Physicochemical Relationships Research Articles

Prediction of Melting and Solid Phase Transitions Temperatures and Enthalpies for Triacylglycerols using Artificial Neural Networks

Triacylglycerols (TAG) are the main components of vegetable oils and any attempt to simulate vegetable oils processes will demand knowledge of their properties. However, experimental values are scarce, considering that several TAG in their pure forms are unavailable or too expensive for experimental measurements. On the other hand, correlating physical properties with TAG molecular structure is not simple. TAG is a molecule composed of 3 fatty acids (FA) esterified to a glycerol (GL) backbone, making properties dependent on carbon number (CN) of each FA, number of unsaturations (UN) of each FA, and position of the FA in the GL backbone. Few models are available in literature for prediction of TAG melting properties, with a special attention to melting temperature (Tfus) and enthalpy (ΔHfus) and solid-solid transition properties of the TAG polymorphic forms. Wesdorp's, Moorthy's et al. and Zeberg-Mikkelsen and Stenby's works present models based on the Group-Contribution theory nowadays used, despite some flaws, particularly considering the polymorphic transitions. Therefore, this work was aimed at evaluating Artificial Neural Network (ANN) models for prediction of TAG's Tfus and ΔHfus (β-form) as well as temperature and enthalpy transitions of molecule polymorphic forms (α and β’). Database was composed of temperature and enthalpy experimental data from literature. For each TAG, 7 input data were provided: total CN, as well as CN and UN at sn-1, 2 and 3 TAG position. The Multilayer Perceptron Feed Forward (MPL) model was used, and the topology was evaluated for number of hidden layers (HL), number of neurons (NN) and activation function at each hidden layer, and convergence algorithm. Number of HL and NN was screened by using a Central Composite Rotatable Design (CCRD). Models were further evaluated by Explainable Artificial Intelligence (XAI) and feature evaluation strategies. Architectures showed a significant higher accuracy for calculation and prediction of TAG's melting properties of the 3 polymorphic forms, with R2 higher to 0.91 for all databases when compared to literatures’ models (excepted for the prediction of the melting temperature of the β form, where Wesdorp's model presented a better predictive ability, despite great similarity). Good results were probably related to the well-defined physicochemical relationship between input (molecular structure descriptors) and output (melting properties), that could be described by XAI evaluation. This is an important advantage considering the improvement of the performance of process and products design including TAG molecules.

Analysis of the physico-chemical relationship between losses of water, soil and soil nutrients in the water of the Farinha River – MA

Brazil has a vast reserve of water resources, but pollution from various sources and the effects of climate change have triggered a crisis in this sector. The as-sessment of water quality indices plays a crucial role in monitoring and unders-tanding this issue, and the country has established its own standards and moni-toring requirements to guarantee water quality. In addition, the physical-chemical relationship plays a fundamental role in the conservation of both soil and water. In this context, a study was carried out in the Farinha river basin, located in Maranhão, in the Cerrado biome, over an area of 55,338.12 hecta-res. Data was collected at ten different points along the river during the rainy and dry seasons. A Van Dorn bottle was used to collect water samples at vari-ous depths, which were analysed for pH, dissolved oxygen, electrical conducti-vity and temperature. Nutrients such as potassium, calcium, magnesium, sodi-um, silicon, nitrate and total phosphorus were quantified using filtration and spectroscopy techniques. The data obtained was tabulated and subjected to analysis of variance, with the means analysed using the Tukey test. This study reveals significant seasonal variations in the physico-chemical parameters of the water in the Farinha River in Maranhão, impacting aquatic life and water quality. This highlights the importance of continuous monitoring and manage-ment of these resources.

Evaluation of drinking water quality and associated health risks in Adama City, Ethiopia

Drinking water deterioration causes to risk of public health which is essential to supply safe water to the public. This study assessed groundwater quality and health risks in Adama City by analyzing groundwater and chlorine samples. Ion photometry techniques detected anions and cations, ensuring accuracy with quality control protocols. Water Quality Index (WQI) and chlorine decay modeling via WaterGEMs assessed water quality. Hazard index (HI) calculations evaluated exposure risks; Pearson correlation analyzed physicochemical relationships. Findings highlighted water quality and hazards. Aquachem software analyzed Adama's groundwater, revealing high total alkalinity and potassium exceeding WHO limits. Other parameters (nitrate, nitrite, chloride, fluoride, and sulfate) met WHO standards. Sodium, calcium, magnesium, iron, manganese, and boron also complied. Multivariate analysis showed significant parameter associations. Water types included Ca–Na–HCO3 (27.27 %), Na–Ca–HCO3 (36.36 %), Na–Ca–Mg–HCO3, Na–HCO3 (9.09 % each), and Na–Mg–HCO3 (18.18 %). Drinking Water Quality Index rated boreholes as "Good." Health risk assessments found no significant fluoride, iron, or manganese risks across ages. Chlorine residual analysis indicated 74 % had levels below WHO recommendations, prompting chlorine dosing adjustments. Findings inform groundwater management in Adama City.

