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Cloud point

The cloud point is the temperature at which a or multicomponent in the isobaric temperature-composition plane first exhibits a decrease in due to the appearance of from . This phenomenon is characterized by the initial onset of cloudiness or haziness and can be induced by changes in temperature or composition, with the exact temperature influenced by factors such as heating or cooling rates. In , the cloud point is particularly significant for aqueous solutions of nonionic surfactants, where it marks the above which the solution undergoes liquid-liquid separation, forming a surfactant-rich and a dilute aqueous phase that renders the mixture turbid. For polyoxyethylene-based nonionic surfactants, this occurs as of the hydrophilic chains reduces with increasing , typically resulting in an upper cloud point upon heating. This property serves as a key parameter for water-soluble surfactants in emulsions and dispersions, influencing their stability and performance in formulations. The cloud point also finds applications in analytical techniques, such as cloud point extraction (CPE), an environmentally friendly method for separating and preconcentrating analytes from aqueous samples using nonionic without organic solvents. In this process, the solution is heated to its cloud point to form micelles that partition hydrophobic species, enabling efficient isolation for subsequent analysis. Additionally, in the , the cloud point of fuels and other products is defined as the at which a haze of wax crystals first becomes apparent upon cooling, causing visible cloudiness and indicating potential operability limits in cold conditions. This measurement, standardized by methods like ASTM D5772, helps predict fuel flow issues and guides additive use to improve low-temperature performance.

Fundamentals

Definition

The cloud point is the at which a or begins to exhibit or cloudiness due to the formation of a dispersed second phase, such as crystals, micelles, or emulsions. This typically occurs upon cooling or heating, depending on the system, and marks the onset of incomplete between components. In chemical contexts, it serves as a critical indicator of limits in like fuels, oils, and aqueous solutions. Unlike the , which represents the lowest temperature at which a can still under prescribed test conditions due to increased from solidified components, or the freezing point, which denotes the temperature of complete solidification into a homogeneous , the cloud point specifically signals the initial formation of heterogeneous structures without full cessation of or solidification. For instance, in petroleum-derived , this initial separation often involves wax crystals, while in systems, it may involve aggregation leading to splitting. The term "cloud point" originated in early 20th-century petroleum chemistry to characterize the temperature at which haze from wax precipitation first appears in hydrocarbon mixtures, as traditionally defined in standards like ASTM D2500. The concept has been applied to surfactant science, where it describes the upper consolute temperature for aqueous solutions of nonionic surfactants prone to liquid-liquid phase separation.

Physical Mechanisms

In systems exhibiting lower critical solution temperature (LCST) behavior, such as aqueous solutions of nonionic surfactants, the cloud point marks the temperature above which the solubility diminishes with increasing temperature, resulting in liquid-liquid phase separation. This counterintuitive temperature dependence arises from thermodynamic principles where the Gibbs free energy of mixing becomes positive due to an unfavorable entropy contribution outweighing the enthalpic gains from interactions like hydrogen bonding. In aqueous systems, this is often mediated by the disruption of hydrogen bonds between solute and solvent at elevated temperatures, coupled with enhanced hydrophobic interactions that favor solute aggregation over solvation. Cloud points can be classified as upper (upon heating, typically LCST liquid-liquid demixing) or lower (upon cooling, often solid-liquid separation). In crystal-forming systems like products, the lower cloud point corresponds to the initiation of in supersaturated solutions, where solute molecules—such as paraffin-like hydrocarbons—begin to organize into ordered lattices upon cooling below the . This process involves the formation of critical nuclei that overcome the barrier for , followed by growth through the attachment of additional molecules to the surfaces, leading to visible as solid phases emerge from the liquid. , achieved by reduction, drives this metastable-to-stable transition, with the rate of increasing exponentially near the cloud point. In micellar systems with non-ionic surfactants, the upper cloud point arises from the progressive dehydration of hydrophilic polymer chains, such as polyoxyethylene segments, as temperature rises and weakens the bonds sustaining their shells. This reduced exposes hydrophobic moieties, promoting inter-micellar attractions and the coalescence of individual micelles into larger aggregates or networks, which scatter light and induce macroscopic into dilute and concentrated phases. The gain from releasing structured molecules around the chains further favors this aggregation over dispersed states. The temperature-dependent miscibility underlying these mechanisms is captured by the Flory-Huggins theory of polymer-solvent interactions, which models the of mixing via the Flory-Huggins interaction parameter . This parameter determines phase stability, with demixing occurring when for binary systems. Its basic temperature dependence is expressed as \chi = \frac{\Delta H - T \Delta S}{RT}, where \Delta H and \Delta S represent the enthalpic and entropic contributions to mixing, T is the absolute temperature, and R is the ; as T increases, the entropic term -T \Delta S can render \chi sufficiently large to destabilize the homogeneous phase, aligning with LCST-type transitions in polymer-like systems.

