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Metal cation‐doped lead halide perovskite (LHP) quantum dots (QDs) with photoluminescence quantum yields (PLQYs) higher than unity, due to quantum cutting phenomena, are an important building block of the next‐generation renewable energy technologies. However, synthetic route exploration and development of the highest‐performing QDs for device applications remain challenging. In this work, Smart Dope is presented, which is a self‐driving fluidic lab (SDFL), for the accelerated synthesis space exploration and autonomous optimization of LHP QDs. Specifically, the multi‐cation doping of CsPbCl3 QDs using a one‐pot high‐temperature synthesis chemistry is reported. Smart Dope continuously synthesizes multi‐cation‐doped CsPbCl3 QDs using a high‐pressure gas‐liquid segmented flow format to enable continuous experimentation with minimal experimental noise at reaction temperatures up to 255°C. Smart Dope offers multiple functionalities, including accelerated mechanistic studies through digital twin QD synthesis modeling, closed‐loop autonomous optimization for accelerated QD synthetic route discovery, and on‐demand continuous manufacturing of high‐performing QDs. Through these developments, Smart Dope autonomously identifies the optimal synthetic route of Mn‐Yb co‐doped CsPbCl3 QDs with a PLQY of 158%, which is the highest reported value for this class of QDs to date. Smart Dope illustrates the power of SDFLs in accelerating the discovery and development of emerging advanced energy materials. [ABSTRACT FROM AUTHOR]

Photostability of colloidal quantum dots (QDs) is one of the major criteria determining their long‐term applicability in energy and chemical technologies. Yet, photostability studies of QDs are extremely sensitive to experimental conditions, lack a detailed mechanistic understanding, and are time‐, material‐, and labor‐intensive. Herein, an automated microfluidic platform for accelerated photostability studies of colloidal QDs is introduced, 3.5× faster and 100× more material efficient than the conventional flask‐based studies. The developed microfluidic strategy provides real‐time in situ access to the optical properties of QDs throughout the photostability experiments. Specifically, the material‐efficient microfluidic platform is used to study the mechanism and kinetics of CdSe QDs' photodegradation. The studies suggest that a generation of singlet oxygen via triplet energy transfer from colloidal CdSe QDs can initiate photo‐oxidation of CdSe QDs. Furthermore, the presence of at least one additional photodegradation pathway of CdSe QDs parallel to the photo‐oxidation pathway is unveiled. The systematic photostability experiments reveal how the incident photon flux and the starting average diameters of CdSe QDs affect their photodegradation rates. This work sheds light on the complex and multifaceted photodegradation phenomena of colloidal CdSe QDs and illustrates the unique characteristics of microfluidic strategies to improve and accelerate photostability studies of QDs. [ABSTRACT FROM AUTHOR]

The urgency of finding solutions to global energy, sustainability, and healthcare challenges has motivated rethinking of the conventional chemistry and material science workflows. Self‐driving labs, emerged through integration of disruptive physical and digital technologies, including robotics, additive manufacturing, reaction miniaturization, and artificial intelligence, have the potential to accelerate the pace of materials and molecular discovery by 10–100X. Using autonomous robotic experimentation workflows, self‐driving labs enable access to a larger part of the chemical universe and reduce the time‐to‐solution through an iterative hypothesis formulation, intelligent experiment selection, and automated testing. By providing a data‐centric abstraction to the accelerated discovery cycle, in this perspective article, the required hardware and software technological infrastructure to unlock the true potential of self‐driving labs is discussed. In particular, process intensification as an accelerator mechanism for reaction modules of self‐driving labs and digitalization strategies to further accelerate the discovery cycle in chemical and materials sciences are discussed. [ABSTRACT FROM AUTHOR]

Development and scalable nanomanufacturing of high‐quality heavy metal‐free quantum dots (QDs) with high‐dimensional experimental design spaces still remain a challenge. In this work, a universal flow chemistry framework for accelerated fundamental and applied studies of heavy metal‐free QDs with multi‐stage chemistries is presented. By introducing flexible time‐ and temperature‐to‐distance transformation using modular fluidic blocks, an in‐flow synthetic route of InP QDs with the highest reported first excitonic absorption peak to valley ratio is unveiled with a reaction time one order of magnitude faster than batch reactors. The flexible time‐ and temperature‐to‐distance transformation as an enabling factor for generalization of flow reactors toward the accelerated discovery, development, and nanomanufacturing of high‐quality emerging nanomaterials for next‐generation energy, display, and chemical technologies is discussed. [ABSTRACT FROM AUTHOR]

A generalizable and versatile microfluidic approach for facile synthesis of a wide range of metal oxide microparticles using atypical metal‐organic precursors is reported. Microparticles of three single oxide materials, zinc(II) oxide, tin(IV) oxide, and cerium(IV) oxide, as well as a binary rare earth mixed oxide, lanthanum(III) praseodymium(III) oxide, are synthesized in flow. The tin(IV) oxide is shown to vary in composition from 14.2 % to 0 % orthorhombic phase at annealing temperatures ranging from 500 °C to 900 °C, while the lanthanum(III) praseodymium(III) oxide forms at a relatively low temperature of ∼700 °C. [ABSTRACT FROM AUTHOR]

