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fsdl  (Edinburgh Instruments)

 
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    Edinburgh Instruments fsdl
    (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off <t>intervals.</t> <t>FSDL’s</t> PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.
    Fsdl, supplied by Edinburgh Instruments, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/fsdl/pmc12746153-28-33-46?v=Edinburgh+Instruments
    Average 86 stars, based on 1 article reviews
    fsdl - by Bioz Stars, 2026-08
    86/100 stars

    Images

    1) Product Images from "Programmable Light-Driven Color Tuning of Perovskite Quantum Dots"

    Article Title: Programmable Light-Driven Color Tuning of Perovskite Quantum Dots

    Journal: ACS Central Science

    doi: 10.1021/acscentsci.5c01651

    (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off intervals. FSDL’s PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.
    Figure Legend Snippet: (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off intervals. FSDL’s PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.

    Techniques Used: Sampling

    Schematic overview of the closed-loop autonomous experimentation framework for programmable synthesis of high-performing MHP NCs via PIAERs. The multiobjective BO loop is initiated by an LHS strategy to generate a diverse and unbiased set of initial experiments for training the surrogate ML model. These experiments are executed using a single-droplet microfluidic photoreactor. In situ optical characterization captures the resulting UV/vis absorption and PL spectra, from which key photophysical metrics are extracted via automated data processing. The surrogate ML model, based on Gaussian Process regression (GPR), is then retrained with the newly acquired data, updating its predictions and uncertainty estimates over the high-dimensional parameter space. Sampling strategies guided by acquisition functions (e.g., Expected Hypervolume Improvement) are used to explore the updated surrogate landscape and identify promising regions near the Pareto front. A decision policy selects the next experiment by balancing exploration and exploitation, leading to the generation of new input conditions that are passed to the FSDL’s hardware for execution. This iterative loop continues until convergence on optimal PIAER conditions for targeted optical outputs, enabling on-demand, material-efficient synthesis of compositionally tuned MHP NCs.
    Figure Legend Snippet: Schematic overview of the closed-loop autonomous experimentation framework for programmable synthesis of high-performing MHP NCs via PIAERs. The multiobjective BO loop is initiated by an LHS strategy to generate a diverse and unbiased set of initial experiments for training the surrogate ML model. These experiments are executed using a single-droplet microfluidic photoreactor. In situ optical characterization captures the resulting UV/vis absorption and PL spectra, from which key photophysical metrics are extracted via automated data processing. The surrogate ML model, based on Gaussian Process regression (GPR), is then retrained with the newly acquired data, updating its predictions and uncertainty estimates over the high-dimensional parameter space. Sampling strategies guided by acquisition functions (e.g., Expected Hypervolume Improvement) are used to explore the updated surrogate landscape and identify promising regions near the Pareto front. A decision policy selects the next experiment by balancing exploration and exploitation, leading to the generation of new input conditions that are passed to the FSDL’s hardware for execution. This iterative loop continues until convergence on optimal PIAER conditions for targeted optical outputs, enabling on-demand, material-efficient synthesis of compositionally tuned MHP NCs.

    Techniques Used: In Situ, Sampling



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    (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off <t>intervals.</t> <t>FSDL’s</t> PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.
    Fsdl, supplied by Edinburgh Instruments, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/fsdl/pmc12746153-28-33-46?v=Edinburgh+Instruments
    Average 86 stars, based on 1 article reviews
    fsdl - by Bioz Stars, 2026-08
    86/100 stars
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    (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off <t>intervals.</t> <t>FSDL’s</t> PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.
    Fsdl Biotin, supplied by BioSurface Technologies Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Image Search Results


    (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off intervals. FSDL’s PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.

