 0.82
• AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation.
  The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we intr…
  pubmed Panapitiya G, Saldanha E, Job H, Hess O 2026 Jun 25 置信度 0.82
• Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.
  Artificial intelligence and organic chemistry are redefining each other in a fundamentally bidirectional relationship. This Review highlights how the intrinsic challenges of organic chemistry have acted as a catalyst for conceptual and methodological innovatio…
  pubmed Chawla NV, González-Montiel GA, Guo K, Guo T 等 2026 Jul 8 置信度 0.82
• BAGO: A Self-Optimizing Tool for LC-MS Gradient Design in Metabolomics.
  A self-driving metabolomics laboratory has long been envisioned but remains largely unrealized due to the complexity of analytical method design. As an initial step toward this goal, we developed BAGO, a self-optimizing framework for automated liquid chromatog…
  pubmed Yu H, Biswas P, Rideout E, Cao Y 等 2026 Jun 30 置信度 0.82
• Decoding α-MoC(1-) (x) Nanoparticle Formation in Continuous Flow via Machine Learning.
  Molybdenum carbide nanoparticles (α-MoC 1- x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1- x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitor…
  pubmed Pan B, Forsberg AP, Chairil R, Madani MS 等 2026 Jul 置信度 0.82
• Autonomous Chemistry and Materials Innovation Driven by Scientific Agents.
  Large language model (LLM)-based agents are reshaping how self-driving laboratories (SDLs) may support autonomous chemical and materials research. Although SDLs have enabled major advances in mechanized experimentation and closed-loop optimization, their scien…
  pubmed Xie Z, Luo M, Ye Z, Chen L 等 2026 May 25 置信度 0.82
• Leveling Up Upconverting Nanoparticles with Machine Learning.
  ConspectusUpconverting nanoparticles (UCNPs) transform low-energy light into higher-energy photons, enabling applications in subwavelength and subsurface imaging, nanoscale sensing, therapeutics, optogenetics, printing, and optical computing. However, the wide…
  pubmed Luo R, Hamm J, Chan EM 2026 Jun 16 置信度 0.82
• From High-Throughput Screening to Generative Design: Artificial Intelligence-Driven Dielectric Materials Discovery.
  High-performance dielectric materials are strategically vital for post-Moore microelectronics, high-power electrostatic capacitors, and flexible advanced electronics, yet their design is constrained by the intrinsic trade-off between breakdown strength ( E b )…
  pubmed Tang J, Cao L, Xu G, Li M 2026 Jun 3 置信度 0.82
• Autonomous microfluidic experimentation for exploring reaction inference and synthesizing double perovskite nanoplatelets.
  Self-driving laboratories enable accelerated exploration of chemical and materials spaces by coupling automated experimentation with machine-learning-guided decision making. However, extending autonomous discovery to compositionally complex materials with mult…
  pubmed Li J, Delgado-Licona F, Liu Z, Perry H 等 2026 May 4 置信度 0.82
• Interactive Cognition of Self-driving: A Multidimensional Analysis Model and Implementation.
  Self-driving vehicles rely closely on interactions with humans, vehicles, and the surrounding environment. However, the interactive analysis of self-driving is impacted by multiple perception sources, heterogeneous data, and complex environments in actual scen…
  pubmed Ma N, Wu Z, Li K, Xu G 等 2025 置信度 0.82
• Accelerated Emergence of Self-Driving Laboratories for Accelerating Materials Discovery.
  The rise of self-driving laboratories (SDLs) marks a transformative era in materials science. By leveraging automation and machine learning, SDLs provide unprecedented opportunities to rapidly explore complex chemical landscapes and accelerate discoveries. In …
  pubmed Brown AK, Soni A, Lin D, Berlinguette CP 2026 Mar 25 置信度 0.82
• Closing the loop: AI-driven integration of multi-omics and phenomics for systematic resilient crop engineering.
  Sustaining global food security amidst accelerating climate change necessitates a paradigm shift from reductionist breeding to systematic, AI-driven crop engineering. This review provides a critical synthesis of the edge-to-cloud closed-loop framework that uni…
  pubmed Yang Z, Tang T 2026 Sep 置信度 0.82
• Chemist Eye: a visual language model-powered system for safety monitoring and robot decision-making in self-driving laboratories.
  The use of robotics and automation in self-driving laboratories (SDLs) can introduce additional safety complexities, beyond those already present in conventional research laboratories. Personal protective equipment (PPE) is an essential requirement for ensurin…
  pubmed Munguia-Galeano F, Zhou Z, Veeramani S, Fakhruldeen H 等 2026 May 20 置信度 0.82
• Recent Advances in Artificial Intelligence in Organic Electronic Research.
  The discovery of novel organic optoelectronic materials for applications such as organic light-emitting diodes, organic photovoltaics, and organic field-effect transistors has traditionally been constrained by the inefficiency of trial-and-error experimentatio…
  pubmed Zhang Q, Su Z, Zhang H, Sun Y 等 2026 May 置信度 0.82
• CrystalX: High-Accuracy Crystal Structure Analysis Using Deep Learning.
  Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences. This sophisticated technique necessitates not only a solid foundation in crystallography but also a profound comprehension of the intricacies of …
  pubmed Zheng K, Huang W, Ouyang W, Zhong HS 等 2026 May 27 置信度 0.82
• A user's guide to your first self-driving liquid handling lab.
  Experimentation is inherently difficult because most methods require substantial refinement, calibration, and validation before high-quality, reliable data can be collected. In most cases, experimental outcomes are impacted by multiple variables, thus requirin…
  pubmed Maroulis AP, Waynor DM, Gallagher QM, Patel RA 等 2026 May 20 置信度 0.82
• Spinal posture helps crash response evaluation of reclined occupant.
  The growing adoption of self-driving vehicles and zero-gravity seats presents emerging challenges for occupant safety. With lumbar spine injury of reclined occupants receiving increasing research attention, the influence of spinal postures on crash response wa…
  pubmed Shen W, Tang J, Tan P, Zhuang Z 等 2026 Apr 6 置信度 0.82
• Database utility for cyclovoltammetry knowledge (DUCK): unified platform for electrochemical data.
  Cyclic voltammetry (CV) is a valuable tool for electrochemistry, providing qualitative and quantitative information about redox processes occurring in solution. Despite its ubiquity, the lack of standardized reporting and sharing protocols, commonly adopted, s…
  pubmed Garay-Ruiz D, Pablo-García S, Hao H, Martín-González M 2026 Apr 22 置信度 0.82
• Artificial Intelligence as a Disruptive Force in Pharmaceutical Innovation: Transforming Discovery, Development, and Manufacturing.
  Artificial Intelligence (AI) is increasingly being implemented in pharmaceutical sciences and has the potential to improve efficiency across the value chain, from drug candidate discovery to manufacturing, quality monitoring, and regulatory process support. No…
  pubmed Herdiana Y, Mohammed AFA, Kautsar AP, Sopyan I 等 2026 置信度 0.82
• A Self-Driving and Self-Reporting Petal-Like Au-Cu(2)O Metalloenzyme for Probing H(2)S-Mediated Cuproptosis.
  Hydrogen sulfide (H 2 S), highly enriched in colorectal tumors, acts as an upstream regulator of copper homeostasis and cuproptosis. However, most existing cuproptosis nanotherapeutics focus on downstream copper overload while lacking the ability to resolve th…
  pubmed Jiang L, Lu Q, Gong E, Liu J 等 2026 Mar 31 置信度 0.82
• Toward self-driving laboratory 2.0 for chemistry and materials discovery.
  The convergence of laboratory automation, artificial intelligence (AI), and data-driven science has catalyzed the emergence of self-driving laboratories (SDLs), autonomous platforms capable of designing, executing, and analyzing experiments with minimal human …
  pubmed Lee H, Yoo HJ, Jang HS, Park B 等 2026 May 26 置信度 0.82
• LUMI-lab: A foundation model-driven autonomous platform enabling discovery of ionizable lipid designs for mRNA delivery.
  Integrating AI with robotics offers a promising approach to molecular discovery and optimization, enabling efficient exploration of vast chemical spaces. However, its application in emerging fields is often constrained by sparse historical data. Here, we intro…
  pubmed Xu Y, Cui H, Pang K, Li G 等 2026 Mar 19 置信度 0.82
• Autonomous microfluidic labs: progress and prospects.
  Global challenges such as climate change, escalating energy demands, and health equity require new scientific innovations able to deliver timely solutions. Self-driving laboratories (SDLs) combine robotics and lab automation with artificial intelligence to eff…
  pubmed Damir S, Delgado-Licona F, deMello A, Abolhasani M 2026 Mar 4 置信度 0.82
• The ADePT framework for assessing autonomous laboratory robotics.
  Laboratory robotics is advancing from routine automation toward autonomous systems capable of intelligent decision-making and flexible execution. This perspective outlines key milestones and introduces the ADePT framework, which defines four core dimensions of…
  pubmed Salazar-Villacis P, Benyahia B 2026 Feb 20 置信度 0.82
• Boosting Computational Catalysis and Chemical Reactivity with Artificial Intelligence.
  Artificial intelligence (AI) and machine learning (ML) are rapidly reshaping the landscape of computational chemistry, offering new opportunities for accelerating catalyst discovery and deepening our understanding of chemical reactivity. This perspective highl…
  pubmed Vogiatzis KD, Corminboeuf C, Nova A, Jorner K 等 2026 Mar 11 置信度 0.82
• Discovery of tunable and soluble organic emitters for solid-state lasers with a self-driving laboratory.
  We have recently demonstrated the ability of using self-driving laboratories for AI-driven searches of organic emitters for solid-state lasing devices. Our past workflow featured solubility challenges for such large molecular moieties. In this next-generation …
  pubmed Park HS, Mazaheri M, Choi C, Hao H 等 2026 Feb 19 置信度 0.82
• Pondering the Future of Chemical Research Amid the Wider Adoption of Artificial Intelligence Technologies.