Industrial Applications

In Petroleum Products

In petroleum products, the cloud point serves as a critical indicator of low-temperature performance for fuels like and , marking the onset of that can lead to clogging and engine failure in cold conditions. For conventional , this occurs when waxes begin to crystallize as temperatures drop below the cloud point, typically ranging from -10°C for winter-grade formulations to 10°C for summer grades, ensuring reliable operability across seasonal climates. In , derived from vegetable oils or animal fats, the cloud point is often higher—around 0°C to 5°C for common feedstocks like —due to the presence of saturated methyl esters that form biowax crystals more readily, exacerbating cold flow issues in blends with . Standards such as ASTM D2500 and its equivalent IP 219 define the manual test method for determining cloud point in these products, providing the basis for regulatory limits in major markets. In the United States, ASTM D975 for implies seasonal cloud point controls through operability requirements, while biodiesel under ASTM D6751 lacks a direct cloud point specification but emphasizes cold soak filterability to mitigate related risks. European specifications under mandate maximum cloud points varying by climate class, such as ≤ +3°C for summer and ≤ -10°C for winter grades in milder regions, extending to ≤ -34°C in conditions to prevent during transport and use. These standards ensure fuels meet performance thresholds, with biodiesel blends (e.g., B7) required to align with limits under EN 14214. As of 2022, ASTM D975 includes updated provisions for renewable blends to address flow properties. A high cloud point in and carries significant economic and safety implications, particularly following the biofuel mandates like the U.S. Renewable Fuel Standard and EU Directive, which boosted biodiesel adoption and highlighted cold-weather vulnerabilities. Precipitation can cause gelling, leading to stalled , emergency towing, and repair costs, as well as safety risks including stranded motorists in remote or harsh conditions, potential accidents from power loss, and broader disruptions in cold climates, underscoring the need for seasonal formulations or depressants to maintain flow. For instance, untreated biodiesel blends may fail at temperatures 10–15°C above their cloud point, increasing additive demands and blending expenses for refiners. Compared to other fuels, heating oils—similar to No. 2 diesel—exhibit higher cloud points around 0°C to 5°C, tolerable in stationary heating systems but still requiring to avoid line blockages. In contrast, kerosene (Jet A ) prioritizes freeze point stability (maximum -40°C), with typical cloud points below -20°C, to prevent solidification at high-altitude cruising temperatures.