Dynamic modeling and robust optimal operation of the hydrothermal synthesis of zeolites in a continuous oscillatory baffled reactor

Continuous flow synthesis offers major advantages in the production of specialty products, e.g. zeolites, such as tight temperature control and lower variation in product quality. Here we consider the hydrothermal synthesis of NaX zeolites in a continuous oscillatory baffled reactor (COBR). A process model is derived from physico-chemical relationships to analyze and optimize the operation of a pilot scale continuous oscillatory baffled reactor for zeolite synthesis. The process model is validated using plant data. Furthermore, the uncertainty of the model predictions is quantified. Based on this analysis, robust optimization is used to compute robust optimal operation points of the COBR. These optimal operation points are validated by the application to a real pilot plant.

Assessing the groundwater quality in Ghana's Nanton District: comprehensive evaluation and implications for sustainable management

Abstract This study, conducted in the Nanton District of Northern Ghana, assesses groundwater quality for drinking purposes and examines hydrochemical processes. We collected and analyzed 30 groundwater samples, evaluating their physicochemical properties, microbial content, microbial and physicochemical relationship, and hydrochemistry. Utilizing methods such as the weighted arithmetic water quality index (WQI), Gibbs and Piper diagrams, Stiff plots, scatter plots, and correlation matrices, we aimed to comprehensively understand groundwater quality in the district. Physicochemically, our findings indicate that approximately 83.3% of the groundwater is safe for direct consumption without treatment. However, microbial contamination was prevalent in all samples, rendering them unsafe. Parameters such as iron, manganese, color, turbidity, nitrates, sulfate, and pH were identified as potential influencers of microbial survival in the groundwater. Regarding major ions, sodium (Na+) dominated among cations, while bicarbonate (HCO3-) was the primary anion. Water types were categorized as Na-K-HCO3−, Na-K-Cl-SO42−, Ca-Mg-HCO3−, and mixed water, reflecting the hydrochemical composition. Our analysis revealed that rock weathering, evaporation, ion exchange, and human activities influence groundwater chemistry. We recommend further research to assess groundwater availability for sustainable development in the district. Additionally, continued research is encouraged to enhance our understanding of the correlation between coliform bacteria and physicochemical water parameters.

Computational Risk Assessment of Persistence, Bioaccumulation, and Toxicity of Novel Flame-Retardant Chemicals.

Novel brominated flame retardants (NBFRs) have emerged as chemicals of environmental concern, as they have been widely used as an alternative to polybrominated diphenyl ethers (PBDEs). Considering the similar structural features of NBFRs and PBDEs necessitates a comprehensive investigation to understand the physicochemical relationships of these compounds and their ability to alter biological functions. In this study, we investigated the persistent nature of NBFRs in terms of thyroid-disrupting potential by understanding the structure-stability aspects using density functional theory (DFT)-based reactivity parameters and interactions via molecular docking and molecular dynamics (MD) simulations. The results indicate that the DFT-based stability descriptor (chemical hardness) is associated with the persistent nature of NBFRs. The computed molecular interaction profile revealed prominent interactions between thyroid receptor-β (TR-β) and NBFRs. Stable trajectory and interactions with TR-β were obtained with ATE, p-TBX, PBT, PBEB, and TBBPA-DBPE during 100 ns of MD simulation. The results of these studies have suggested that the presence of a higher number of halogenated atoms increases the stability vis-à-vis the persistence and endocrine disruption potential of NBFRs.

The context dependency of fish-habitat associations in separated karst ecoregions.

