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Adhesiveness

Q: What factors influence the adhesiveness of a substance or material?

Adhesiveness can be influenced by a variety of factors, including surface tension, chemical composition, and physical structure. Understanding how these elements impact adhesiveness is crucial for ensuring reliable performance, reproducibility, and efficacy in research and product development.

Q: Are there different types or variations of adhesiveness that I should be aware of?

Yes, there are various types and applications of adhesiveness, such as in adhesives, coatings, and medical devices. Each use case may require specific adhesive properties or characteristics. PubCompare.ai can help you navigate these differents types of adhesiveness and identify the optimal solutions for your research or product development.

Adhesiveness refers to the property of a substance or material to stick to other surfaces.
This characteristic is crucial in various applications, such as adhesives, coatings, and medical devices.
Adhesiveness can be influenced by factors like surface tension, chemical composition, and physical structure.
Understanding and optimizing adhesiveness is essential for ensuring reliable performance, reproducibility, and efficacy in research and product development.
PubCompare.ai's AI-driven Adhesiveness Optimization tool can help researchers easily locate relevant protocols and identify the best products for their needs, taking the guesswork out of the process and enhancing research reproducibility.

Most cited protocols related to «Adhesiveness»

Selecting Severe Malaria-Associated P. falciparum Variants

The P. falciparum clone 3D7 was cultured in 0 Rh⁺ RBCs as previously described (21 (link)). Repeated rounds of panning on DynaBeads coated by IgG from two plasma pools (SM1 and SM2) from semi-immune Ghanaian children (22 (link)) and one plasma pool (SM3) from semi-immune Tanzanian children (23 (link)) were used to select 3D7 parasites expressing VSAs that were highly recognized by IgG in these plasma pools (19 (link)).
Standard panning techniques (24 (link)) were used to select 3D7 asexual parasites for adhesiveness to TrHBMECs (20 (link), 25 (link)). After three rounds of selection followed by cryo preservation and recovery, the ability of the selected subline and the parental culture to adhere to TrHBMEC (5,000–20,000/well) was compared. On average (six experiments), selected 3D7 bound 69 infected RBCs/100 TrHBMECs compared with 17.5 infected RBCs/100 TrHBMECs for the unselected parental parasites (P = 0.0008; Student's t test).
Flow cytometry (21 (link)) was used to verify that each of the four selected sublines expressed VSA_SM-type VSAs, i.e., had a plasma IgG recognition pattern resembling that of VSAs expressed by P. falciparum parasites isolated from children with severe malaria (2 (link), 3 (link)). The genotypic identity of 3D7 and the selected sublines was regularly verified by PCR at the polymorphic msp1, msp2, and glurp loci (3 (link)).
In addition, parasites were isolated on days 8, 9, and 10 from a Dutch volunteer exposed on day 0 to mosquitoes infected by P. falciparum isolate NF54 (26 (link)) as part of ongoing studies of experimental infections (27 (link)). These parasites were cultured in vitro for 27 (day 8 and day 9 isolates) or 33 d (day 10 isolate) to obtain sufficient parasites for DNA/RNA analysis. Experiments involving samples of human origin received ethical clearance from the National Institute for Medical Research, Dar es Salaam, Tanzania, and the Ethical Committee of the University Medical Centre, Nijmegen, Netherlands.

Jensen A.T., Magistrado P., Sharp S., Joergensen L., Lavstsen T., Chiucchiuini A., Salanti A., Vestergaard L.S., Lusingu J.P., Hermsen R., Sauerwein R., Christensen J., Nielsen M.A., Hviid L., Sutherland C., Staalsoe T, & Theander T.G. (2004). Plasmodium falciparum Associated with Severe Childhood Malaria Preferentially Expresses PfEMP1 Encoded by Group A var Genes. The Journal of Experimental Medicine, 199(9), 1179-1190.

