Efficient ¹³C hyperpolarization of ketoisocaproate is demonstrated in natural isotopic abundance and [1-¹³C]enriched forms via SABRE-SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei). Parahydrogen, as the source of nuclear spin order, and ketoisocaproate undergo simultaneous chemical exchange with an Ir-IMes-based hexacoordinate complex in CD₃OD. SABRE-SHEATH enables spontaneous polarization transfer from parahydrogen-derived hydrides to the ¹³C nucleus of transiently bound ketoisocaproate. ¹³C polarization values of up to 18% are achieved at the 1-¹³C site in 1 min in the liquid state at 30 mM substrate concentration. The efficient polarization build-up becomes possible due to favorable relaxation dynamics. Specifically, the exponential build-up time constant (14.3 ± 0.6 s) is substantially lower than the corresponding polarization decay time constant (22.8 ± 1.2 s) at the optimum polarization transfer field (0.4 microtesla) and temperature (10 °C). The experiments with natural abundance ketoisocaproate revealed polarization level on the ¹³C-2 site of less than 1%—i.e., one order of magnitude lower than that of the 1-¹³C site—which is only partially due to more-efficient relaxation dynamics in sub-microtesla fields. We rationalize the overall much lower ¹³C-2 polarization efficiency in part by less favorable catalyst-binding dynamics of the C-2 site. Pilot SABRE experiments at pH 4.0 (acidified sample) versus pH 6.1 (unaltered sodium [1-¹³C]ketoisocaproate) reveal substantial modulation of SABRE-SHEATH processes by pH, warranting future systematic pH titration studies of ketoisocaproate, as well as other structurally similar ketocarboxylate motifs including pyruvate and alpha-ketoglutarate, with the overarching goal of maximizing ¹³C polarization levels in these potent molecular probes. Finally, we also report on the pilot post-mortem use of HP [1-¹³C]ketoisocaproate in a euthanized mouse, demonstrating that SABRE-hyperpolarized ¹³C contrast agents hold promise for future metabolic studies.

The global use of IoT-enabled devices powered by renewable energy can create a smart, efficient, and eco-friendly network. By leveraging data analytics and machine learning, these systems can predict energy consumption, optimize resources, and maintain renewable energy assets proactively. IoT device adoption is rapidly increasing, with a projected 13% growth in 2024, bringing the total to 18.8 billion devices globally. However, there is a critical need for advanced applications of IoT technology, improved sensors implementation, and up-to-date software development to control IoT devices which is essential to fully harness renewable energy and combat global warming, ultimately achieving the vision of a smart green planet. This review examines the operational and technical needs of IoT devices, their integration with various renewable energy sources using Raspberry Pi or Arduino platforms equipped with sensors (such as motion, vibration, flow, and gyroscope), and the application of machine learning in IoT devices to showcase the potential of these technologies in fostering a smart, green world. To further this investigation, the study thoroughly examined the pros and cons of integrating various renewable energy sources to develop smart systems, such as smart grids, smart cities, smart transportation, and smart waste collection. Additionally, this study also examines the challenges faced by smart IoT systems, providing critical analysis and identifying promising directions for future advancements.

Hyperpolarization (HP) techniques, such as Parahydrogen-Induced Polarization (PHIP), Signal Amplification by Reversible Exchange (SABRE), and dissolution Dynamic Nuclear Polarization (d-DNP), significantly enhance the sensitivity of nuclear magnetic resonance (NMR) spectroscopy for chemical analysis and metabolic imaging. However, the high cost of equipment, ranging from tens of thousands to millions of dollars, limits accessibility of hyperpolarization for the broad scientific community. In this work, we aim to mitigate some of the challenges by developing a cost-effective solution for parahydrogen (pH₂)-based PHIP and SABRE HP methods. A custom coil-winding machine was designed to fabricate solenoid magnet coils, which were then evaluated for their magnetic field profiles, demonstrating a high degree of magnetic field homogeneity. A model ¹H SABRE experiment successfully implemented the constructed solenoid, achieving efficient hyperpolarization. Additionally, the solenoid magnet can be utilized for in situ detection of hyperpolarization when integrated with a low-field NMR spectrometer, reducing the total setup cost to a few thousand dollars. These findings suggest that our approach makes HP technology more affordable and accessible, potentially broadening its applications in chemical and biomedical research, as well as educational settings involving undergraduate student researchers. This work provides a practical pathway to lower the financial barriers associated with pH₂ HP setups.