  The rapid adoption of artificial intelligence (AI) and machine learning (ML) in chemistry coincides with increasing structural pressures on academic research, including funding constraints, talent competition, and changing attitudes toward scientific careers. …
  pubmed Boiko DA, Polynski MV 2026 May 5 置信度 0.82
• Autonomous Synthesis of Nanoparticles with Target Scattering Patterns.
  Controlled synthesis of materials with specified atomic structures underpins technological advances yet remains reliant on iterative, trial-and-error approaches. Nanoparticles (NPs), whose atomic arrangement dictates their emergent properties, 1-5 are particul…
  pubmed Anker AS, Jensen JH, González-Duque M, Moreno R 等 2026 Mar 3 置信度 0.82
• Dara: Automated Multiple-Hypothesis Phase Identification and Refinement from Powder X‑ray Diffraction.
  Powder X-ray diffraction (XRD) is a foundational technique for characterizing crystalline materials. However, the reliable interpretation of XRD patterns, particularly in multiphase systems, remains a manual and expertise-demanding task. As a characterization …
  pubmed Fei Y, McDermott MJ, Rom CL, Wang S 等 2026 Feb 10 置信度 0.82
• Machine Learning and Autonomous Systems for Accelerated Synthesis.
  Autonomous systems integrating machine learning (ML) and laboratory automation are transforming synthetic chemistry by enabling closed-loop experimentation and discovery. In this review, we examine the state-of-the-art in autonomous systems for organic synthes…
  pubmed McDonald MA, Jensen KF 2026 May 置信度 0.82
• Infrared spectroscopy-assisted prediction of impurities in chemicals using machine learning: towards smart self-driving laboratories.
  The changeable nature of chemicals requires constant monitoring. In a self-driving laboratory (SDL), manual revision of chemicals should be replaced by automated compliance checks. Infrared spectroscopy is an SDL compatible tool that can be integrated into a r…
  pubmed Kutskaia AM, Rodygin KS 2026 Feb 11 置信度 0.82
• Artificial intelligence and machine learning guided optimization in drug delivery.
  The optimisation of drug delivery systems is a complex, multidimensional challenge involving the interplay of formulation composition, process parameters, and biological performance. Traditional empirical and statistical approaches are increasingly limited by …
  pubmed Ros H, Chan N, Cook MT, Shorthouse D 2026 May 置信度 0.82
• Self-driving bioprinting laboratories.
  The severe shortage of donor organs and limitations of current disease models highlight the urgent need for transformative strategies in tissue engineering (TE) and regenerative medicine (RM). Bioprinting has emerged as a powerful approach for creating functio…
  pubmed Liu S, Kaur N, Song DH, Moses JC 等 2026 Jan 22 置信度 0.82
• Materials Informatics: Emergence to Autonomous Discovery in the Age of AI.
  We provide a perspective on the evolution of materials informatics, tracing its conceptual roots to foundational ideas in physics and information theory and its maturation through the integration of machine learning and artificial intelligence (AI). Early cont…
  pubmed Lookman T, Liu Y, Gao Z 2026 May 置信度 0.82
• Digital twins for self-driving chemistry laboratories.
  pubmed Zhao T, Zeng Y 2026 Jan 置信度 0.82
• Programmable Light-Driven Color Tuning of Perovskite Quantum Dots.
  Precise, sustainable, and scalable bandgap tuning of metal halide perovskite (MHP) nanocrystals (NCs) is critical for their integration into advanced optoelectronic and photocatalytic systems. Photoinduced anion exchange reactions (PIAERs) enable uniform halid…
  pubmed Jha P, Mukhin N, Xu J, Moran CHJ 等 2025 Dec 24 置信度 0.82
• A Modular Self-Driving Laboratory for Automated Synthesis of CsPb(Cl/Br/I)(3) Perovskite Nanocrystals.
  Self-driving laboratories (SDLs) integrating automation and data-driven control are increasingly used in materials synthesis. Existing SDLs still face challenges in hardware integration and stable flow operation. Here, we report a modular fluidic-microwave SDL…
  pubmed Chen Y, Rajabi-Kochi M, Huang G, Wu J 等 2026 Jan 14 置信度 0.82
• Pareto-Optimal Experimentation: Human-Guided Multi-Objective Bayesian Optimization in Scanning Probe Microscopy.
  Automated experimentation has the potential to accelerate scientific discovery across disciplines, but its success requires systematic methods to optimize multiple, often conflicting, objectives under uncertainty. We present multi-objective Bayesian optimizati…
  pubmed Liu Y, Kalinin SV 2026 Jan 14 置信度 0.82
• Interpreting X-ray Diffraction Patterns of Metal-Organic Frameworks via Generative Artificial Intelligence.
