@article{bateni_sadeghi_orouji_bennett_punati_stark_wang_rosko_chen_castellano_et al._2024, title={Smart Dope: A Self-Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots (Adv. Energy Mater. 1/2024)}, volume={14}, ISSN={["1614-6840"]}, DOI={10.1002/aenm.202470001}, abstractNote={Advanced Energy MaterialsVolume 14, Issue 1 2470001 Cover PictureFree Access Smart Dope: A Self-Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots (Adv. Energy Mater. 1/2024) Fazel Bateni, Fazel Bateni Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorSina Sadeghi, Sina Sadeghi Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorNegin Orouji, Negin Orouji Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorJeffrey A. Bennett, Jeffrey A. Bennett Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorVenkat S. Punati, Venkat S. Punati Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorChristine Stark, Christine Stark Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorJunyu Wang, Junyu Wang Department of Chemistry, Brown University, Providence, RI, 02912 USASearch for more papers by this authorMichael C. Rosko, Michael C. Rosko Department of Chemistry, North Carolina State University, Raleigh, NC, 27695-8204 USASearch for more papers by this authorOu Chen, Ou Chen Department of Chemistry, Brown University, Providence, RI, 02912 USASearch for more papers by this authorFelix N. Castellano, Felix N. Castellano Department of Chemistry, North Carolina State University, Raleigh, NC, 27695-8204 USASearch for more papers by this authorKristofer G. Reyes, Kristofer G. Reyes Department of Materials Design and Innovation, University at Buffalo, Buffalo, NY, 14260 USASearch for more papers by this authorMilad Abolhasani, Milad Abolhasani Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this author Fazel Bateni, Fazel Bateni Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorSina Sadeghi, Sina Sadeghi Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorNegin Orouji, Negin Orouji Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorJeffrey A. Bennett, Jeffrey A. Bennett Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorVenkat S. Punati, Venkat S. Punati Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorChristine Stark, Christine Stark Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this authorJunyu Wang, Junyu Wang Department of Chemistry, Brown University, Providence, RI, 02912 USASearch for more papers by this authorMichael C. Rosko, Michael C. Rosko Department of Chemistry, North Carolina State University, Raleigh, NC, 27695-8204 USASearch for more papers by this authorOu Chen, Ou Chen Department of Chemistry, Brown University, Providence, RI, 02912 USASearch for more papers by this authorFelix N. Castellano, Felix N. Castellano Department of Chemistry, North Carolina State University, Raleigh, NC, 27695-8204 USASearch for more papers by this authorKristofer G. Reyes, Kristofer G. Reyes Department of Materials Design and Innovation, University at Buffalo, Buffalo, NY, 14260 USASearch for more papers by this authorMilad Abolhasani, Milad Abolhasani Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, 27695-7905 USASearch for more papers by this author First published: 05 January 2024 https://doi.org/10.1002/aenm.202470001AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Graphical Abstract Self Driving Lab In article number 2302303,Milad Abolhasani and co-workers present a self-driving lab, called Smart Dope, for the fast-tracked discovery of doped quantum dots (QDs) for applications in clean energy technologies. Smart Dope utilizes machine learning-guided operation of flow reactors integrated with an in-situ characterizationmodule in a 'closed-loop' fashion to discover the best-in-class QD within one day of autonomous experiments. Volume14, Issue1January 5, 20242470001 RelatedInformation}, number={1}, journal={ADVANCED ENERGY MATERIALS}, author={Bateni, Fazel and Sadeghi, Sina and Orouji, Negin and Bennett, Jeffrey A. and Punati, Venkat S. and Stark, Christine and Wang, Junyu and Rosko, Michael C. and Chen, Ou and Castellano, Felix N. and et al.}, year={2024}, month={Jan} }
 @article{sadeghi_bateni_kim_son_bennett_orouji_punati_stark_cerra_awad_et al._2023, title={Autonomous nanomanufacturing of lead-free metal halide perovskite nanocrystals using a self-driving fluidic lab}, volume={12}, ISSN={["2040-3372"]}, DOI={10.1039/d3nr05034c}, abstractNote={We present a self-driving fluidic lab for accelerated synthesis science studies of lead-free metal halide perovskite nanocrystals.}, journal={NANOSCALE}, author={Sadeghi, Sina and Bateni, Fazel and Kim, Taekhoon and Son, Dae Yong and Bennett, Jeffrey A. and Orouji, Negin and Punati, Venkat S. and Stark, Christine and Cerra, Teagan D. and Awad, Rami and et al.}, year={2023}, month={Dec} }