Publication 2004

Adhesiveness Child Clone Cells Cryopreservation Culicidae Erythrocytes Flow Cytometry Genotype Infection Malaria Merozoite Surface Protein 1 Neutrophil Parasites Parent Plasma Surgical Clearance Voluntary Workers

Galvanic Vestibular Stimulation Protocol for Subliminal Perception

Galvanic vestibular stimulation was delivered to subjects through carbon rubber electrodes (17 cm²) in a bilateral, bipolar fashion. For bilateral stimulation, an electrode was placed over the mastoid process behind each ear, and coated with Tac gel (Pharmaceutical Innovations, NJ, USA) to optimize conductivity and adhesiveness. The average impedance of the subjects was measured around 1 kΩ. Digital signals were generated on a computer using MATLAB and converted to analog signals via a NI USB-6221 BNC digital acquisition module (National Instruments, TX, USA). The analog command voltage signals were subsequently passed to a constant current stimulator (Model DS5, Digitimer, Hertfordshire, UK), which was connected to the stimulating electrodes.
Bipolar stimulation signals were zero-mean, linearly detrended, noisy currents with a 1/f-type power spectrum (pink noise) as previously applied to PD and healthy subjects (Soma et al., 2003 (link); Yamamoto et al., 2005 (link); Pan et al., 2008 (link)). The stimulation signal was generated between 0.1 and 10 Hz with a Gaussian probability density, with the command signal delivered to the constant-current amplifier at 60 Hz (Figure 2). The stimulus was applied at an imperceptible level to avoid effects by general arousal and/or voluntary selective attention, with the current level individually determined according to each subject’s cutaneous sensory threshold.
Since perception of GVS is inherently subjective, we utilized systematic procedures that have been previously used in determining subliminal current levels for both GVS and transcranial stimuli (Hummel et al., 2005 (link); Utz et al., 2011 (link); Wilkinson et al., 2012 (link)). Starting from a basal current level of 20 μA, noisy test stimuli were delivered for 20 s periods with gradual stepwise increases (20 μA) in current intensity until subjects perceived a mild, local tingling in the area of the stimulating electrodes. As performed previously, a threshold value was defined once subjects reported a tingling sensation (Utz et al., 2011 (link); Wilkinson et al., 2012 (link)), which lasted for the duration of the test stimulus. The current level was then decreased each time by one level until sensation was no longer reported during delivery of test stimulus pulses, and increased by one step in current intensity to confirm threshold. Each delivery of a test stimulus was followed by a period of no stimulation for at least 30 s to preclude a hysteretic effect carrying over to the next test stimulus. Subjects were blind to the onset and duration of test stimuli, as well as the threshold-testing scheme. After completing the threshold test and throughout the experiment, stimuli were delivered at subthreshold intensity (190–900 μA), which is achieved at 90% of the determined cutaneous sensory threshold value.

Lee S., Kim D.J., Svenkeson D., Parras G., Oishi M.M, & McKeown M.J. (2015). Multifaceted effects of noisy galvanic vestibular stimulation on manual tracking behavior in Parkinson’s disease. Frontiers in Systems Neuroscience, 9, 5.

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Publication 2015

Adhesiveness Arousal Attention Carbon Carisoprodol Electric Conductivity Fingers Healthy Volunteers Innovativeness Obstetric Delivery Pharmaceutical Preparations Process, Mastoid Pulses Rubber Vestibular Labyrinth Visually Impaired Persons

Texture Profile Analysis of Samples

Textural parameters were measured by using texture profile analysis (TPA) (Zwick Company, Ulm, Germany) with mechanical compression of samples and the back extrusion test in four cycles with the cylindrically shaped probe (diameter of 40 mm). TPA instrument measured different parameters such as hardness, chewiness, gumminess, springiness, cohesiveness, and adhesiveness. The analyzer was connected to a computer that documented data via a software program called test software testXpert^® II.

Mousavi M., Heshmati A., Daraei Garmakhany A., Vahidinia A, & Taheri M. (2019). Texture and sensory characterization of functional yogurt supplemented with flaxseed during cold storage. Food Science & Nutrition, 7(3), 907-917.

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Publication 2019

Adhesiveness Gingiva Natural Springs

Texture Analysis of Yogurt

The texture of yogurt was determined by penetration measurements (TA.XT plus, Texture Analyzer, Stable Micro Systems Ltd., England). The instrument was adjusted to the following conditions: cylindrical probe, probe diameter: 35 mm; penetration speed: 1.0 mm/s; penetration distance, 20 mm into surface. The software used was Exponent (Stable Micro Systems, 2006, version 5.0). 100 mL of yogurt sample was analyzed in each cup. Four parameters were evaluated, the firmness (g) (maximum force, i.e., exerted on the sample), defined as the force necessary to attain a given deformation; the cohesiveness (g/s) (adhesive force), defined as forces of internal bonds, which keep the product complete; the viscosity (g); and the adhesiveness (g/s) (total negative area); the work is necessary for overcoming the force of attraction between the area of foodstuff and other solids coming to contact with them.