  Metal-organic frameworks (MOFs) have attracted considerable attention owing to their multifaceted applications and structurally tunable characteristics. Powder X-ray diffraction (XRD) is an essential technique for high-throughput characterization of MOFs. Howe…
  pubmed Feng B, Wang B, Lv L, Zhang M 等 2026 Jan 14 置信度 0.82
• Chemistry in Transformation: A European Moment.
  Chemistry stands at a pivotal juncture, facing unprecedented expectations to decarbonize, enable circularity, and sustain essential sectors, while remaining globally competitive. Europe embodies these pressures acutely. Although the region excels in frontier r…
  pubmed García-Martínez J 2026 Jan 22 置信度 0.82
• EcoBOT: an AI/ML enabled automated phenotyping capability for model plants.
  Advances in automation and AI/ML offer new opportunities for plant science, including design, modeling, and analysis. This study aimed to develop an automated platform for researching small model plants under axenic conditions and integrate it with AI/ML tools…
  pubmed Andeer PF, Zwart PH, Ushizima D, Noack MM 等 2025 置信度 0.82
• Leading artificial intelligence-driven drug discovery platforms: 2025 landscape and global outlook.
  Artificial intelligence (AI) has progressed from experimental curiosity to clinical utility, with AI-designed therapeutics now in human trials across diverse therapeutic areas. This review critically compares 5 leading AI-driven discovery platforms: generative…
  pubmed Dharmasivam M, Kaya B, Akinware A, Azad MG 等 2026 Jan 置信度 0.82
• A VibV Dataset Integrating Vibration and Vision for Enhanced Safety in Self-Driving Tasks.
  Due to the complexity of real-world traffic scenarios, autonomous driving systems still face safety challenges and uncontrolled threats in blind spots. Currently, it primarily relies on cameras, LiDAR, radar, and their fusion to perceive the environment. Howev…
  pubmed Shen Y, Zhang X, Yang L, Chen Z 等 2025 Dec 11 置信度 0.82
• Self-driving lab discovers principles for steering spontaneous emission beyond conventional Fourier optics.
  We develop an autonomous experimentation platform to accelerate interpretable scientific discovery in ultrafast nanophotonics, targeting a novel method to steer spontaneous emission from reconfigurable semiconductor metasurfaces. Despite the potential of recon…
  pubmed Desai S, Addamane S, Tsao JY, Brener I 等 2025 Dec 9 置信度 0.82
• Toward full automation in synthetic biology: A progressive conceptual framework integrating robotics and intelligent agents.
  Synthetic biology is a rapidly evolving discipline that seeks to understand, modify, design, and build biological systems by applying modular and systemic principles inspired by engineering. Automation in synthetic biology offers significant gains in efficienc…
  pubmed Plante M, Champie A, Michaud F, Rodrigue S 2026 Jan 置信度 0.82
• Perspectives for artificial intelligence in bioprocess automation.
  Recent advances in artificial intelligence (AI) have rapidly changed the lab automation landscape, promoting self-driving laboratories (SDLs) that enable autonomous scientific discovery. These trends are increasingly applied in bioprocess development, yet…
  pubmed Helleckes LM, Putz S, Gupta K, Franzreb M 等 2026 Feb 置信度 0.82
• Advances and critical evaluation of autonomous protein engineering: towards transparent, accessible, and reproducible platforms.
  Protein engineering aims to enhance enzymatic properties such as activity, selectivity, stability, and solvent tolerance by restructuring protein frameworks beyond natural performance limits. This process relies on the iterative Design-Build-Test-Learn cycle, …
  pubmed Weigmann KF, Bornscheuer UT, Doerr M 2026 Feb 置信度 0.82
• Localization, inspection, and reasoning (LIRA) module for autonomous workflows in self-driving laboratories.
  Self-driving labs (SDLs) combine robotic automation with artificial intelligence (AI) to allow autonomous, high-throughput experimentation. However, robot manipulation in most SDL workflows operates in an open-loop manner, lacking real-time error detection and…
  pubmed Zhou Z, Veeramani S, Munguia-Galeano F, Fakhruldeen H 等 2025 Nov 28 置信度 0.82
• Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy.
  Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. T…
  pubmed Barakati K, Liu Y, Funakubo H, Kalinin SV 2025 Nov 26 置信度 0.82
• A Visual Dataset for Anomaly Detection in Self-Driving Laboratories.
  Self-driving laboratories accelerate the application of the scientific method and the discovery process through high-throughput experimentation, intelligent perception and planning, and effective human-robot collaboration. However, detecting anomalies in event…
  pubmed Lin S, Chen Z, Jia X, Wang Y 等 2025 Nov 14 置信度 0.82
• Accident prevention in electric vehicles through battery state-of-health estimation based on GRU-HSIC.
  The State of Health (SOH) of an Electric Vehicle (EV) battery has a direct impact on both vehicle performance and passenger safety. Accurate SOH estimation is critical for accident prevention, as estimation inaccuracies can enable undetected battery degradatio…
  pubmed Dang L, Huang Z, Xie Y, Ye Q 等 2026 Jan 置信度 0.82
• Ionizable lipids empowered with artificial intelligence for mRNA delivery.