Despite the potential of hydrogen (H2) storage in liquid organic carriers to achieve carbon neutrality, the energy required for H2 release and the cost of catalyst recycling have hindered its large‐scale adoption. In response, a photo flow reactor packed with rhodium (Rh)/titania (TiO2) photocatalyst was reported for the continuous and selective acceptorless dehydrogenation of 1,2,3,4‐tetrahydroquinoline to H2 gas and quinoline under visible light irradiation at room temperature. The tradeoff between the reactor pressure drop and its photocatalytic surface area was resolved by selective in‐situ photodeposition of Rh in the photo flow reactor post‐packing on the outer surface of the TiO2 microparticles available to photon flux, thereby reducing the optimal Rh loading by 10 times compared to a batch reactor, while facilitating catalyst reuse and regeneration. An example of using quinoline as a hydrogen acceptor to lower the energy of the hydrogen production step was demonstrated via the water‐gas shift reaction. [ABSTRACT FROM AUTHOR]

Lead halide perovskite (LHP) nanocrystals (NCs) are considered an emerging class of advanced functional materials with numerous outstanding optoelectronic characteristics. Despite their success in the field, their precision synthesis and fundamental mechanistic studies remain a challenge. The vast colloidal synthesis and processing parameters of LHP NCs in combination with the batch‐to‐batch and lab‐to‐lab variation problems further complicate their progress. In response, a self‐driving fluidic micro‐processor is presented for accelerated navigation through the complex synthesis and processing parameter space of NCs with multistage chemistries. The capability of the developed autonomous experimentation strategy is demonstrated for a time‐, material‐, and labor‐efficient search through the sequential halide exchange and cation doping reactions of LHP NCs. Next, a machine learning model of the modular fluidic micro‐processors is autonomously built for accelerated fundamental studies of the in‐flow metal cation doping of LHP NCs. The surrogate model of the sequential halide exchange and cation doping reactions of LHP NCs is then utilized for five closed‐loop synthesis campaigns with different target NC doping levels. The precise and intelligent NC synthesis and processing strategy, presented herein, can be further applied toward the autonomous discovery and development of novel impurity‐doped NCs with applications in next‐generation energy technologies. [ABSTRACT FROM AUTHOR]

Despite the groundbreaking advancements in the synthesis of inorganic lead halide perovskite (LHP) nanocrystals (NCs), stimulated from their intriguing size‐, composition‐, and morphology‐dependent optical and optoelectronic properties, their formation mechanism through the hot‐injection (HI) synthetic route is not well‐understood. In this work, for the first time, in‐flow HI synthesis of cesium lead iodide (CsPbI3) NCs is introduced and a comprehensive understanding of the interdependent competing reaction parameters controlling the NC morphology (nanocube vs nanoplatelet) and properties is provided. Utilizing the developed flow synthesis strategy, a change in the CsPbI3 NC formation mechanism at temperatures higher than 150 °C, resulting in different CsPbI3 morphologies is revealed. Through comparison of the flow‐ versus flask‐based synthesis, deficiencies of batch reactors in reproducible and scalable synthesis of CsPbI3 NCs with fast formation kinetics are demonstrated. The developed modular flow chemistry route provides a new frontier for high‐temperature studies of solution‐processed LHP NCs and enables their consistent and reliable continuous nanomanufacturing for next‐generation energy technologies. [ABSTRACT FROM AUTHOR]

Autonomous experimentation and chemical discovery strategies are rapidly rising across multiple fields of science. However, closed-loop material development approaches have not been widely employed in colloidal nanoscience mainly due to the challenges in synthesis space size, sensitivity to reaction conditions, and the complexity of monitoring multiple synthesis outputs. Recent advancements in automated reactor designs for controlled and reproducible nanocrystal synthesis and intelligent experiment selection algorithms are leading to wider propagation of artificial intelligence-guided autonomous experimentation techniques in colloidal nanoscience. This review will cover the current literature on closed-loop, autonomous platforms for accelerated development of colloidal nanomaterials and discuss the critical features and strategies for developing autonomous robotic experimentation systems suitable to problems in colloidal nanoscience, while providing the context, effectiveness, and prospects of each technique. Then, we will discuss some immediate opportunities in the field for more rapid technological advancement and colloidal nanomaterial discovery. [ABSTRACT FROM AUTHOR]

We present an integrated flow chemistry strategy using two membrane-based flow reactors to enhance the extraction and recovery rates of switchable hydrophilicity solvents (SHSs) by five times compared to batch reactors. The developed green flow chemistry strategy achieves an overall single-pass recovery efficiency of 60.1% for 2-(dibutyl amino)ethanol. [ABSTRACT FROM AUTHOR]

Green solvent utilization and recovery enabled by switchable hydrophilicity solvents (SHSs), using carbon dioxide as the switching trigger, offer intriguing advantages in sustainable chemistry. To further elevate SHSs, an intensified continuous flow strategy is presented, providing an accurate in situ reaction monitoring and a scalable green solvent extraction route. [ABSTRACT FROM AUTHOR]