    Journal: ACS Central Science

    Article Title: Programmable Light-Driven Color Tuning of Perovskite Quantum Dots

    doi: 10.1021/acscentsci.5c01651

    Figure Lengend Snippet: (A,B) Time-resolved evolution of λ em during UV-on and UV-off experiments for blue- and red-shifts, respectively. The gray-shaded regions represent UV-off intervals. FSDL’s PIAER reproducibility study with random sampling experiments for (C, blue) chloride- (D, red) and iodide-exchange reactions. Each plot shows fwhm, P PLQY , and λ em across 10 experiments with 5 repeats of the same baseline (black data points) and randomly selected (blue and red data points) PIAER conditions. Black dashed lines indicate the mean values across baseline condition replicates. Experimental conditions (baseline): [CsPbBr 3 ] = 4.2 μM; [DCM] = 4.1 M; [1-iodopropane] = 0.24 M; photon flux = 15 pmol s –1 (DCM) and 55 pmol s –1 (1-iodopropane); residence time = 2.0 min; T = 23 °C.

    Article Snippet: This normalization corrects for variations in NCs concentration and excitation efficiency, ensuring that the metric reflects the fraction of absorbed photons re-emitted rather than raw PL I . , , We validated the FSDL’s in situ characterization module by benchmarking it against conventional benchtop spectroscopy (FS5, Edinburgh Instruments).

    Techniques: Sampling

    Schematic overview of the closed-loop autonomous experimentation framework for programmable synthesis of high-performing MHP NCs via PIAERs. The multiobjective BO loop is initiated by an LHS strategy to generate a diverse and unbiased set of initial experiments for training the surrogate ML model. These experiments are executed using a single-droplet microfluidic photoreactor. In situ optical characterization captures the resulting UV/vis absorption and PL spectra, from which key photophysical metrics are extracted via automated data processing. The surrogate ML model, based on Gaussian Process regression (GPR), is then retrained with the newly acquired data, updating its predictions and uncertainty estimates over the high-dimensional parameter space. Sampling strategies guided by acquisition functions (e.g., Expected Hypervolume Improvement) are used to explore the updated surrogate landscape and identify promising regions near the Pareto front. A decision policy selects the next experiment by balancing exploration and exploitation, leading to the generation of new input conditions that are passed to the FSDL’s hardware for execution. This iterative loop continues until convergence on optimal PIAER conditions for targeted optical outputs, enabling on-demand, material-efficient synthesis of compositionally tuned MHP NCs.

    Journal: ACS Central Science

    Article Title: Programmable Light-Driven Color Tuning of Perovskite Quantum Dots

    doi: 10.1021/acscentsci.5c01651

    Figure Lengend Snippet: Schematic overview of the closed-loop autonomous experimentation framework for programmable synthesis of high-performing MHP NCs via PIAERs. The multiobjective BO loop is initiated by an LHS strategy to generate a diverse and unbiased set of initial experiments for training the surrogate ML model. These experiments are executed using a single-droplet microfluidic photoreactor. In situ optical characterization captures the resulting UV/vis absorption and PL spectra, from which key photophysical metrics are extracted via automated data processing. The surrogate ML model, based on Gaussian Process regression (GPR), is then retrained with the newly acquired data, updating its predictions and uncertainty estimates over the high-dimensional parameter space. Sampling strategies guided by acquisition functions (e.g., Expected Hypervolume Improvement) are used to explore the updated surrogate landscape and identify promising regions near the Pareto front. A decision policy selects the next experiment by balancing exploration and exploitation, leading to the generation of new input conditions that are passed to the FSDL’s hardware for execution. This iterative loop continues until convergence on optimal PIAER conditions for targeted optical outputs, enabling on-demand, material-efficient synthesis of compositionally tuned MHP NCs.

    Article Snippet: This normalization corrects for variations in NCs concentration and excitation efficiency, ensuring that the metric reflects the fraction of absorbed photons re-emitted rather than raw PL I . , , We validated the FSDL’s in situ characterization module by benchmarking it against conventional benchtop spectroscopy (FS5, Edinburgh Instruments).

    Techniques: In Situ, Sampling