  Ionizable lipids are the most significant component of lipid nanoparticles and govern the ability to deliver mRNA in vitro and in vivo. Traditional development methods for ionizable lipids depend on the labor-intensive multistep synthesis and empirical screeni…
  pubmed Zhang G, Zuo Z, Wang J, Gong N 等 2025 Dec 置信度 0.82
• Architectures of emerging biofoundry platforms for synthetic biology.
  Biofoundries are integrated, automated platforms that accelerate synthetic biology applications by facilitating high-throughput and labor-intensive experiments. They incorporate robotic systems, analytical instruments, and software for workflow design, executi…
  pubmed Heo YB, Park JS, Woo HM 2025 Dec 置信度 0.82
• Automating quantum computing laboratory experiments with an agent-based AI framework.
  Fully automated self-driving laboratories promise high-throughput, large-scale scientific discovery by reducing repetitive labor. However, they require deep integration of laboratory knowledge, which is often unstructured, multimodal, and hard to incorporate i…
  pubmed Cao S, Zhang Z, Alghadeer M, Fasciati SD 等 2025 Oct 10 置信度 0.82
• Evaluating large language model agents for automation of atomic force microscopy.
  Large language models (LLMs) are transforming laboratory automation by enabling self-driving laboratories (SDLs) that could accelerate materials research. However, current SDL implementations rely on rigid protocols that fail to capture the adaptability and in…
  pubmed Mandal I, Soni J, Zaki M, Smedskjaer MM 等 2025 Oct 14 置信度 0.82
• Harnessing data and control with AI/ML-driven polymerization and copolymerization.
  Creating and curating new data to augment heuristics is a forthcoming approach to materials science in the future. Highly improved properties are advantageous even with "commodity polymers" that do not need to undergo new synthesis, high-temperature processes,…
  pubmed Advincula R, Ivanov I, Vasudevan R, Kumar R 等 2026 Jan 8 置信度 0.82
• Reac-Discovery: an artificial intelligence-driven platform for continuous-flow catalytic reactor discovery and optimization.
  Digital technologies, including artificial intelligence and additive manufacturing, have revolutionized chemistry and chemical engineering. In reactor engineering, performance improvements have been enabled by novel geometries, yet design approaches have tradi…
  pubmed Tinajero C, Zanatta M, Sánchez-Velandia JE, García-Verdugo E 等 2025 Oct 13 置信度 0.82
• AI, agentic models and lab automation for scientific discovery - the beginning of scAInce.
  Until recently, the conversation about generative artificial intelligence in science revolved around the textual prowess of large language models such as GPT-3.5 and the promise that they might one day draft a decent literature review. Since then, progress has…
  pubmed Hartung T 2025 置信度 0.82
• Bridging Innovation and Efficiency: The Promises and Challenges of Self-Driving Labs as Sustainable Drivers for Chemistry.
  Self-driving laboratories (SDLs) are reshaping scientific discovery by combining robotics, artificial intelligence (AI), and data science to automate the full Design-Make-Test-Analyze (DMTA) cycle. This review highlights how SDLs address the inefficiencies of …
  pubmed Formica FA, Wu E, Brey L, Pacheco Gutiérrez D 等 2025 Sep 10 置信度 0.82
• High-Throughput Microfluidic Electroporation (HTME): A Scalable, 384-Well Platform for Multiplexed Cell Engineering.
  Electroporation-mediated gene delivery is a cornerstone of synthetic biology, offering several advantages over other methods: higher efficiencies, broader applicability, and simpler sample preparation. Yet, electroporation protocols are often challenging to in…
  pubmed Gaillard WR, Sustarich J, Li Y, Carruthers DN 等 2025 Jul 22 置信度 0.82
• Deep active optimization for complex systems.
  Inferring optimal solutions from limited data is considered the ultimate goal in scientific discovery. Artificial intelligence offers a promising avenue to greatly accelerate this process. Existing methods often depend on large datasets, strong assumptions abo…
  pubmed Wei Y, Peng B, Xie R, Chen Y 等 2025 Sep 置信度 0.82
• Autonomous multi-robot synthesis and optimization of metal halide perovskite nanocrystals.
  Metal halide perovskite (MHP) nanocrystals (NCs) offer extraordinary tunability in their optical properties, yet fully exploiting this potential is challenged by a vast and complex synthesis parameter space. Herein, we introduce Rainbow, a multi-robot self-dri…
  pubmed Xu J, Moran CHJ, Ghorai A, Bateni F 等 2025 Aug 22 置信度 0.82
• Autonomous 'self-driving' laboratories: a review of technology and policy implications.
  This article reviews and provides perspective on the emerging technology of autonomous, 'self-driving' laboratories (SDLs) that combine artificial intelligence (AI) and laboratory automation to perform research in chemistry, materials science and biological sc…
  pubmed Tobias AV, Wahab A 2025 Jul 置信度 0.82
• Steering towards safe self-driving laboratories.