Han X., Yang Z., Jing X., Yu P., Zhang Y., Yi H, & Zhang L. (2016). Improvement of the Texture of Yogurt by Use of Exopolysaccharide Producing Lactic Acid Bacteria. BioMed Research International, 2016, 7945675.

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Publication 2016

Adhesiveness Bond Force dental cement G Force Viscosity Yogurt

Collagen Hydrogel Preparation for Cell Culture

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Publication 2017

Acetic Acid Acids Adhesiveness Bicarbonate, Sodium Binding Sites Cell Culture Techniques Cells Collagen Collagen Type I HEPES Hydrogels Phosphates Proteins Saline Solution Salts Sodium Hydroxide Staphylococcal Protein A Strains Tail

Most recents protocols related to «Adhesiveness»

Optimizing Secondary Battery Pouch Film Production

Not available on PMC !

Example 1

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 100° C.

A secondary battery pouch film is produced, after the process temperature of the two-component type solvent-based emulsion having a start temperature lowered to 135° C. to 150° C. is set to 100° C.

Example 2

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 120° C.

Example 3

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 135° C.

Example 4

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 150° C.

Example 5

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 165° C.

Example 6

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 180° C.

Example 7

A secondary battery pouch film is produced, after the drying process temperature of the two-component type solvent-based emulsion having a start temperature of 175° C. to 190° C. is set to 200° C.

Example 8

Example 9

Example 10

TABLE 1

Start Drying process

No.temperature (° C.)temperature (° C.)

Comparative Example 1175~190100

Comparative Example 2120

Comparative Example 3135

Comparative Example 4150

Comparative Example 5165

Comparative Example 6180

Comparative Example 7200

Example 1135~150100

Example 2120

Example 3135

Example 4150

Comparative Example 8165

Comparative Example 9180

Comparative Example 10200

Evaluation of Properties

Evaluation of Initial Peel Strength

- (1) An experimental sample is prepared by cutting the secondary battery pouch film to have a size of 1.5 cm by 15 cm in width and length, respectively.
- (2) The metal layer and the sealant layer are peeled off, and the peel strength is measured.

Evaluation of Hydrofluoric Acid Resistance

- (1) After the secondary battery pouch film is cut to have a size of 10 cm by 20 cm, two surfaces on both sides thermally adhered to each other.
- (2) A manufacturing solution (electrolyte+water (10,000 ppm (about 1%) of concentration of water in the solution)) is put inside the secondary battery pouch having the two surfaces adhering to each other, thermal adhering is performed, and a pack is manufactured.
- (3) The pack is stored at a high-temperature condition (85° C.) for 24 hours.
- (4) The electrolyte inside the pack is removed, and the sample is prepared (width 1.5 cm and length 15 cm) in the same manner as in the evaluation of initial peel strength.
- (5) The peel strength between the metal layer and the sealant layer is measured.

Evaluation of Electrolyte Resistance

- (1) An experimental sample is prepared by cutting the secondary battery pouch film to have a size of 1.5 cm by 15 cm in width and length, respectively.
- (2) The prepared sample is impregnated with a standard electrolyte (1.0 M LiPF6(EC/DEC/EMC: 1/1/1)) and is stored at a high temperature condition (85° C.) for 24 hours.
- (3) After the electrolyte is washed off, the metal layer and the sealant layer are peeled off, and the peel strength is measured.

Evaluation of Formability

- (1) A sample is prepared by cutting the produced secondary battery pouch film to have a size of 15 cm by 15 cm.
- (2) The prepared samples are formed by using a test die (size of 3 cm×4 cm) manufactured by Youlchon Chemical, Co., Ltd.
- (3) Evaluation of formability is repeatedly performed by changing the setting of the forming depth and is performed until ten or more samples are not broken.
- (4) A forming depth, in ten or more samples are not broken, is measured.

Evaluation of Penetration Strength

- (1) A sample having a width of 35 mm and a length of 600 mm is produced from the secondary battery pouch film.
- (2) The penetration strength is measured at intervals of about 40 mm in a direction from the outer layer toward the inner layer.
- (3) After the strength is measured ten times, an average value thereof is recorded.