Fish populations may be isolated via natural conditions in geographically separated ecoregions. Although reconnecting these populations is not a management goal, we need to understand how these populations persist across landscapes to develop meaningful conservation actions, particularly for species occupying sensitive karst ecosystems. Our study objective was to determine the physicochemical factors related to the occurrence of four spring-associated fishes. Arbuckle Uplift and Ozark Highlands ecoregions, USA. We used a hierarchical approach to identify habitat relationships at multiple spatial scales. We collected detection data using snorkeling and seining. We examined the physicochemical relationships related to the detection and occurrence of four spring-associated fishes using occupancy modeling in a Bayesian framework. We found physicochemical relationships that differed and were similar between ecoregions for several fishes. For three species, we found different water temperature relationships between ecoregions. Smallmouth bass were ubiquitous in their use of drainage areas in the Ozark Highlands but only associated with the lower network of the Arbuckle Uplift. There were several mirrored relationships between ecoregions, including an interaction between residual pool depth and water temperature, where sites with deeper pools were more likely to be occupied during warmer water temperatures. There were single-species occurrence relationships with percent vegetation and percent agriculture. Lastly, snorkeling was a more efficient sampling method compared to seining for all fishes. Our results indicate stream temperature mitigation may be possible via the maintenance of key channel morphologies, and we identify shared stressors between ecoregions. Channel mitigation to maintain reaches with deeper pools may be an important strategy for maintaining thermal refugia, particularly when considering climate change. Identifying the mechanistic underpinning of other multiscale ecological relationships would be helpful to discern if some of the different ecoregion relationships represent warning signals or interactions with unmeasured biotic or abiotic factors.

Advanced characterization techniques for the development of Subatomic scale catalysts: One step closer to industrial scale fabrication

To date, the large-scale fabrication of subatomic scale catalysts (SSCs) remains a formidable challenge despite their tremendous potential to drive future clean energy conversion and decarbonization technologies. The primary hurdle lies in understanding the physicochemical relationship at the multi-scale interface (i.e., nanoscale, sub-nano, clusters, atomic) in constructing the heterogeneous catalysts. Conversely, high throughput advanced characterizations offer efficient and accelerated analysis of catalysts' chemical properties, bridging the gap between laboratory-to-industrial scale catalyst development for various engineering applications. The implementation of advanced characterizations is paramount in reducing uncertainties in bulk production, particularly during pre-screening assessments of a diverse range of SSCs compositions and configurations. Overall, this review aims to provide an illuminating overview of the streamlined SSCs development process, propelling us one step closer to achieving bulk-scale fabrication.

A framework for forming thermoset polymer networks during laser powder bed fusion additive manufacturing

It is commonly reported that the limited availability of material types is a major barrier to widespread adoption for polymer laser powder bed fusion (PBF/L) additive manufacturing (AM). A deeper understanding of the physico-chemical relationships between AM process stimuli and polymer responsive behavior is needed to make data-driven decisions for PBF/L specific material development and formulation. Many researchers have cumulatively built the current state of PBF/L “science-based manufacturing” framework where an initial guess for process parameter values can be determined from measured polymer properties and the first-principles of physics. However, published literature has focused on developing this framework for thermoplastic processing of polymers omitting many specific concerns unique to processing thermosetting materials. The authors consider in the present work the implications of many specific aspects unique to thermosetting polymers during PBF/L manufacturing. These aspects are contextually discussed according to the five sub-functions of PBF/L and are described mathematically where appropriate alongside example data from thermosetting materials commercially available in powder form. This expansion of the prevailing material development framework to include thermosetting polymers paves the way for the unique performance properties offered by that class to be manifest through AM’s geometric freedom.

Probing Redox Properties of Extreme Concentrations Relevant for Nonaqueous Redox-Flow Batteries

Redox-flow batteries are an emerging energy storage technology that can pair with intermittent renewable energy technologies. There remains a need, however, to understand physicochemical relationships among the solvent, electrolyte salt, and redox-active molecules that comprise catholyte and anolyte solutions. To examine this relationship, we detail a systematic study wherein the concentrations of the redox-active molecule 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) and TBAPF6 electrolyte salts are varied over concentrations of 1 mM to over 1000 mM in acetonitrile. Three series were investigated: (1) varying the concentration of TEMPO while holding the concentration of TBAPF6 constant, (2) varying the concentration of TBAPF6 while holding the concentration of TEMPO constant, and (3) varying both the concentration of TEMPO and TBAPF6 with a 5:1 TBAPF6:TEMPO ratio. Cyclic voltammetry data from macro- and microelectrodes were used to quantify diffusion coefficients and heterogeneous electron transfer rates, and these metrics were connected to the conductivity and viscosity to develop clear trends over the entire concentration range. Fundamental chemical interactions that lead to changes in physical properties were implicated via vibrational spectroscopy and molecular dynamics (MD) simulations. Trends in conductivity and viscosity for systems were inversely related and correlated to trends in diffusion coefficients and heterogeneous electron transfer rates. Intuitively, faster diffusion and electron-transfer rates occurred with lower TEMPO concentrations and higher TBAPF6 concentrations, with the majority of conditions falling in the general proximity of literature values (k0 = 0.1–0.5 cm/s, D ≈ (2.0–4.0) × 10–5 cm2/s). At the highest TBAPF6 concentrations, vibrational spectroscopy and MD simulations show that intermolecular interactions were more nuanced, and solvation and ion-pairing effects begin to influence electrochemical and physical properties. This functional approach including electrochemical and physical characterization paired with MD simulations provides a template for methodically studying systems for redox flow battery applications.