  The past decade has witnessed remarkable advancements in autonomous systems, such as automobiles that are evolving from traditional vehicles to ones capable of navigating complex environments without human intervention. Similarly, the rise of self-driving labo…
  pubmed Leong SX, Griesbach CE, Zhang R, Darvish K 等 2025 Oct 置信度 0.82
• Atomistic Insights into Halide Double Perovskite Nanocrystals obtained by Multistep Synthesis and Efficient Compositional Engineering.
  Lead-free halide double perovskites (HDP), particularly those within the Cs 2 B + InCl 6 family that show a direct band gap, have recently emerged as promising semiconductors to address key challenges associated with lead-based perovskites, such as toxicity an…
  pubmed Dengo N, Macias-Pinilla DF, Anzini P, Colombo M 等 2025 Aug 26 置信度 0.82
• Tech-Enhanced Synthesis: Exploring the Synergy between Organic Chemistry and Technology.
  Recent years have witnessed growing interest in integrating enabling technologies into synthetic organic chemistry to address long-standing challenges in reproducibility, sustainability, and scalability. This perspective showcases how modern tools, ranging fro…
  pubmed Bonciolini S, Pulcinella A, Noël T 2025 Aug 13 置信度 0.82
• Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self-Driving Lab.
  Optimizing enzymatic catalysis is crucial for enhancing the efficiency and scalability of many bioprocesses such as biotransformations, pharmaceutical synthesis, and food processing, as well as for improving the performance of analytical applications, includin…
  pubmed Putz S, Teetz N, Abt M, Jerono P 等 2025 Nov 置信度 0.82
• Affordable Automated Modules for Lab-Scale High-Throughput Synthesis of Inorganic Materials.
  The development of sustainable advanced materials is increasingly driven by the need for sustainable, faster, scalable, and more efficient research workflows. Advancements in computational screening, high-throughput experimentation, and artificial intelligence…
  pubmed Monterrubio I, Orive J, Ismail M, Castillo E 等 2025 Sep 16 置信度 0.82
• Self-Driving Laboratories: Translating Materials Science from Laboratory to Factory.
  The field of materials science stands at a critical inflection point. While laboratory innovations continue to emerge at an unprecedented pace, the traditional timeline from discovery to market in 10-20 years has become an unacceptable bottleneck in addressing…
  pubmed Low AKY, Cheng JJW, Hippalgaonkar K, Ng LWT 2025 Jul 22 置信度 0.82
• Opportunities and Challenges of Self-Driving Laboratories for Sensing.
  pubmed Masson JF 2025 Jul 25 置信度 0.82
• Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.
  The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease pro…
  pubmed Ibrahim KA, Cathala C, Bevilacqua C, Feletti L 等 2025 Jul 24 置信度 0.82
• Best practices for multi-fidelity Bayesian optimization in materials and molecular research.
  Multi-fidelity Bayesian optimization (MFBO) is a promising framework to speed up materials and molecular discovery as sources of information of different accuracies are at hand at increasing cost. Despite its potential use in chemical tasks, there is a lack of…
  pubmed Sabanza-Gil V, Barbano R, Pacheco Gutiérrez D, Luterbacher JS 等 2025 Jul 置信度 0.82
• Autonomous De Novo Lead Halide CsPbBr(3) Perovskite Quantum Dots Synthesis Platform With Transfer Learning Accelerated Bayesian Optimization.
  Compared to traditional expert-driven pattern, the emerging concept of self-driving labs enabled by flow chemistry and artificial intelligence provides a new autonomous paradigm to significantly improve the R&D efficiency of functional material synthesis. …
  pubmed Hu H, Wang H, Huang X, Geng Y 等 2025 Sep 置信度 0.82
• The Alchemist, the Scientist, and the Robot: Exploring the Potential of Human-AI Symbiosis in Self-Driving Polymer Laboratories.
  Polymer chemistry research has progressed through three methodological eras: the alchemist's intuitive trial-and-error, the scientist's rule-based design, and the robot's algorithm-guided automation. While approaches combining combinatorial chemistry with stat…
  pubmed Dadfar B, Alemdag B, Kabay G 2025 Dec 置信度 0.82
• Self-Driving Laboratory for Accelerated On-Surface Synthesis under Ultrahigh Vacuum.
  The automation of experimentation has accelerated advances in materials synthesis. While most automated platforms operate under atmospheric conditions, many synthesis processes require ultrahigh vacuum (UHV) environments with stringent constraints. We present …
  pubmed Li Y, Huang Q, Yang T, Zhu Z 等 2025 Jul 30 置信度 0.82
• Analysis of factors contributing to severity of AV crashes at intersections: Insights from the Autonomous Vehicle Operation Incident Dataset Across The Globe (AVOID).
