Monte Carlo sampling for stochastic weight functions

Real-Time Monitoring and Rapid Determination of Pork Freshness Using a Colorimetric Sensor Array Based on Porphyrin and pH Indicator Ligand Combination

This study presents the development of a colorimetric sensor array (CSA) that combines pH indicators with porphyrin solutions to create a sensitive and stable sensor for monitoring pork freshness. Four pH indicators─bromophenol blue, bromocresol green, bromocresol violet, and chlorophenol red─were chosen for their ability to detect volatile gases produced during pork spoilage. Color changes were quantified by extracting grayscale values, and various porphyrins, including TPPNi, TPPMnCl, and TPPCu, were screened for their interactions with the pH indicators. Principal component analysis was used to determine the optimal concentration of the porphyrin solution. The CSA was then constructed by combining the four pH indicators with the selected porphyrins, resulting in an average stability improvement of 21.94%, 23.59%, 28.84%, and 23.31%, respectively. The occurrence of coordination is verified by Fourier transform infrared (FTIR), and theoretical calculations are applied to explain the possible reasons for the increased stability. The CSA was tested on pork samples stored for different periods, and a partial least squares regression model was built using grayscale data to predict freshness. Furthermore, storage experiments were conducted to evaluate the CSA's stability over 3, 7, and 15 days, and the retention of color in CSA was 99.02%, 99.01%, and 98.84%, respectively. The models achieved 98.89% average accuracy (n = 30 samples) in predicting the freshness grades of pork samples from different batches and in assessing the stability of the CSA, demonstrating its potential as a reliable tool for rapid and accurate pork freshness discrimination.

Effect of Catalyst Inlet Flow Field Distribution Characteristics on Outlet NO Concentration Distribution in SCR Denitration Reactor Based on Monte Carlo Method

Selective catalytic reduction (SCR) technology plays a crucial role in flue gas denitration. The nonuniform distribution of catalyst inlet parameters causes the nonuniform distribution of NO concentration at the outlet, thus affecting accuracy of ammonia injection. Regarding this issue, this paper describes the impacts of nonuniform velocity and temperature on both the confidence of NO concentration measured at a single measuring point at the outlet and the denitration efficiency, which can provide a basis for structural optimization of SCR denitration reactor and decrease in ammonia slip. The random distribution form of velocity and temperature above the catalyst layer are derived from the actual gas volume and the actual SCR reactor model, and then the catalyst inlet boundary conditions were generated with different relative standard deviation of velocity and temperature accordingly. The confidence of outlet NO concentration measurement results can be counted by means of Monte Carlo simulation. Finally, the relation model can be obtained to calculate the confidence of outlet NO concentration measurement results at different working conditions. The results show that within the gas volume range of this work, in order to ensure the confidence of the NO concentration measurement results, the relative standard deviation of temperature before the catalyst inlet must be within 0.005 and the relative standard deviation of velocity before the catalyst inlet must be within 0.1. With the increase in relative standard difference in temperature, there is a slight decrease in the efficiency of denitration. With the different mean value of temperature, the variation range of denitration efficiency is similar to that of temperature-relative standard difference. With the different mean value of velocity, the deviation range of corresponding efficiency is similar to that of the temperature-relative standard difference. When the relative standard difference in velocity increases, the denitration efficiency decreases slightly. The greater velocity value, the decreasing range of denitration efficiency is larger than the variation range of relative standard difference in velocity.

Numerical method for computing the free energy of glasses

We propose a numerical technique to compute the equilibrium free energy of glasses that cannot be prepared quasireversibly. For such systems, standard techniques for estimating the free energy by extrapolation cannot be used. Instead, we use a procedure that samples the equilibrium partition function of the basins of attraction of the different inherent structures (local potential energy minima) of the system. If all relevant inherent structures could be adequately sampled in the (supercooled) liquid phase, our approach would be rigorous. In any finite simulation, we will miss the lower-energy inherent structures that become dominant at very low temperatures. We find that our free energy estimates for a Kob-Andersen glass are lower than those obtained by very slow cooling, even at temperatures down to one-third of the glass transition temperature. The current approach could be applied to compute the chemical potential of ultrastable glassy materials and should enable the estimation of their solubility.