Co0.75Mo3S3.75/CoS2@2D-MoS2 nanosheets on carbon cloth: A progressive binder-free electrocatalyst for hydrogen evolution reaction

The development of ultrathin non-noble metal dichalcogenide electrocatalysts with tunable physical properties such as phase transformations, defect engineering, and activating plane edges is essential in order to enhance their electrocatalytic performance for water splitting applications. In this present work, we account to report a facile approach to cationic modulations through a single-step hydrothermal approach for the fabrication of a two-dimensional (2D) self-assembled ultrathin Co0.75Mo3S3.75/CoS2 (Co–Mo–S) @MoS2 nanoflowers directly grown on carbon fibre cloth. The systematic physicochemical relationship of cobalt ion modulations into MoS2 nanoflowers (Co/Mo/S) enabled the formation of flower-like Co–Mo–S@MoS2 ultrathin nanosheets with enhanced active sites, resulting in enhanced electrocatalytic contribution for hydrogen evolution reaction. The synthesised catalyst exhibited an ultralow overpotential value of 43 mV (RHE) at 20 mA/cm2, very small Tafel value of ∼36.6 mV/dec, and long durability/stability of 51 h of electrolysis. As a whole, these presented results demonstrate a rational construction of 2D ion modulated MoS2 ultrathin nanosheet electrodes that are beneficial for sustainable energy storage devices, which could be potentially extended to other dimensional MoS2 based materials.

Multivariate prediction of Saliva Precipitation Index for relating selected chemical parameters of red wines to the sensory perception of astringency

Astringency is an essential sensory attribute of red wine closely related to the saliva precipitation upon contact with the wine. In this study a data matrix of 52 physico-chemical parameters was used to predict the Saliva Precipitation Index (SPI) in 110 Italian mono-varietal red wines using partial least squares regression (PLSr) with variable selection by Variable Importance for Projection (VIP) and the significance of regression coefficients. The final PLSr model, evaluated using a test data set, had 3 components and yielded an R2test of 0.630 and an RMSEtest of 0.994, with 19 independent variables whose regression coefficients were all significant at p < 0.05. Variables selected in the final model according to the decreasing magnitude of their absolute regression coefficient include the following: Procyanidin B1, Epicatechin terminal unit, Total aldehydes, Protein content, Vanillin assay, 520 nm, Polysaccharide content, Epigallocatechin PHL, Tartaric acid, Volatile acidity, Titratable acidity, Catechin terminal unit, Proanthocyanidin assay, pH, Tannin-Fe/Anthocyanin, Buffer capacity, Epigallocatechin PHL gallate, Catechin + epicatechin PHL, and Tannin-Fe. These results can be used to better understand the physico-chemical relationship underlying astringency in red wine.

Anticancer Agents as Design Archetypes: Insights into the Structure-Property Relationships of Ionic Liquids with a Triarylmethyl Moiety.

A fundamental challenge underlying the design principles of ionic liquids (ILs) entails a lack of understanding into how tailored properties arise from the molecular framework of the constituent ions. Herein, we present detailed analyses of novel functional ILs containing a triarylmethyl (trityl) motif. Combining an empirically driven molecular design, thermophysical analysis, X-ray crystallography, and computational modeling, we achieved an in-depth understanding of structure-property relationships, establishing a coherent correlation with distinct trends between the thermophysical properties and functional diversity of the compound library. We observe a coherent relationship between melting (T m) and glass transition (T g) temperatures and the location and type of chemical modification of the cation. Furthermore, there is an inverse correlation between the simulated dipole moment and the T m/T g of the salts. Specifically, chlorination of the ILs both reduces and reorients the dipole moment, a key property controlling intermolecular interactions, thus allowing for control over T m/T g values. The observed trends are particularly apparent when comparing the phase transitions and dipole moments, allowing for the development of predictive models. Ultimately, trends in structural features and characterized properties align with established studies in physicochemical relationships for ILs, underpinning the formation and stability of these new lipophilic, low-melting salts.