In this case, the higher the formability, a forming process range may be wider during manufacturing of a battery. It is appropriate that the electrolyte resistance strength is equal to or higher than 90% of the initial peel strength, and the hydrofluoric acid resistance strength should be equal to or higher than 5 N/15 mm. Since the electrolyte resistance strength and the hydrofluoric acid resistance strength are much affected by the initial peel strength, it is appropriate that the initial peel strength is equal to or higher than 14 N/15 mm.

Table 2 shows evaluation of physical properties based on the curing start temperature and the drying process temperature.

TABLE 2

Hydrofluoric

DryingInitialElectrolyteacid

StartprocesspeelresistanceresistancePenetration

temperaturetemperaturestrengthstrengthstrengthstrengthFormability

No.(° C.)(° C.)(N/15 mm)(N/15 mm)(N/15 mm)(N)(mm)

Comparative1751002PeelingPeeling18.46.5

Example 1~190

Comparative1202.3PeelingPeeling19.26.6

Example 2

Comparative1352.2PeelingPeeling19.36.6

Example 3

Comparative1506.4PeelingPeeling19.36.5

Example 4

Comparative16514.514.15.824.26.3

Example 5

Comparative18014.814.35.724.66.1

Example 6

Comparative20015.614.85.824.56.1

Example 7

Example 11351009.2 8.13.919.46.8

Example 2~15012012.411.64.320.26.7

Example 313514.614.26.221.86.7

Example 415015.014.36.422.36.8

Comparative16515.114.86.423.86.3

Example 8

Comparative18015.715.16.224.26.1

Example 9

Comparative20016.115.46.524.76.0

Example 10

As known from the above, when an emulsion having a start temperature of 175° C. to 190° C. (Comparative Examples 1, 2, 3, and 4) is applied, the initial peel strength is relatively very low to be 10 N or lower when the drying process temperature is 150° C. or lower. The low initial peel strength resulted in a phenomenon where the sealant layer and the metal layer are completely separated from each other during evaluation of the electrolyte resistance strength and the hydrofluoric acid resistance strength.

When the drying process temperature is 165° C. to 200° C. (Comparative Examples 5, 6, and 7), the initial peel strength, the electrolyte resistance strength, and the hydrofluoric acid resistance strength are all good. However, the penetration strength increased to 24 N or higher. As well, a result that the formability does not reach 6.5 mm is obtained.

When the emulsion having a start temperature lowered to 135° C. to 150° C. is applied, the initial peel strength is 10 N/15 mm or lower only when the drying process temperature is 100° C. (Example 1), and the initial peel strength is 12 N/15 mm or higher in a drying process condition of 120° C. or higher (Examples and Comparative Examples 8 to 10). It is confirmed that a decrease in start temperature improves the adhesiveness even at a low drying process temperature.

However, the hydrofluoric acid resistance strength does not reach 5 N/15 mm in the 120° C. condition (Example 2), and the initial peel strength, the electrolyte resistance strength, and the hydrofluoric acid resistance strength are all good in conditions of 135° C. or higher (Examples 3 and 4 and Comparative Examples 8 to 10).

Similar to Comparative Examples 1 to 7, results of an increase in penetration strength in a condition of 165° C. to 200° C. (Comparative Examples 8, 9, 10) and the result of formability smaller than 6.5 mm is obtained.

The penetration strength increased to 20 N or higher at a condition of 135° C. to 150° C. (Examples 3 and 4), but has the best of the formability of 6.5 mm or more.

Therefore, only in a drying process temperature condition corresponding to the start temperature, all the properties of the initial peel strength, the electrolyte resistance strength, the hydrofluoric acid resistance strength are appropriate. When the drying process temperature is above 150° C., and particularly 165° C. or higher as found in an experiment, the penetration strength of the secondary battery pouch film significantly increases, and thus the formability decreases.

Therefore, in order to appropriately obtain all the physical properties, it is preferable to lower the drying process temperature to 150° C. or below, and to this end, it is preferable to lower the start temperature of the solvent-based emulsion to 150° C. or below.

According to the exemplary embodiments of the invention, when the secondary battery pouch film is manufactured, the primer layer composition that is interposed between the metal layer and the melt-extrusion resin layer or the sealant layer is made of a two-component curing-type organic solvent-based emulsion composition containing acid-modified polypropylene and a curing agent, wherein the curing start temperature and the drying process temperature are adjusted, and thermal lamination is not performed. Thereby, good formability, as well as good initial peel strength, hydrofluoric acid resistance, electrolyte resistance, etc. may be achieved.

