Crystallization of Ammonium Nitrate from Nonaqueous Solvents

Doxsee, Kenneth M.; Francis, Perry E.

doi:10.1021/ie0004500

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…In the absence of sunlight, nitric acid can be produced by the heterogeneous conversion of N 2 O 5 , formed from the reaction of NO 2 with NO 3 , by hydrated aerosols − but has a relatively high vapor pressure. As such, ammonium nitrate has been the subject of a few rather limited studies of its hydration and dehydration properties.…”

Section: Resultsmentioning

confidence: 99%

Ion-Induced Nucleationin Solution: Promotion of Solute Nucleation in Charged Levitated Droplets

et al. 2007

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We have investigated the nucleation and growth of sodium chloride in both single quiescent charged droplets and charged droplet populations that were levitated in an electrodynamic levitation trap (EDLT). In both cases, the magnitude of a droplet's net excess charge (ions(DNEC)) influenced NaCl nucleation and growth, albeit in different capacities. We have termed the phenomenon ion-induced nucleation in solution. For single quiescent levitated droplets, an increase in ions(DNEC) resulted in a significant promotion of NaCl nucleation, as determined by the number of crystals observed. For levitated droplet populations, a change in NaCl crystal habit, from regular cubic shapes to dome-shaped dendrites, was observed once a surface charge density threshold of -9 x 10(-4) e.nm(-2) was surpassed. Although promotion of NaCl nucleation was observed for droplet population experiments, this can be attributed in part to the increased rate of solvent evaporation observed for levitated droplet populations having a high net charge. Promotion of nucleation was also observed for two organic acids, 2,4,6-trihydroxyacetophenone monohydrate (THAP) and alpha-cyano-4-hydroxycinnamic acid (CHCA). These results are of direct relevance to processes that occur in both soft-ionization techniques for mass spectrometry and to a variety of industrial processes. To this end, we have demonstrated the use of ion-induced nucleation in solution to form ammonium nitrate particles from levitated droplets to be used in in vitro toxicology studies of ambient particle types.

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Section: Resultsmentioning

confidence: 99%

Ion-Induced Nucleationin Solution: Promotion of Solute Nucleation in Charged Levitated Droplets

et al. 2007

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“…Crystallization is a pivotal process in sectors such as pharmaceutical, food and beverage, and chemical production, playing a critical role in defining the quality and characteristics of a wide range of products. This process is fundamental in creating crystalline products that span a diverse array of applications, including bulk chemicals like sodium chloride and sucrose, essential in everyday life, and crucial agricultural fertilizers such as ammonium nitrate [1], potassium chloride [2], ammonium phosphates [3] and urea [4]. In the pharmaceutical industry, crystallization is vital for producing valuable products such as active pharmaceutical ingredients [5] and organic fine chemicals [6], where the purity and morphology of crystals can significantly impact drug efficacy and safety.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions

Kandaswamy,

Schwaminger

2024

Crystals

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Crystallization plays a crucial role in defining the quality and functionality of products across various industries, including pharmaceutical, food and beverage, and chemical manufacturing. The process’s efficiency and outcome are significantly influenced by solute–solvent interactions, which determine the crystalline product’s purity, size, and morphology. These attributes, in turn, impact the product’s efficacy, safety, and consumer acceptance. Traditional methods of optimizing crystallization conditions are often empirical, time-consuming, and less adaptable to complex chemical systems. This research addresses these challenges by leveraging machine learning techniques to predict and optimize solute–solvent interactions, thereby enhancing crystallization outcomes. This review provides a novel approach to understanding and controlling crystallization processes by integrating supervised, unsupervised, and reinforcement learning models. Machine learning not only improves product the quality and manufacturing efficiency but also contributes to more sustainable industrial practices by minimizing waste and energy consumption.

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Stabilization and spheroidization of ammonium nitrate: Co-crystallization with crown ethers and spherical crystallization by solvent screening

Lee

Chen

Lee

et al. 2013

Chemical Engineering Journal

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Crystallization of Ammonium Nitrate from Nonaqueous Solvents

Cited by 4 publications

References 31 publications

Ion-Induced Nucleationin Solution: Promotion of Solute Nucleation in Charged Levitated Droplets

Ion-Induced Nucleationin Solution: Promotion of Solute Nucleation in Charged Levitated Droplets

Machine Learning Methods to Improve Crystallization through the Prediction of Solute–Solvent Interactions

Stabilization and spheroidization of ammonium nitrate: Co-crystallization with crown ethers and spherical crystallization by solvent screening

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