  The market for autonomous vehicles (AVs) is developing rapidly, while safety concerns persist as a critical challenge hindering their widespread development and commercialization. Intersections, characterized by highly dynamic and unpredictable traffic conditi…
  pubmed Guo R, Chen Y, Zhang Y, Yi F 2026 置信度 0.82
• Solving Mazes of Organelle-Targeted Therapies with DNA Nanomachines.
  Despite decades of research, cancer remains a growing global health challenge. Nanomaterials-based therapeutics have shown promise, but their clinical applications are often limited by poor selectivity and undesirable side effects. Recently, deoxyribonucleic a…
  pubmed Farooq MU, Lawrie CH, Deng NN 2025 Oct 置信度 0.82
• Data-driven microstructural optimization of Ag-Bi-I perovskite-inspired materials.
  Microstructural design is crucial yet challenging for thin-film semiconductors, creating barriers for new materials to achieve practical applications in photovoltaics and optoelectronics. We present the Daisy Visual Intelligence Framework (Daisy), which combin…
  pubmed Nandishwara KM, Cheng S, Liu P, Zhu H 等 2025 置信度 0.82
• A self-supervised robotic system for autonomous contact-based spatial mapping of semiconductor properties.
  Integrating robotically driven contact-based material characterization techniques into self-driving laboratories can enhance measurement quality, reliability, and throughput. While deep learning models support robust autonomy, current methods lack reliable pix…
  pubmed Siemenn AE, Das B, Ji K, Sheng F 等 2025 Jul 4 置信度 0.82
• A refined lion optimizer for deep learning.
  Optimization algorithms play a fundamental role in training neural networks. The optimizer focuses on the updating weights of momentum and velocity on learning rates and losses, furthermore the complexity of the optimizer and the quantity of updated parameters…
  pubmed Rong J, Ma C, Zhang Q, Cao Y 等 2025 Jul 2 置信度 0.82
• Learnable Operational Design Condition monitor for failure prediction in autonomous driving.
  Autonomous vehicle accidents frequently originate from violations of Operational Design Conditions (ODC)-the predefined operational limits of vehicle states, environmental factors, and driver capabilities. ODC violation indicates a high probability of impendin…
  pubmed Xu H, Bian Y, Li Y, Qin H 等 2025 Sep 置信度 0.82
• Hybrid Supervised and Reinforcement Learning for Motion-Sickness-Aware Path Tracking in Autonomous Vehicles.
  Path tracking is an essential task for autonomous driving (AD), for which controllers are designed to issue commands so that vehicles will follow the path of upper-level decision planning properly to ensure operational safety, comfort, and efficiency. Current …
  pubmed Lv Y, Chen Y, Chen Z, Fan Y 等 2025 Jun 12 置信度 0.82
• Characterizing Transport Properties of Surface Charged Nanofiltration Membranes via Model-Based Data Analytics.
  This study presents an integrated framework for characterizing the transport properties of surface-charged nanofiltration (NF) membranes through dynamic diafiltration experiments and model-based data analytics. By incorporating startup dynamics, time correctio…
  pubmed Liu X, Estrada L, Ouimet JA, McClure M 等 2025 Jun 18 置信度 0.82
• A revolutionary paradigm in chemistry and materials science research: self-driving laboratories.
  A self-driving laboratory (SDL), an automated experimental platform that integrates machine learning algorithms and robotics, has the potential to revolutionize traditional research methods and accelerate progress in chemistry and materials science. However, d…
  pubmed Qiu J, Zhu L, Feng Z, Luo Z 等 2025 Jul 3 置信度 0.82
• Self-Driving and Detachable Lab-Microrobots Tailor Drug Delivery for Closed-Loop Stimulation of the Antitumor Immune Cycle.
  Hypoxia arises in most solid tumors with insufficient blood flow, which hinders the delivery and efficacy of therapeutic agents to tumors. In this work, utilizing anaerobic bacteria capable of seeking out hypoxic areas for flourishing, we constructed a liposom…
  pubmed Huang H, Peng H, He Y, Chen Y 等 2025 Jul 1 置信度 0.82
• From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing.
  Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remai…
  pubmed Petzold CJ, Mukhopadhyay A 2025 Aug 置信度 0.82
• IvoryOS: an interoperable web interface for orchestrating Python-based self-driving laboratories.
  Self-driving laboratories (SDLs), powered by robotics, automation and artificial intelligence, accelerate scientific discoveries through autonomous experimentation. However, their adoption and transferability are limited by the lack of standardized software ac…
  pubmed Zhang W, Hao L, Lai V, Corkery R 等 2025 Jun 4 置信度 0.82
• Biohybrids of Anoxia-Targeted Bacteria/MDPP for Enabling Targeted Synergistic Immunotherapy and Chemotherapy Against Breast Tumors.
  The hypoxic tumor microenvironment (TME) significantly impacts the effectiveness of various therapies on breast cancer. Conventional chemotherapeutic agents are unable to target hypoxic tumor tissue specifically, leading to reduced treatment efficacy and sever…
  pubmed Hu T, Zhang L, Lu Y, Xiong K 等 2025 置信度 0.82
• Dirac-cone induced metallic conductivity in Cu(3)(HHTP)(2): high-quality MOF thin films fabricated via ML-driven robotic synthesis.