The present invention was made under Project ID 20007148 from the Ministry of Trade, Industry and Energy, Korea Evaluation Institute of Industrial Technology under research project “Development of Technology of Materials and Components—Materials and Components Packaging Type”, research title “Performance Evaluation of Medium and Large Size Secondary Battery Pouch and Empirical Research for Application to Demand Companies” granted to Youl Chon Chemical Co., Ltd. For the period 2019 Sep. 1-2021 Feb. 28.

While the present invention has been described with respect to the specific embodiments, it will be apparent to those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims.

US11876235B2. Primer layer composition, secondary battery pouch film using the same, and method of manufacturing the same (2024-01-16). Youlchon Chemical Co., Ltd. [KR]. Inventors: Nok Jung Song [KR], Han Chul Park [KR], Hee Sik Han [KR], Ji Min Lee [KR].

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Patent 2024

Acids Adhesiveness Cold Temperature Electrolytes Emulsions Fever Hydrofluoric acid Metals Oligonucleotide Primers Physical Processes Polypropylenes Resins, Plant Solvents Technology Assessment

Modeling Glioblastoma Cell Migration on Linear Fibers

To model the cell migration of a single U251 glioblastoma cell on a linear fiber, the model developed by Ron et al., 2020 was used.^[²⁰^] In this model, the actin polymerization and adhesion dynamics were localized at the edges of the cell. For each edge, therefore, three dynamical equations were obtained: 1) For the position of the edge x_i, 2) for the polymerization speed v_i, and 3) for the adhesion concentration n_i, where i denotes the front or the back

{\dot{x}}_{f, b} = \frac{1}{Γ_{f, b}} (\pm (\frac{r}{r + r_{0}}) v_{f, b} \mp k (x_{f} - x_{b} - 1))

{\dot{n}}_{f, b} = r (1 - n_{f, b}) - n_{f, b} \exp (\frac{- (\frac{r}{r + r_{0}}) v_{f, b} + k (x_{f} - x_{b} - 1)}{f_{s} n_{f, b}})

{\dot{v}}_{f, b} = - δ (v_{f, b} - v_{f, b}^{*})

where r represent the cell‐fiber adhesiveness due to the binding and unbinding of slip‐bond adhesions at the cell rear, and the parameter r₀ represents the fiber adhesiveness due to the binding and unbinding of catch‐bond‐like adhesions at the cell front. The parameter k represents the cell elasticity (mean cell spring constant). The parameters f_s and κ are associated with the mechanical properties of the adhesions.^[²⁰^] The parameter δ represents a time scale for changes in the local actin polymerization speed.
The term Γ_f,b represents the friction term which changes with respect to the direction of motion of the cell's edge, and is given by

Γ_{f, b} = \{\begin{matrix} \frac{r}{r + r_{0}}, \pm {\dot{x}}_{f, b} > 0 \\ n_{f, b} κ \exp (\frac{(\frac{r}{r + r_{0}}) v_{f, b} - k (x_{f} - x_{b} - 1)}{f_{s} n_{f, b}}), \pm {\dot{x}}_{f, b} < 0 \end{matrix}

such that the top function in Equation (13) applies to edges that extend outward, while the complex lower function in Equation (13) applies to edges that retract.
The terms vf,b∗ represent the steady‐state polymerization speeds at the cell's edges, and are given by

v_{f, b}^{*} = β (\frac{1}{1 + c_{f, b}})

where β is the maximal actin polymerization speed which couples the steady‐state actin polymerization speed to the saturated polarity cue at the cell's edge.
The functional form of cf,b is given by

c_{f, b} = \frac{c (v_{f}^{*} - v_{b}^{*})}{D} (\frac{e^{- \frac{(v_{f}^{*} - v_{b}^{*}) x_{f, b}}{D}}}{e^{- \frac{(v_{f}^{*} - v_{b}^{*}) x_{b}}{D}} - e^{- \frac{(v_{f}^{*} - v_{b}^{*}) x_{f}}{D}}})

where D is the diffusion coefficient of the polarity cue, and c is a dimensionless quantity that encapsulates the concentration and its saturation properties.^[²⁰^] Equation (15) is derived from the description of the advection‐diffusion process of the polarity cue along the cell and is fully discussed in Maiuri et al. 2015^[²²^], and Ron et al. 2020^[²⁰^].
For the construction of the phase diagram (Figure 7B) two bifurcation curves were calculated:

The transition between the “no‐motility” and the “smooth motion” phases, calculated by finding a critical coupling strength β_c at which the actin polymerization speed is sufficient for the cell to become polarized. The value of β_c is determined by equating the two polarization lengths which are derived from the model.^[²⁰^]

The first critical length arises due to the advection of the polarity cue

l_{c} = \frac{c}{\sqrt{\frac{c β}{D} - 1}}

and the second critical length is derived from the force balance between the actin polymerization and the cell elasticity

l_{p} = \frac{1}{2} (1 - c) + \frac{β}{2 k} (\frac{r}{r + r_{0}}) + \sqrt{c + {(\frac{1}{2} (1 - c) + \frac{β}{2 k} (\frac{r}{r + r_{0}}))}^{2}}

Equating the lengths in these two equations, the analytical form of β_c as a function of r is given by

β_{c} (r) = \frac{D}{2 c} + c k (1 + \frac{r_{0}}{r}) + \frac{c k^{2}}{2 D} {(1 + \frac{r_{0}}{r})}^{2} + (\frac{D - c k (1 - \frac{r_{0}}{r})}{2 c D}) F (r)

F (r) = \sqrt{{(D + c k (1 + \frac{r_{0}}{r}))}^{2} + 4 c^{2} D k (1 + \frac{r_{0}}{r})}

The second transition line between the smooth motion and the stick‐slip motion is a Hopf bifurcation transition line which is obtained using a continuation method with AUTO07P.^[³⁰^]

To calculate the persistence time in (Figure 7E(i)), random Gaussian noise was added to the actin polymerization speed (Equation (12)). The average amplitude of the noise was chosen to be Δv = 2 (in dimensionless units, as β) to provide sufficient fluctuations for the cell to change its direction. The formula for the persistence time is given by

τ_{p e r s i s t e n c e} = \frac{\sum T i m e s b e t w e e n d i r e c t i o n c h a n g e s}{N u m b e r o f d i r e c t i o n c h a n g e s}

Throughout the simulations, the fixed parameters that were used in the model are c = 4, D = 4, k = 1, f_s = 5, κ = 20, r₀ = 1, δ = 100, r = 5. For Figure 7C,D the values that were used for the maximal actin polymerization speeds are β = 8, 12 (with respect to the black points in Figure 7B).
To calculate the cell's speed as a function of the adhesion parameter r in Figure 7F(i), the velocity of the moving front was averaged over 500 simulations with a very small noise amplitude of Δv=10−7. We choose the velocity of the moving front as a proxy for the mean cell speed as it remains constant during stick‐slip events. This calculation was performed for β = 8, 12 (“KO”, “WT” in Figure 7B).

Mukherjee A., Ron J.E., Hu H.T., Nishimura T., Hanawa‐Suetsugu K., Behkam B., Mimori‐Kiyosue Y., Gov N.S., Suetsugu S, & Nain A.S. (2023). Actin Filaments Couple the Protrusive Tips to the Nucleus through the I‐BAR Domain Protein IRSp53 during the Migration of Cells on 1D Fibers. Advanced Science, 10(7), 2207368.

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Publication 2023

Actins Adhesiveness Cell Adhesion Cells Diffusion Elasticity Fibrosis Friction Glioblastoma Migration, Cell Motility, Cell Polymerization

Texture Profiling of Food Emulsions

Texture profile analysis (TPA) was carried out with a TAXTplus texturometer (Stable MicroSystems, UK), using a 5 kg load cell. Penetration tests were carried out with a cylindrical probe (19 mm diameter), with a pre-test, test and post-test speed of 1 mms⁻¹ and the samples were analyzed in a cylindrical container (45 mm height and 60 mm diameter). The experiments were carried out 24 h after preparation, to allow the emulsions to stabilize at 4 °C. Before any measurements, the emulsions were allowed to equilibrate at 20 °C for approximately 1 h in a temperature-controlled room. The TPA was performed at least five times for each formulation.
Texture parameters were calculated from the texturogram force (N) versus time (s). Firmness (N) was considered as the maximum resistance force to probe penetration during the first compression cycle. Adhesiveness (-N.s) represented the work required to pull the probe away from the sample and was recorded as the area under the force curve of any negative peak after the first penetration cycle. Firmness and adhesiveness are textural parameters that are closely related to rheology and are suitable for characterizing the texture of emulsions [23 (link),25 (link)]. In addition, firmness is key in determining the texture, as it influences consumer perception and sensory acceptance.