Investigation of the Physicochemical Relationships of the Production of a Polyelectrolyte Complex Based on Polydialldimethylammonium Chloride and Sodium Lignosulfonate as an Effective Inhibitor of Salt Deposits

Investigation of the Physicochemical Relationships of the Production of a Polyelectrolyte Complex Based on Polydialldimethylammonium Chloride and Sodium Lignosulfonate as an Effective Inhibitor of Salt Deposits

Three-dimensional (3D) morphological and liquid absorption assessment of sustainable biofoams absorbents using X-ray microtomography analysis

The three-dimensional (3D) microstructure of sustainable and biodegradable protein foam absorbents is correlated to their liquid absorption characteristics using X-ray microtomography. The physicochemical relationships between the protein material pore size and liquid penetration and distribution allow for understanding how the pores' interconnectivity impacts the absorption, particularly considering capillary-driven transport phenomena within the thin nano cell walls. The foams were made via lyophilization of protein solutions containing cellulose nanofibers to emphasize the impact of the processing on the foam microstructure. The results show gaseous and solid phases of the foams covering ca. 1000 pores, providing information that cannot be obtained using traditional 2D analysis (SEM). A correlation with the channel tortuosity was established based on the statistical accuracy of the diameter and number of pores per mm3. The relationship between absorption kinetics and physical parameters enables the designing of biofoams with functionality also resembling commercial synthetic products that currently generate a high amount of nondegradable waste in our society.

Multi-scale structures and physicochemical properties of waxy starches from different botanical origins

The multi-scale structures and physicochemical relationships of three different types of waxy starches (maize, tapioca, and potato) were investigated. The maize and tapioca starches exhibited A-type crystalline polymorph compared to potato starch (B-type). The WMS showed higher amorphous content (5.56 %) than other waxy starches. The WTS exhibited a low tendency of retrogradation with its high fa (DP 6–12) and low fb3 (DP ≥ 37) proportion of chains. Double helix content of WPS was observed highest with a high pasting viscosity (952.3 BU). Low fa (DP 6–12) and high fb3 (DP ≥ 37) chain proportions of the WPS retrograded easily. The compactness of the semi-crystalline aggregation structure influenced the retrogradation properties of waxy starches with a positive correlation. Furthermore, the peak viscosity of pastes was correlated with the proportion of fb3 (DP ≥ 37) chains, mass fractal dimension, and double helix content. The results provide guidance to design the application of waxy starches in the production of clean-labels.

Moisture sorption isotherms and thermodynamic properties of cowpea (Vigna unguiculate L. Walp) stored in a chamber under controlled humidity and temperature

AbstractThe sorption process of cowpea stored in a chamber the relative humidity of which is controlled by an atomizing humidifier was studied in 25, 35, and 45°C over 0.1%–0.9% water activities. A type III (J‐shapes) behavior was observed for the sorption isotherms of cowpea. The temperature increase caused a decrease in the equilibrium moisture content (EMC). Hysteresis effect existed over the entire water activity range. The experimental sorption data were fitted to many well‐known isotherm equations (GAB, BET, Henderson, Oswin, Peleg, Smith, Caurie, Halsey, Ferro‐Fontan, Kuhn, Chung‐Pfost, White‐Eiring). Among models evaluated, the Peleg equation was selected as the model giving the best fit quality for predicting the sorption behavior of cowpea. The sorption isotherms data were used to estimate the thermodynamic functions (sorption isoteric heat and entropy, Gibbs free energy, net integral enthalpy and entropy) providing an understanding energy requirement. The sorption isosteric heat calculated using the Clausius‐Clapeyron equation and the net integral enthalpy decreased swiftly with increasing moisture content while an increase was observed in the net integral entropy. Thermodynamic approach showed that the sorption process for cowpea was the enthalpy‐controlled and nonspontaneous.Practical ApplicationsSince the determination of the physicochemical relationship between water and food is very important for the continuity of food quality stability, many researches are carried out on this subject. The quality stability of foods is expressed in moisture sorption isotherms, which are the relationship between EMC and water activity at any temperature. Generally, data on equilibrium humidity were obtained using saturated salt solutions. No study was found on the moisture sorption isotherm data of cowpea stored in a chamber whose relative humidity is controlled by an atomized humidification system. It is thought that the data obtained with this system will achieve more successful results in equipment and process design since it is closer to the actual storage conditions.