Identifying the optimal formulation of emerging inorganic lead halide perovskite quantum dots (LHP QDs) with their vast colloidal synthesis universe and multiple synthesis/postsynthesis processing parameters is a challenging undertaking for material‐ and time‐intensive, batch synthesis strategies. Herein, a modular microfluidic synthesis strategy, integrated with an artificial intelligence (AI)‐guided decision‐making agent for intelligent navigation through the complex colloidal synthesis universe of LHP QDs with 10 individually controlled synthesis parameters and an accessible parameter space exceeding 2 × 107, is introduced. Utilizing the developed autonomous microfluidic experimentation strategy within a global learning framework, the optimal formulation of LHP QDs is rapidly identified through a two‐step colloidal synthesis and postsynthesis halide exchange reaction, for 10 different emission colors in less than 40 min per desired peak emission energy. Using two in‐series microfluidic reactors enables continuous bandgap engineering of LHP QDs via in‐line halide exchange reactions without the need for an intermediate washing step. Using an inert gas within a three‐phase flow format enables successful, self‐synchronized continuous delivery of halide salt precursor into moving droplets containing LHP QDs, resulting in accelerated closed‐loop formulation optimization and end‐to‐end continuous manufacturing of LHP QDs with desired optoelectronic properties. [ABSTRACT FROM AUTHOR]

Over the past decade, continuous flow reactors have emerged as a powerful tool for accelerated fundamental and applied studies of gas–liquid reactions, offering facile gas delivery and process intensification. In particular, unique features of highly gas-permeable tubular membranes in flow reactors (i.e., tube-in-tube flow reactor configuration) have been exploited as (i) an efficient analytic tool for gas–liquid solubility and diffusivity measurements and (ii) reliable gas delivery/generation strategy, providing versatile adaptability for a wide range of gas–liquid processes. The tube-in-tube flow reactors have been successfully adopted for rapid exploration of a wide range of gas–liquid reactions (e.g., amination, carboxylation, carbonylation, hydrogenation, ethylenation, oxygenation) using gaseous species both as the reactant and the product, safely handling toxic and flammable gases or unstable intermediate compounds. In this highlight, we present an overview of recent developments in the utilization of such intensified flow reactors within modular flow chemistry platforms for different gas–liquid processes involving carbon dioxide, oxygen, and other gases. We provide a detailed step-by-step guideline for robust assembly and safe operation of tube-in-tube flow reactors. We also discuss the current challenges and potential future directions for further development and utilization of tubular membrane-based flow reactors for gas–liquid processes. [ABSTRACT FROM AUTHOR]

Developing light‐harvesting materials with tunable emission colors is highly desirable in applications requiring a specific color on‐demand. The modulation in material composition, structures, and polymerization can provide a useful tool for producing a wide range of emission colors. However, controlling the color gamut in a ready‐made material remains a formidable challenge. Here, several germinate‐based phosphors are reported that provide precise dynamic emission color tuning in the visible color range through the optical multiplexing of lanthanides and other ion dopants, such as lead (Pb2+) and manganese (Mn2+). The emission gamut of the developed germinate‐based materials in the full visible color range can be tuned on demand by adjusting the excitation wavelength, thereby allowing dynamic synergistic multicolor, multitemporal, and multimodal integration with ready‐made materials. The multicolored photoluminescence property of the developed phosphors is related to the different interaction modes of dopants in the crystals. Furthermore, the applications of color‐tunable phosphors in multicolor display and anticounterfeiting are demonstrated. These findings provide valuable insights toward developing next‐generation smart luminescent materials and sensors. [ABSTRACT FROM AUTHOR]

Opportunities for accessible microfluidic device integration have sharply grown with the rise of readily available lab-in-a-tube strategies. Herein, we present a facile, non-invasive, plug-and-play phase velocity and length measuring strategy for rapid deployment onto tube-based microfluidic systems, enabling quick and accurate residence (reaction) time measurement and tuning. Our approach utilizes inexpensive off-the-shelf optical phase sensors and requires no prior knowledge of the fluid composition or physical properties. Compared to camera-based measurements in fluoropolymer tubing, the optical phase sensor-based technique shows mean absolute percentage errors of 1.3% for velocity and 3.3% for length. Utilizing the developed multiphase flow monitoring technique, we screen the accessible parameter space of gas–liquid segmented flows. To further demonstrate the functionality of this process monitoring strategy, we implement two feedback controllers to establish simultaneous setpoint control for phase velocity and length. Next, to showcase the effectiveness and versatility of the developed multiphase flow process controller, we apply it to systematic studies of the effect of liquid slug velocity (controlling precursor mixing timescale) on the colloidal synthesis of cesium lead tribromide nanocrystals. By varying the liquid slug velocity and maintaining constant precursor composition, liquid slug length, and residence time, we observe a bandgap tunability from 2.43 eV (510 nm) to 2.52 eV (494 nm). [ABSTRACT FROM AUTHOR]