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Not AvailableIntegrating data science and Python programming into secondary chemistry education addresses gaps in preparing students for STEM (science, technology, engineering, and mathematics) careers, where computational and analytical skills are essential. Traditional laboratories often treat instruments as “black boxes,” restricting students’ ability to grasp basic principles. High instrumentation costs and limited access to advanced data analysis tools restrict hands-on learning. We present a cost-effective laboratory module combining a do-it-yourself (DIY) spectrometer kit with data analysis using Python in Google Colaboratory (Colab). Students learn to plot data, perform least-squares fitting, calculate errors, and conduct kinetic studies, thereby developing analytical chemistry skills. These skills are applied in a problem-based learning environment to bridge introductory chemistry with quantitative analysis. Student feedback indicated a perceived improvement in understanding of instrumental components, calibration, and analytical techniques such as determining limits of linearity and dynamic range of detectors. By demystifying instruments and promoting chemical literacy and computational proficiency, this curriculum offers a model for integrating data science into secondary chemistry education. 

For carbon dots, careful purification and electronic structure calculations facilitate learning about the origin of optical properties. 

Over the past decade, the proliferation of pulsed laser sources with high repetition rates has facilitated a merger of ultrafast time-resolved spectroscopy with imaging microscopy. In transient absorption microscopy (TAM), the excited-state dynamics of a system are tracked by measuring changes in the transmission of a focused probe pulse following photoexcitation of a sample. Typically, these experiments are done using a photodiode detector and lock-in amplifier synchronized with the laser and images highlighting spatial heterogeneity in the TAM signal are constructed by scanning the probe across a sample. Performing TAM by instead imaging a spatially defocused widefield probe with a multipixel camera could dramatically accelerate the acquisition of spatially resolved dynamics, yet approaches for such widefield imaging generally suffer from reduced signal-to-noise due to an incompatibility of multipixel cameras with high-frequency lock-in detection. Herein, we describe implementation of a camera capable of high-frequency lock-in detection, thereby enabling widefield TAM imaging at rates matching those of high repetition rate lasers. Transient images using a widefield probe and two separate pump pulse configurations are highlighted. In the first, a widefield probe was used to image changes in the spatial distribution of photoexcited molecules prepared by a tightly focused pump pulse, while in the second, a widefield probe detected spatial variations in photoexcited dynamics within a heterogeneous organic crystal excited by a defocused pump pulse. These results highlight the ability of high-sensitivity lock-in detection to enable widefield TAM imaging, which can be leveraged to further our understanding of excited-state dynamics and excitation transport within spatially heterogeneous systems. 

The lack of a detailed mechanistic understanding for plasmon-mediated charge transfer at metal-semiconductor interfaces severely limits the design of efficient photovoltaic and photocatalytic devices. A major remaining question is the relative contribution from indirect transfer of hot electrons generated by plasmon decay in the metal to the semiconductor compared to direct metal-to-semiconductor interfacial charge transfer. Here, we demonstrate an overall electron transfer efficiency of 44 ± 3% from gold nanorods to titanium oxide shells when excited on resonance. We prove that half of it originates from direct interfacial charge transfer mediated specifically by exciting the plasmon. We are able to distinguish between direct and indirect pathways through multimodal frequency-resolved approach measuring the homogeneous plasmon linewidth by single-particle scattering spectroscopy and time-resolved transient absorption spectroscopy with variable pump wavelengths. Our results signify that the direct plasmon-induced charge transfer pathway is a promising way to improve hot carrier extraction efficiency by circumventing metal intrinsic decay that results mainly in nonspecific heating. 

The surfaces of colloidal nanocrystals are frequently passivated with carboxylate ligands that exert significant effects on their optoelectronic properties and chemical stability. The binding geometries of these ligands are often experimentally investigated using vibrational spectroscopy, but the interpretation of the IR signal is usually not trivial. Here, using machine-learning (ML) algorithms trained on DFT data, we simulate an IR spectrum of a lead-rich PbS nanocrystal passivated with butyrate ligands. We obtain good agreement with the experimental signal and demonstrate that the observed line shape stems from a very wide range of “tilted-bridge”-type geometries and does not indicate the coexistence of “bridging” and “chelating” binding modes as has been previously assumed. This work illustrates the limitations of empirical spectrum assignment and demonstrates the effectiveness of ML-driven molecular dynamics simulations in reproducing the IR spectra of nanoscopic systems. 

Time-resolved spectroscopy of plasmonic nanoparticles is a vital technique for probing their ultrafast electron dynamics and subsequent acoustic and photothermal properties. Traditionally, these experiments are performed with spectrally broad probe beams on the ensemble level to achieve high signal amplitudes. However, the relaxation dynamics of plasmonic nanoparticles is highly dependent on their size, shape, and crystallinity. As such, the inherent heterogeneity of most nanoparticle samples can complicate efforts to build microscopic models for these dynamics solely on the basis of ensemble measurements. Although approaches for collecting time-resolved microscopy signals from individual nanoparticles at selected probe wavelengths have been demonstrated, acquiring time-resolved spectra from single objects remains challenging. Here, we demonstrate an alternate method that efficiently yields the time-resolved spectra of a single gold nanodisk in one measurement. By modulating the frequency-doubled output of a 96 MHz Ti:sapphire oscillator at 8 kHz, we are able to use a lock-in pixel-array camera to detect photoinduced changes in the transmission of a white light continuum probe derived from a photonic crystal fiber to produce broadband femtosecond transmission spectra of a single gold nanodisk. We also compare the performance of the lock-in camera for the same single nanoparticle to measurements with a single-element photodiode and find comparable sensitivities. The lock-in camera thus provides a major advantage due to its ability to multiplex spectral detection, which we utilize here to capture both the electronic dynamics and acoustic vibrations of a single gold nanodisk following ultrafast laser excitation.