Identification and expression analysis of the sucrose synthase gene family in pomegranate (Punica granatum L.).

BackgroundSucrose synthase (SUS, EC 2.4.1.13) is one of the major enzymes of sucrose metabolism in higher plants. It has been associated with C allocation, biomass accumulation, and sink strength. The SUS gene families have been broadly explored and characterized in a number of plants. The pomegranate (Punica granatum) genome is known, however, it lacks a comprehensive study on its SUS genes family.MethodsPgSUS genes were identified from the pomegranate genome using a genome-wide search method. The PgSUS gene family was comprehensively analyzed by physicochemical properties, evolutionary relationship, gene structure, conserved motifs and domains, protein structure, syntenic relationships, and cis-acting elements using bioinformatics methods. The expression pattern of the PgSUS gene in different organs and fruit development stages were assayed with RNA-seq obtained from the NCBI SRA database as well as real-time quantitative polymerase chain reaction (qPCR).ResultsFive pomegranate SUS genes, located on four different chromosomes, were divided into three subgroupsaccording to the classification of other seven species. The PgSUS family was found to be highly conserved during evolution after studying the gene structure, motifs, and domain analysis. Furthermore, the predicted PgSUS proteins showed similar secondary and tertiary structures. Syntenic analysis demonstrated that four PgSUS genes showed syntenic relationships with four species, with the exception of PgSUS2. Predictive promoter analysis indicated that PgSUS genes may be responsive to light, hormone signaling, and stress stimulation. RNA-seq analysis revealed that PgSUS1/3/4 were highly expressed in sink organs, including the root, flower, and fruit, and particularly in the outer seed coats. qPCR analysis showed also that PgSUS1, PgSUS3, and PgSUS4 were remarkably expressed during fruit seed coat development. Our results provide a systematic overview of the PgSUS gene family in pomegranate, developing the framework for further research and use of functional PgSUS genes.

Prediction of small-molecule compound solubility in organic solvents by machine learning algorithms

Rapid solvent selection is of great significance in chemistry. However, solubility prediction remains a crucial challenge. This study aimed to develop machine learning models that can accurately predict compound solubility in organic solvents. A dataset containing 5081 experimental temperature and solubility data of compounds in organic solvents was extracted and standardized. Molecular fingerprints were selected to characterize structural features. lightGBM was compared with deep learning and traditional machine learning (PLS, Ridge regression, kNN, DT, ET, RF, SVM) to develop models for predicting solubility in organic solvents at different temperatures. Compared to other models, lightGBM exhibited significantly better overall generalization (logS ± 0.20). For unseen solutes, our model gave a prediction accuracy (logS ± 0.59) close to the expected noise level of experimental solubility data. lightGBM revealed the physicochemical relationship between solubility and structural features. Our method enables rapid solvent screening in chemistry and may be applied to solubility prediction in other solvents.

Predicting Solvent-Dependent Nucleophilicity Parameter with a Causal Structure Property Relationship

Solvent-dependent reactivity is a key aspect of synthetic science, which controls reaction selectivity. The contemporary focus on new, sustainable solvents highlights a need for reactivity predictions in different solvents. Herein, we report the excellent machine learning prediction of the nucleophilicity parameter N in the four most-common solvents for nucleophiles in the Mayr's reactivity parameter database (R2 = 0.93 and 81.6% of predictions within ±2.0 of the experimental values with Extra Trees algorithm). A Causal Structure Property Relationship (CSPR) approach was utilized, with focus on the physicochemical relationships between the descriptors and the predicted parameters, and on rational improvements of the prediction models. The nucleophiles were represented with a series of electronic and steric descriptors and the solvents were represented with principal component analysis (PCA) descriptors based on the ACS Solvent Tool. The models indicated that steric factors do not contribute significantly, because of bias in the experimental database. The most important descriptors are solvent-dependent HOMO energy and Hirshfeld charge of the nucleophilic atom. Replacing DFT descriptors with Parameterization Method 6 (PM6) descriptors for the nucleophiles led to an 8.7-fold decrease in computational time, and an ∼10% decrease in the percentage of predictions within ±2.0 and ±1.0 of the experimental values.