  Metal-organic frameworks have garnered interest for over 25 years in energy and electronics, yet their adoption in devices has been hindered by low electrical conductivity, largely attributed to activated transport. Our study demonstrates a significant shift, …
  pubmed Scheiger C, Pöhls JF, Mostaghimi M, Pilz L 等 2025 Aug 11 置信度 0.82
• Boosted Water-Induced Electricity Generation via a Multistrategy Approach for a Self-Driven System.
  Carbon-based water-induced generators (WIGs) with unique advantages offer a promising method for autonomous power generation. However, the traditional configuration still suffers from low output power. Herein, we introduce a promising WIG with high power outpu…
  pubmed Hu H, Li X, Wu S, Zhang Z 等 2025 Jun 4 置信度 0.82
• Self-Driving like a Human driver instead of a Robocar: Personalized comfortable driving experience for autonomous vehicles
  This paper issues an integrated control system of self-driving autonomous vehicles based on the personal driving preference to provide personalized comfortable driving experience to autonomous vehicle users. We propose an Occupant's Preference Metric (OPM) whi…
  arxiv Il Bae, Jaeyoung Moon, Junekyo Jhung, Ho Suk 等 2020-01-12T11:07:07Z 置信度 0.78 eess.SYcs.RO
• Agents for self-driving laboratories applied to quantum computing
  Fully automated self-driving laboratories are promising to enable high-throughput and large-scale scientific discovery by reducing repetitive labour. However, effective automation requires deep integration of laboratory knowledge, which is often unstructured, …
  arxiv Shuxiang Cao, Zijian Zhang, Mohammed Alghadeer, Simone D Fasciati 等 2024-12-10T23:30:44Z 置信度 0.78 cs.AIquant-ph
• Incorporating Voice Instructions in Model-Based Reinforcement Learning for Self-Driving Cars
  This paper presents a novel approach that supports natural language voice instructions to guide deep reinforcement learning (DRL) algorithms when training self-driving cars. DRL methods are popular approaches for autonomous vehicle (AV) agents. However, most e…
  arxiv Mingze Wang, Ziyang Zhang, Grace Hui Yang 2022-06-21T10:55:39Z 置信度 0.78 cs.HCcs.CLcs.CVcs.LGcs.SD
• The Evolving Role of Programming and LLMs in the Development of Self-Driving Laboratories
  Machine learning and automation are transforming scientific research, yet the implementation of self-driving laboratories (SDLs) remains costly and complex, and it remains difficult to learn how to use these facilities. To address this, we introduce Claude-Lig…
  arxiv John R. Kitchin 2025-03-30T19:09:04Z 置信度 0.78 cs.HC
• Autonomous Manipulation of Hazardous Chemicals and Delicate Objects in a Self-Driving Laboratory: A Sliding Mode Approach
  Precise handling of chemical instruments and materials within a self-driving laboratory environment using robotic systems demands advanced and reliable control strategies. Sliding Mode Control (SMC) has emerged as a robust approach for managing uncertainties a…
  arxiv Shifa Sulaiman, Francesco Schetter, Tobias Jensen, Simon Bøgh 等 2026-01-18T21:05:47Z 置信度 0.78 cs.RO
• Advancing the Pareto front for thin-film materials using a self-driving laboratory
  Useful materials must satisfy multiple objectives, where the optimization of one objective is often at the expense of another. The Pareto front reports the optimal trade-offs between competing objectives. Here we report a self-driving laboratory, "Ada", that d…
  arxiv Benjamin P. MacLeod, Fraser G. L. Parlane, Connor C. Rupnow, Kevan E. Dettelbach 等 2021-06-01T20:07:28Z 置信度 0.78 cond-mat.mtrl-sciphysics.app-ph
• Chemical Reaction Engineering and Catalysis: AI/ML Workflows and Self-Driving Laboratories
  Chemical reaction engineering is key to industrial might and sustainable chemistry. This will be enabled using smart, efficient catalysts or catalysis ecosystems. This is possible with advanced artificial intelligence and machine learning (AI/ML) workflows tha…
  arxiv Rigoberto Advincula, Jihua Chen 2026-02-26T02:45:25Z 置信度 0.78 physics.chem-phcond-mat.mtrl-sci
• Laboratory Astrophysics and the State of Astronomy and Astrophysics
  Laboratory astrophysics and complementary theoretical calculations are the foundations of astronomy and astrophysics and will remain so into the foreseeable future. The impact of laboratory astrophysics ranges from the scientific conception stage for ground-ba…
  arxiv AAS WGLA, :, Nancy Brickhouse, John Cowan 等 2009-03-13T19:42:14Z 置信度 0.78 astro-ph.IMastro-ph.COastro-ph.EPastro-ph.GAastro-ph.HE