Aybar M., Simões S., Sales J.R., Santos J., Figueira D, & Raymundo A. (2023). Tenebrio molitor as a Clean Label Ingredient to Produce Nutritionally Enriched Food Emulsions. Insects, 14(2), 147.

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Publication 2023

Adhesiveness Cells Emulsions Preparation H

Texture Analysis of Jellified Products

The instrumental analysis of jellified products was performed with a Brookfield CT3 Texture Analyzer (Brookfield Ametek, Middleboro, MA, USA), assisted by TexturePro CT V1.5 software. Texture Profile Analysis (TPA) method was used to determine the firmness, adhesiveness, cohesiveness, and springiness of the samples. Immediately after obtaining, the jellified products were packed into cylindrical plastic containers (43 mm diameter and 40 mm height). The containers were kept overnight at room temperature in order to achieve the final gel structure. A double penetration test, using a 38.1 mm diameter acrylic cylinder, was applied until the target distance of 5 mm was reached. Penetration speed was 0.5 mm/s; the trigger was a load at 0.067 N, and the load cell was 9.8 N. Four replicates for each sample were made.

Teodorescu A.A., Milea Ș.A., Păcularu-Burada B., Nistor O.V., Andronoiu D.G., Râpeanu G, & Stănciuc N. (2023). Customized Technological Designs to Improve the Traditional Use of Rosa canina Fruits in Foods and Ingredients. Plants, 12(4), 754.

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Publication 2023

Adhesiveness Cells Natural Springs Precipitating Factors

Texture Analysis of Food Samples

Eight grams of each selected sample were placed in Falcon^® tubes (50 mL) and centrifuged for 3 min at 2663× g to ensure a smooth surface and the elimination of air bubbles. The tubes were left to rest for 24 h and subsequently analyzed using a texture analyzer; TA.XTplus (Stable Micro Systems, Godalming, UK).
The sample was placed beneath a cylindrical analytical probe (∅ = 10 mm) and compression was initiated at a velocity of 0.5 mm/s. When the probe reached 10 mm of depth the probe was raised out of the sample at 0.1 mm/s. After 5 s, the probe ran a second cycle at the same parameters. All analyses were performed at 25 °C and each sample was analyzed in triplicate.
Graphs of force by time were acquired and peaks of hardness and areas under curve (AUC) of compressibility and adhesiveness were achieved using Exponent^® (Stable Micro Systems Data Analysis Godalming, UK). Cohesion was calculated as the difference of compressibility area between the second and first cycle.

Fonseca-Santos B., Araujo G.A., Ferreira P.S., Victorelli F.D., Pironi A.M., Araújo V.H., Carvalho S.G, & Chorilli M. (2023). Design and Characterization of Lipid-Surfactant-Based Systems for Enhancing Topical Anti-Inflammatory Activity of Ursolic Acid. Pharmaceutics, 15(2), 366.

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Publication 2023

Adhesiveness

Top products related to «Adhesiveness»

Ta xt plus by Stable Micro Systems

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The TA-XT Plus is a texture analyzer designed for objective measurement of textural properties of a wide range of materials. It is a versatile instrument that can perform various tests, including compression, tension, extrusion, and penetration, to evaluate the physical properties of samples. The TA-XT Plus is equipped with a sensitive load cell and a precision actuator, allowing it to accurately measure the force, distance, and time parameters of the tested samples.

Ta xt plus texture analyzer by Stable Micro Systems

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The TA.XT Plus Texture Analyzer is a laboratory instrument designed to measure the physical properties and characteristics of a wide range of materials. It is capable of performing various texture analysis tests, including compression, tension, extrusion, and other specialized analyses.

Ta xt2i by Stable Micro Systems

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The TA-XT2i is a texture analyzer designed for measuring the physical properties of a wide range of materials. It is capable of performing a variety of tests, including tension, compression, extrusion, and more. The TA-XT2i is a versatile instrument that can be used to assess the textural characteristics of various products, such as food, cosmetics, and pharmaceuticals.