In Surfactants and Detergents

In non-ionic , the cloud point represents the at which ethoxylated chains lose , leading to of the hydrophilic polyoxyethylene head groups and subsequent lower consolute (LCST) into a surfactant-rich and a dilute aqueous . This phenomenon arises from the reduced of the surfactant as disrupts hydrogen bonding between the units and molecules, causing aggregation and . The cloud point typically ranges from 0°C to 100°C, directly influenced by the content, where higher degrees of increase the cloud point by enhancing hydrophilicity and . In formulations, the cloud point determines the maximum operating temperature for effective performance in and applications, as exceeding it results in that reduces cleaning efficacy and stability. Higher cloud points above 60°C are preferred for products intended for hot-water washing, ensuring the remains soluble and active during typical household cycles up to 60–90°C, thereby maintaining detergency and preventing . For instance, in automatic detergents, surfactants with cloud points in the 20–70°C range are selected to balance low-foaming properties with removal under varying temperatures. Formulation strategies often involve polyethoxylated alcohols, such as linear C12E6 (dodecaoxyethylene monododecyl ), which exhibits a cloud point around 57°C, allowing control over and in aqueous systems. Branched variants of these alcohols provide greater tunability, as the branching in the hydrophobic tail alters packing and hydration, enabling adjustment of the cloud point for specific temperature requirements without compromising micellar stability. Environmental considerations have driven the adoption of biodegradable non-ionic surfactants like alkyl polyglycosides (APGs), derived from renewable glucose and fatty alcohols, which emerged prominently in the 1990s amid initiatives to replace less sustainable ethoxylates. In APGs, the cloud point is modulated by the sugar chain length, with longer units (e.g., average 1.4–5) increasing hydrophilicity and often resulting in higher or absent cloud points, promoting better cold-water and ultimate biodegradability into non-toxic components. This shift supports eco-friendly designs that minimize aquatic impact while preserving performance.

In Extraction Techniques

Cloud point extraction (CPE) is a separation technique that employs non-ionic or mixed to target analytes, including metal ions and compounds, into a compact surfactant-rich when the solution is heated above the cloud point , thereby enabling efficient recovery from aqueous matrices. This method leverages the temperature-dependent behavior of solutions, where the cloud point marks the onset of , concentrating analytes for subsequent or purification. The process begins with micelle formation in the aqueous phase below the cloud point, solubilizing hydrophobic or complexed analytes within the micellar cores; upon heating beyond this threshold, the solution becomes turbid, leading to rapid phase disengagement into a viscous surfactant-rich phase (typically 1-5% of the original volume) and a bulk aqueous phase, with analytes enriched in the former by factors up to 100-fold. Phase separation is often accelerated by centrifugation, followed by analyte recovery from the surfactant phase via dilution or back-extraction. In wastewater treatment applications, CPE achieves extraction efficiencies up to 99% for heavy metals such as lead and chromium, significantly reducing contaminant levels while minimizing waste generation. Introduced in the for environmental trace analysis, CPE was first detailed by Watanabe and Tanaka in 1978, who demonstrated its utility for metal ion preconcentration using polyoxyethylene surfactants. The technique gained broader adoption in the as a sustainable alternative to conventional organic solvent , aligning with principles by avoiding volatile and toxic solvents. Key advantages include the low toxicity and high recyclability of surfactants like Triton X-114 or PONPE-7.5, which can be reused multiple cycles with minimal loss of performance, reducing operational costs and environmental impact compared to methods like liquid-liquid . Representative applications highlight CPE's versatility in analytical purification; for instance, it effectively preconcentrates polycyclic aromatic hydrocarbons (PAHs) from environmental waters, achieving detection limits in the parts-per-billion range for monitoring . Similarly, CPE enables the enrichment of residues, such as organophosphates, from food samples like , with rates exceeding 95% and enrichment factors around 50, supporting in assessments. The tunability of cloud points through additive selection further optimizes selectivity for diverse analytes.