 @article{bateni_sadeghi_orouji_bennett_punati_stark_wang_rosko_chen_castellano_et al._2023, title={Smart Dope: A Self-Driving Fluidic Lab for Accelerated Development of Doped Perovskite Quantum Dots}, volume={11}, ISSN={["1614-6840"]}, DOI={10.1002/aenm.202302303}, abstractNote={AbstractMetal 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.}, journal={ADVANCED ENERGY MATERIALS}, author={Bateni, Fazel and Sadeghi, Sina and Orouji, Negin and Bennett, Jeffrey A. and Punati, Venkat S. and Stark, Christine and Wang, Junyu and Rosko, Michael C. and Chen, Ou and Castellano, Felix N. and et al.}, year={2023}, month={Nov} }
 @article{bateni_epps_antami_dargis_bennett_reyes_abolhasani_2022, title={Autonomous Nanocrystal Doping by Self-Driving Fluidic Micro-Processors}, volume={4}, ISSN={["2640-4567"]}, url={https://doi.org/10.1002/aisy.202200017}, DOI={10.1002/aisy.202200017}, abstractNote={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.}, number={5}, journal={ADVANCED INTELLIGENT SYSTEMS}, publisher={Wiley}, author={Bateni, Fazel and Epps, Robert W. and Antami, Kameel and Dargis, Rokas and Bennett, Jeffery A. and Reyes, Kristofer G. and Abolhasani, Milad}, year={2022}, month={Mar} }
 @article{antami_bateni_ramezani_hauke_castellano_abolhasani_2021, title={CsPbI3 Nanocrystals Go with the Flow: From Formation Mechanism to Continuous Nanomanufacturing}, volume={11}, ISSN={["1616-3028"]}, url={https://doi.org/10.1002/adfm.202108687}, DOI={10.1002/adfm.202108687}, abstractNote={AbstractDespite 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.}, journal={ADVANCED FUNCTIONAL MATERIALS}, author={Antami, Kameel and Bateni, Fazel and Ramezani, Mahdi and Hauke, Cory E. and Castellano, Felix N. and Abolhasani, Milad}, year={2021}, month={Nov} }
 @article{bateni_epps_abdel-latif_dargis_han_volk_ramezani_cai_chen_abolhasani_2021, title={Ultrafast cation doping of perovskite quantum dots in flow}, volume={4}, ISSN={["2590-2385"]}, url={https://doi.org/10.1016/j.matt.2021.04.025}, DOI={10.1016/j.matt.2021.04.025}, abstractNote={<h2>Summary</h2> Among all-inorganic metal halide perovskite quantum dots (PQDs), cesium lead chloride (CsPbCl<sub>3</sub>) with its large band-gap energy is an excellent candidate for enhancement of PQD radiative pathways through incorporation of additional internal energy transfer within its exciton band gap. In this study, we introduce a post-synthetic chemistry for ultrafast metal cation doping of CsPbCl<sub>3</sub> QDs with a high degree of tunability, using a model transition metal impurity dopant, manganese. Due to the fast nature of the post-synthetic metal cation-doping reaction, an engineered time-to-space transformation strategy is employed to unravel the kinetics and fundamental mechanism of the doping process. Using a modular microfluidic platform equipped with a translational <i>in situ</i> absorption and photoluminescence spectroscopy probe, we propose a heterogeneous surface-doping mechanism through a vacancy-assisted metal cation migration. The developed in-flow doping strategy can open new avenues for on-demand optoelectronic properties tuning and scalable precision synthesis of high-quality metal cation-doped PQDs.}, number={7}, journal={MATTER}, publisher={Elsevier BV}, author={Bateni, Fazel and Epps, Robert W. and Abdel-latif, Kameel and Dargis, Rokas and Han, Suyong and Volk, Amanda A. and Ramezani, Mahdi and Cai, Tong and Chen, Ou and Abolhasani, Milad}, year={2021}, month={Jul}, pages={2429–2447} }
 @article{bateni_ghahremani_staser_2021, title={Electrochemical oxidative valorization of lignin by the nanostructured PbO2/MWNTs electrocatalyst in a low-energy depolymerization process}, volume={51}, ISSN={["1572-8838"]}, DOI={10.1007/s10800-020-01451-y}, number={1}, journal={JOURNAL OF APPLIED ELECTROCHEMISTRY}, author={Bateni, Fazel and Ghahremani, Raziyeh and Staser, John A.}, year={2021}, month={Jan}, pages={65–78} }
 @article{abdel-latif_epps_bateni_han_reyes_abolhasani_2021, title={Self-Driven Multistep Quantum Dot Synthesis Enabled by Autonomous Robotic Experimentation in Flow}, volume={3}, ISSN={["2640-4567"]}, url={https://doi.org/10.1002/aisy.202000245}, DOI={10.1002/aisy.202000245}, abstractNote={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.}, number={2}, journal={ADVANCED INTELLIGENT SYSTEMS}, publisher={Wiley}, author={Abdel-Latif, Kameel and Epps, Robert W. and Bateni, Fazel and Han, Suyong and Reyes, Kristofer G. and Abolhasani, Milad}, year={2021}, month={Feb} }