Ct3 texture analyzer by Ametek

Sourced in United States, United Kingdom, Canada

The CT3 Texture Analyzer is a lab equipment product designed to measure the physical properties of a wide range of materials. It provides objective and quantitative data on the texture, consistency, and mechanical characteristics of solid, semi-solid, and liquid samples.

Ta xtplus texture analyser by Stable Micro Systems

Sourced in United Kingdom, United States

The TA.XTplus Texture Analyser is a versatile and advanced lab equipment designed to measure the textural properties of a wide range of materials. It provides precise and reliable data on the mechanical characteristics of various samples, enabling users to gain valuable insights into product quality and performance.

Ta xt2i texture analyzer by Stable Micro Systems

Sourced in United Kingdom, United States

The TA-XT2i Texture Analyzer is a versatile laboratory instrument designed to measure the textural properties of a wide range of materials. It is capable of performing various compression, tension, and shear tests to assess the physical characteristics of samples.

Ta xt2 by Stable Micro Systems

Sourced in United Kingdom

The TA-XT2 is a texture analyzer used for objective measurement of the mechanical properties of a wide range of materials. It is a versatile instrument capable of performing various types of tests, including tension, compression, extrusion, and puncture tests. The TA-XT2 provides accurate and reproducible data to assess the textural characteristics of a sample.

Brookfield ct3 texture analyzer by Ametek

Sourced in United States

The Brookfield CT3 Texture Analyzer is a laboratory instrument designed to measure the textural properties of a wide range of materials, including foods, cosmetics, and pharmaceuticals. The device applies a controlled force to a sample and measures the force required to deform or penetrate the material, providing data on its texture-related characteristics.

Ta xt plus texturometer by Stable Micro Systems

Sourced in United Kingdom

The TA.XT.plus texturometer is a versatile laboratory instrument designed for objective texture analysis. It measures the force required to perform a specific action on a sample, providing quantitative data on the sample's textural properties.

Ta xt2 texture analyzer by Stable Micro Systems

Sourced in United Kingdom, United States

The TA-XT2 Texture Analyzer is a versatile instrument designed for the objective measurement of the textural properties of a wide range of materials, including foods, pharmaceuticals, cosmetics, and other products. The instrument utilizes a motorized test platform to apply precise force, compression, or tension to a sample, and measures the resulting response, providing quantitative data on the sample's texture characteristics.

What factors influence the adhesiveness of a substance or material?

How can I ensure I'm using the most effective adhesiveness protocols for my research?

Are there different types or variations of adhesiveness that I should be aware of?

How can PubCompare.ai assist me in optimizing my use of adhesiveness protocols and products?

PubCompare.ai allows you to screen protocol literatuer more efficiently, leveraging AI to pinpoint critical insights. This helps researchers identify the most effective protocols related to Adhesiveness for their specific research goals. The platform's AI-driven analysis can highlight key differences in protocol effectiveness, enabling you to choose the best option for reproducibility and accuarcy.

More about "Adhesiveness"

Adhesiveness is a crucial property in a wide range of applications, from adhesives and coatings to medical devices and research.
This characteristic, also known as tackiness or stickiness, refers to the ability of a substance or material to adhere to other surfaces.
Understanding and optimizing adhesiveness is essential for ensuring reliable performance, reproducibility, and efficacy in various industries and research fields.
Factors that influence adhesiveness include surface tension, chemical composition, and physical structure.
High surface tension, for example, can enhance adhesiveness, while certain chemical compositions and physical structures can affect the strength and durability of the adhesive bond.
In research and product development, adhesiveness is often measured using specialized equipment like the TA-XT Plus, TA.XT Plus Texture Analyzer, TA-XT2i, CT3 Texture Analyzer, TA.XTplus Texture Analyser, TA-XT2i Texture Analyzer, TA-XT2, Brookfield CT3 Texture Analyzer, and TA.XT.plus texturometer.
These instruments can provide valuable insights into the adhesive properties of materials, allowing researchers and developers to optimize their formulations and ensure consistent results.
PubCompare.ai's AI-driven Adhesiveness Optimization tool can help streamline this process by easily locating relevant protocols from literature, pre-prints, and patents, and identifying the best products for your needs.
This tool takes the guesswork out of the research process, enhancing reproducibility and saving time and resources.
Whether you're working with adhesives, coatings, medical devices, or any other application that requires a strong, reliable adhesive bond, understanding and optimizing adhesiveness is crucial.
With the right tools and resources, you can unlock the full potential of your research and development efforts.