Measurement Methods

Manual Methods

Manual methods for determining the cloud point of products rely on visual observation of formation during controlled cooling, with the ASTM D2500/IP 219 standard serving as the primary procedure. This method is applicable to transparent liquids, such as middle distillate fuels, that are clear in layers up to 40 mm thick and have cloud points below 49°C. The detects the at which the first haze or cloud of crystals appears at the bottom of the sample, indicating the onset of . The required equipment includes a cylindrical clear test jar with flat bottom (outside 33 to and height 115 to 125 mm), a series of cooling baths capable of maintaining temperatures down to -60°C or lower, a high-precision (graduated in 1°C intervals), and a contrasting background such as a printed chart for enhanced visibility. The sample volume is standardized at 40 mL to ensure consistent and thermal uniformity within the jar. This setup allows for manual control of the cooling environment while minimizing external influences like vibration or direct light. The procedure begins by heating the sample, if necessary, to at least 14°C above its expected cloud point to dissolve any existing , then pouring it into the test jar up to the 40 mark. The jar is placed in the initial , and the assembly is observed against the background. The jar is transferred sequentially through a series of cooling baths maintained at progressively lower (such as 0°C, -18°C, -33°C, -51°C, and -69°C), achieving an approximate cooling rate of 1.5°C/min. The operator examines the sample at 1°C intervals by tilting the jar to inspect the bottom and lower walls, recording the at which the first persistent of wax crystals is visible; this point is confirmed by reheating and recooling if needed to verify . The entire process typically takes 20–30 minutes per sample, depending on the cloud point . For nonionic , the manual cloud point determination follows standards such as ISO 1065 or ASTM D2024, which involve preparing a dilute (typically 1% w/v) and heating it gradually from while observing for the onset of . The solution is stirred intermittently during heating to ensure uniformity, and the cloud point is recorded as the lowest temperature at which persistent cloudiness appears upon cooling slightly or confirming reversibility. This heating-based method reflects the upper cloud point typical for these materials. This method offers repeatability within ±2°C under ideal conditions but is susceptible to operator subjectivity in identifying the initial , variations in cooling rate homogeneity, and imprecise temperature measurements, which can lead to inconsistencies across laboratories. Due to these limitations, including the labor-intensive nature and potential for , manual techniques like ASTM D2500 have been increasingly supplemented or replaced by automated alternatives in standards since the late 1990s, particularly for high-volume testing.

Automated Methods

Automated methods for cloud point determination rely on instrumental techniques that objectively detect phase transitions through optical changes, offering enhanced precision and efficiency over manual approaches. The , ASTM D5771, outlines an optical detection stepped cooling method for petroleum products and biodiesel fuels transparent in 40 mm layers, applicable over a range of -60°C to +49°C with 0.1°C . In this procedure, the sample is introduced into a test jar or flow-through cell within an automated apparatus, cooled at controlled rates via a programmable jacket, and monitored for wax crystal formation using light transmission or detection. The cooling profile follows predefined steps, with jacket transitions limited to 90 seconds to ensure gradual sample cooling, and the cloud point is recorded when the optical sensor first registers a signal change indicative of . Commercial equipment, such as the ISL CPP 5Gs analyzer, implements this standard using a built-in refrigeration system and photodiodes to measure light intensity variations from crystal-induced scattering, achieving sample temperature accuracy of ±0.1°C and jacket accuracy of ±0.5°C. The method's precision includes repeatability of 2.2°C and reproducibility of 3.9°C for general petroleum products, with improved values of 1.2°C and 2.7°C for biodiesel blends, surpassing manual methods like ASTM D2500 in objectivity. These analyzers often feature compact designs with microprocessor controls, enabling operation down to -95°C without external cooling fluids. For and detergents, automated adaptations focus on nephelometric detection of light scattering from aggregation during temperature ramps, building on principles from ISO 1065 for non-ionic agents. Instruments like the Phase Technology 70Xi employ diffusive light scattering compliant with ASTM D2024, warming the sample until cloudiness appears and then cooling to measure the transition temperature where micelles separate, with a small 0.15 mL sample volume and resolution of 0.1°C. This approach achieves repeatability better than 0.5°C, detecting subtle changes in solution as non-ionic like polyethylene oxide derivatives phase-separate above their cloud point. These methods provide key advantages, including minimization of operator subjectivity, test durations of 5–10 minutes, and alignment with regulatory requirements such as for , which mandates cloud point reporting and accepts automated optical techniques following updates incorporating ASTM D5771 equivalents since 2010. By standardizing detection via photodiodes or scattering sensors, they support high-throughput testing in industrial labs while maintaining traceability to international standards.

