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One of the recently observed effects of plasma in medical applications is the physical effect, suggesting that the electromagnetic (EM) emission of cold atmospheric plasmas can lead to cell membrane oscillations and sensitization to the chemical active ingredient of treatments such as cancer drugs. This is a new aspect that must be considered along with the plasma chemical effects for the future dose definition which is the most urgent research topic of plasma medicine. However, unlike the reactive oxygen and nitrogen species generated from plasma chemistry which is well-known as playing a key role in apoptosis cancer cells, the EM emission power spectrum and emission mechanism are still unquantified. This makes the uncertainty of the physical dosage of the therapy and thus impedes the further understanding and optimization of the plasma therapy. In this paper, we compute the 3D spatial distribution of the power density spectrum of EM emission from a cold atmospheric helium plasma jet. The simulations indicate that the plasma oscillations following the plasma streamer propagation are the main source of EM emission, while the emissions of the bulk current caused by net charge movements and the bremsstrahlung due to charge collisions are negligible. The results are also verified by a microwave power measurement using a heterodyne frequency sweep. These findings will thus fill out the last missing piece of the jigsaw before the plasma medicine community can define the dose in the future.

 

Given the increasing prevalence of droughts, unpredictable rainfall patterns, and limited access to dependable water sources in the United States and worldwide, it has become crucial to implement effective irrigation scheduling strategies. Irrigation is triggered when some variables, such as soil moisture or accumulated water deficit, exceed a given threshold in the most common approaches applied in irrigation scheduling. A High-Resolution Land Data Assimilation System (HRLDAS) was used in this study to generate timely and accurate soil moisture and evapotranspiration (ET) data for irrigation management. By integrating HRLDAS products and the crop growth model (AquaCrop), an automated data-driven irrigation scheduling approach was developed and evaluated. For HRLDAS ET and soil moisture, the ET-water balance (ET-WB)-based method and soil-moisture-based method were applied accordingly. The ET-WB-based method showed a 10.6~33.5% water-saving result in dry and set seasons, whereas the soil moisture-based method saved 7.2~37.4% of irrigation water in different weather conditions. Both of these methods demonstrated good results in saving water (with a varying range of 10~40%) without harming crop yield. The optimized thresholds in the two approaches were partially consistent with the default values from the Food and Agriculture Organization and showed a similar trend in the growing season. Furthermore, the forecasted rainfall was integrated into this model to see its water-saving effect. The results showed that an additional 10% of irrigation water, which is 20~50%, can be saved without harming the crop yield. This study automated the data-driven approach for irrigation scheduling by taking advantage of HRLDAS products, which can be generated in a near-real-time manner. The results indicated the great potential of this automated approach for saving water and irrigation decision making.

 

As the demand for PET plastic products continues to grow, developing effective processes to reduce their pollution is of critical importance. Pyrolysis, a promising technology to produce lighter and recyclable components from wasted plastic products, has therefore received considerable attention. In this work, the rapid pyrolysis of PET was studied by using reactive molecular dynamics (MD) simulations. Mechanisms for yielding gas species were unraveled, which involve the generation of ethylene and TPA radicals from ester oxygen−alkyl carbon bond dissociation and condensation reactions to consume TPA radicals with the products of long chains containing a phenyl benzoate structure and CO2. As atomistic simulations are typically conducted at the time scale of a few nanoseconds, a high temperature (i.e. >1000 K) is adopted for accelerated reaction events. To apply the results from MD simulations to practical pyrolysis processes, a kinetic model based on a set of ordinary differential equations was established, which is capable of describing the key products of PET pyrolysis as a function of time and temperature. It was further exploited to determine the optimal reaction conditions for low environmental impact. Overall, this study conducted a detailed mechanism study of PET pyrolysis and established an effective kinetic model for the main species. The approach presented herein to extract kinetic information such as detailed kinetic constants and activation energies from atomistic MD simulations can also be applied to related systems such as the pyrolysis of other polymers.