Microextraction technique (e.g., solid phase microextraction, thin film microextraction, in-tube extraction) brings a revolutionary change in air sampling techniques over the recent few years. This advanced technique exhibits a high pollutant extraction rate, a low retention time, and a lower error margin compared to conventional air sampling techniques. The accuracy range of microextraction technique (MET) was recorded ~90-95% to isolate the volatile organic components, oxygenated and halogenated carbon particles from the air. However, the efficiency of MET increases additional >3-5% when employed by coupled with gas chromatography or gas chromatography-mass spectrometry. The conventional sampling techniques (e.g., bag sampling, grab sampling) on the other hand, displayed the accuracy of ~75- 80% which is ~20% lower than MET. The factors that potentially affect the performance of both conventional and MET were thoroughly investigated in this study. For instance, it was observed that the quality of needle coating used in MET significantly affects the pollutant trapping and at least ~5% of total performance cut off due to damaged and corroded coating. In addition, smart sensor-based air sampling techniques are also being investigated as this technique is a recent development in air quality monitoring. This fully automated state-of-the-art technology shows more than 98% accuracy with significantly high sensitivity and pollutant extraction rate. Finally, this investigation distinguishes the potential advantages, disadvantages, and challenges to increase accuracy between advanced and conventional sampling techniques, drawing attention to the urgent need to improve the performance of the air sampling techniques investigated in this study.

Precise and accurate charge measurements on microdroplets are essential for understanding the role of charge in modulating microdroplet chemistry, including reaction kinetics, ion distribution, and interfacial dynamics. Despite the availability of various charge measurement techniques, existing contactless techniques either lack the sensitivity to accurately detect charges with ∼1 fC precision or lack the ability to measure charge on micron-sized particles, leaving a significant gap in the field. Here, a new technique is presented to directly measure the net charge of microdroplets exiting a quadrupole electrodynamic trap (QET) using induced charge detection. With this method, the charge droplets induce on a cylindrical electrode (Qinduced) is detected using a homebuilt charge sensitive pre-amplifier (CSP). The long time constant of the CSP (1.02 ± 0.01 s−1) facilitates accurate measurement of Qinduced on slow-moving microdroplets that interact with the detection electrode for up to 100s of ms. The new charge detection method is validated by comparing Qinduced with the charge of droplets measured using a Faraday cup (QFaraday cup) for roughly 2900 droplets with different net charges, sizes, and velocities. Regardless of droplet properties, Qinduced closely correlates with QFaraday cup with absolute differences averaging <5 fC (i.e., 1% accuracy). While the charge detection system is coupled to a QET, it could easily be adapted for other droplet-based measurements (e.g., droplet train experiments). Ultimately, the induced charge detection system presented here will support future studies exploring how charge influences the physical and chemical processing of microdroplets, such as understanding how charge can drive accelerated chemistry in microdroplets.

Microextraction technique (e.g., solid phase microextraction, thin film microextraction, in-tube extraction) brings a revolutionary change in air sampling techniques over the recent few years. This advanced technique exhibits a high pollutant extraction rate, a low retention time, and a lower error margin compared to conventional air sampling techniques. The accuracy range of microextraction technique (MET) was recorded ~90-95% to isolate the volatile organic components, oxygenated and halogenated carbon particles from the air. However, the efficiency of MET increases additional >3-5% when employed by coupled with gas chromatography or gas chromatography-mass spectrometry. The conventional sampling techniques (e.g., bag sampling, grab sampling) on the other hand, displayed the accuracy of ~75- 80% which is ~20% lower than MET. The factors that potentially affect the performance of both conventional and MET were thoroughly investigated in this study. For instance, it was observed that the quality of needle coating used in MET significantly affects the pollutant trapping and at least ~5% of total performance cut off due to damaged and corroded coating. In addition, smart sensor-based air sampling techniques are also being investigated as this technique is a recent development in air quality monitoring. This fully automated state-of-the-art technology shows more than 98% accuracy with significantly high sensitivity and pollutant extraction rate. Finally, this investigation distinguishes the potential advantages, disadvantages, and challenges to increase accuracy between advanced and conventional sampling techniques, drawing attention to the urgent need to improve the performance of the air sampling techniques investigated in this study.