Influencing Factors

Compositional Variables

In petroleum products such as diesel fuels, the cloud point is strongly influenced by the paraffin (wax) content and the chain length of n-alkanes. Higher concentrations of paraffins, particularly those with longer carbon chains (e.g., C20 and above), elevate the cloud point because these molecules have reduced solubility at higher temperatures, leading to earlier precipitation of wax crystals. Empirical correlations, such as those relating cloud point (\theta_{cp}) to wax percentage (%wax), demonstrate this direct proportionality, where increased wax content raises \theta_{cp} by enhancing the solid-forming tendency of the mixture. For instance, the average n-alkane chain length in fuel blends contributes to higher cloud points as chain length increases, with models showing that distributions favoring longer chains shift precipitation to warmer temperatures. In surfactant solutions, particularly nonionic types like alkyl ethoxylates, the ethylene oxide (EO) to propylene oxide (PO) ratio plays a critical role in determining the cloud point. Increasing the EO content enhances hydrophilicity, thereby raising the cloud point, as each additional EO unit strengthens hydrogen bonding with and delays . This effect is approximately linear, with studies indicating an increment of about 5–10°C per EO unit in polyethoxylated chains. Conversely, higher PO content, which introduces more hydrophobic character, lowers the cloud point by reducing overall in aqueous media. Impurities and blend compositions further modulate the cloud point through specific interactions. In petroleum fuels, aromatic compounds depress the cloud point by improving the solvency of paraffins, partitioning into the phase and inhibiting wax crystallization at lower temperatures. In surfactant solutions, added salts induce a salting-out effect that lowers the cloud point by dehydrating the hydrophilic EO chains, reducing micelle stability and promoting earlier ; this is particularly pronounced with anions like or . Quantitative models for cloud point often rely on linear regressions tailored to composition. For nonionic , a simple form is \theta_{cp} = a + b \times ([EO](/page/EO)\ number), where a and b are empirical coefficients derived from structural data, capturing the hydrophilicity-driven increase with EO units. Similar regressions extend to petroleum blends, correlating \theta_{cp} with % or average n-alkane chain length for predictive tuning in formulations.

External Conditions

External conditions, such as and cooling rates during measurement, significantly influence the observed cloud point in products and solutions by altering dynamics. In fuels, elevated s, as encountered in engines, can increase the cloud point by approximately 25°C compared to atmospheric conditions, as higher promotes earlier through enhanced molecular interactions. For nonionic solutions, also elevates the cloud point, with reported increases on the order of 1.05 × 10^{-7} Pa^{-1}, attributed to enhanced hydrogen bonding between and oxygens under compression. Additionally, the cooling rate during testing affects the apparent cloud point; faster rates (e.g., 0.5°C/min versus 0.1°C/min) lead to a depression of up to several degrees due to kinetic , where crystals or lag behind equilibrium conditions. Solvent quality, particularly water purity in surfactant systems, plays a critical role in modulating the cloud point through impurity interactions. In nonionic surfactant solutions, ionic impurities such as salts act as salting-out agents, promoting dehydration of the hydrophilic headgroups and thereby lowering the cloud point; for instance, additions of NaCl or Na₂SO₄ can reduce it by 10–20°C depending on concentration and anion type. This effect arises because electrolytes reduce the water structure around micelles, enhancing aggregation at lower temperatures. In contrast, highly pure deionized water minimizes such perturbations, yielding higher and more reproducible cloud points closer to the intrinsic value. Aging and storage conditions contribute to cloud point variations, especially in biodiesels, where oxidative over time elevates the cloud point. Exposure to air, light, and moderate temperatures during induces peroxidation of unsaturated chains, forming polymeric species and gums that accelerate and raise the cloud point by several degrees after months of , as documented in studies since 2005. This degradation is exacerbated in blends without antioxidants, leading to up to 5–10°C increases within 6–12 months under ambient conditions. Operational contexts, including altitude, introduce subtle pressure-related effects on cloud point determination, though these are generally minimal for products. At high altitudes, reduced (e.g., 0.7 at 3000 m) can slightly depress the cloud point in systems by 1–2°C per 10 decrease, as lower disfavors the compact dehydrated . For -influenced cloud points, altitude lowers the effective temperature scale due to reduced points, necessitating pressure-adjusted testing protocols in elevated locations. In fuels, however, such effects are negligible compared to compositional factors, with standard measurements conducted at sea-level .

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