US 2006/0223917 A1 · Method of optimizing a tire tread compound, and a tire tread compound made by said method

Abstract

The present invention relates to a methodology for determining various rubber composition factors that play a role in the structural and functional attributes of the rubber. The present invention also relates to tire treads that are derived using the methodology for optimizing the same as described herein.

Claims35

Dependent claims

A method of optimizing a tread compound, comprising:

a. providing a rubber composition comprising at least one functionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, wherein said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
and
c. calculating rubber composition factors from the set of tensile retraction curves, wherein the rubber composition factors comprise a trapped entanglements value (NE), a chemical crosslink value (NC), and a filler-filler-polymer interaction value (NF).

1 more element

A method of preparing an optimized tread compound, the method comprising:

a. providing a rubber composition comprising at least one functionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, wherein said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
c. calculating the molecular weight between chain restrictions (Mr) from the equation
M
r
=
ρ
⁢
⁢
RT
⁡
(
Λ
-
Λ
-
2
)
σ
,
for each maximum individual elongation used, wherein ρ is the compound density, σ is stress, R is the gas constant, T is temperature, and Λ is 1+Xε, wherein X is the Guth-Gold equation and the strain, ε, is (l−lset)/lset, wherein l is the specimen length at any point on the retraction curve, and lset is the specimen length after retraction to zero stress;
d. plotting a smooth curve from the data sets of Mr and maximum elongation that have all been adjusted to the same testing rate;
e. fitting the data from the tensile retraction curve to the equation
M
r
=
1
1
β
⁢
(
10
m
⁡
(
Λ
⁢
⁢
max
-
1
)
)
+
1
γ
⁢
(
10
n
⁡
(
Λ
max
-
1
)
)
+
1
M
C
+
S
⁡
(
Λ
max
-
1
)
wherein Mr and Λmax−1 are described above, and the parameters β, γ and Mc, and m, n and S, correspond to intercepts and slopes, respectively, for linearized segments of three regions of the curve represented by the equation above, to obtain values for the β, γ, and Mc intercepts;
f. varying filler content, state of cure, and presence of end-functionality and determining the effect of each β, γ, and Mc to isolate contributions resulting from trapped entanglements (NE), chemical crosslinks (NC), filler-filler-polymer interactions (NF), the number of end-functionality attachments to filler (NR);
and the probability π that an end is attached to the filler;
g. employing NR, NE, NC and NF to calculate the probability (π2) that a difunctional polymer is reacted at both ends;
and
h. providing an optimized tread compound.

74 more elements

A method of optimizing a tread compound, the method comprising the steps of:

a. providing a rubber composition comprising an end-difunctionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, where said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
c. calculating the molecular weight between chain restrictions (Mr) from the equation
M
r
=
ρ
⁢
⁢
RT
⁡
(
Λ
-
Λ
-
2
)
σ
for each maximum individual elongation used wherein ρ is the compound density, σ is stress, R is the gas constant, T is temperature, and Λ is 1+Xε, wherein X is the Guth-Gold equation and the strain, ε, is (l−lset)/lset, wherein l is the specimen length at any point on the retraction curve, and lset is the specimen length after retraction to zero stress;
d. plotting a smooth curve from the data sets of Mr and maximum elongation after they have all been adjusted to the same testing rate;
e. statistically fitting a Mr=S(Λmax−1)+Mc line to the highest elongation region (Region I) by successively adding the next lowest elongation data set of the curve obtained in step (d), such that R (squared) is greater than 0.98;
f. subtracting the crosslink density (νe) predicted from the equation fitted to Region I from the measured νe corresponding to the remainder of the low elongation region of the data curve plotted in step (d) to obtain (Δνe);
g. plotting a smooth curve from the logarithm of Δνe of the data set vs. the remaining elongations;
h. statistically fitting a log Δνe=s(Λmax−1)+m line by starting at the highest remaining elongation region (Region II) and successively adding the next lowest elongation data set of the curve such that R (squared) is greater than 0.98;
i. subtracting the values of Δνe calculated from the equation fitted in Region II from the Δνe measured for the remainder of the low elongation region of the data set (ΔΔνe);
j. plotting a smooth curve from the logarithm of ΔΔνe determined in step (i) vs. the remaining elongations;
k. statistically fitting a log ΔΔνe=t(Λmax−1)+n starting with the highest remaining elongation region (Region III) by successively adding the next lowest elongation data set of the curve such that R (squared) is greater than 0.98;
l. calculating the total number of effective network strands, NT, from the number average molecular weight of the original polymer (Mn) and density (ρ), wherein NT=νeMn/ρ from each Mc intercepts of Region I;
m. plotting the NT for each filler level used vs. the concentration of accelerator [acc];
n. plotting the log ΔΔνe intercepts from Region III of the gum cured rubbers vs. [acc] and determining the molecular weight between entanglements, Me by statistically fitting the equation of y=dx2+ex+f wherein the zero [acc] intercept f is used to calculate Me= 1/10f;
o. calculating the trapped entanglements value for the cured unfilled polymer as
N
E
=
(
n
-
1
n
+
1
)
2
⁢
(
M
n
M
e
-
1
)
wherein n is the number of chemical bounds formed during cure;
p. plotting
N
T
=
(
n
-
1
)
+
(
M
n
M
e
-
1
)
⁢
(
n
-
1
n
+
1
)
2
vs. [acc] the value of n as a function of [acc] can be determined by fitting to the equation n=a[acc]b;
q. subtracting the sum value of NT from the filled value of NT to generate the contribution of the filler NF(H) to the cured rubber;
r. repeating the above steps with an α,ω-difunctional polymer and the equation NT=NC+NE+NF(func)+NR to account for the end group reacting with filler, NR, the change that this reaction causes in the contribution to the filler on crosslinking, NF(func), and the three different contributions of NE that account for trapping of entanglements;
wherein, for one and two end groups reacting with filler, the new equations become
N
T
,
1
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
⁢
(
n
n
+
1
)
2
+
1
⁢
⁢
and
⁢
⁢
N
T
,
2
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
+
2
,
respectively, and use the equation
N
T
,
0
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
⁢
(
n
-
1
n
+
1
)
2
where no polymer end groups react with filler;
s. calculating β= 1/10m from Region II as a measure of the filler contribution to the crosslinked network;
t. calculating the new NF(func) as the beta ratio of the non-functional polymer to the α,ω-difunctional polymer times the NF(H);
u. solving the equation weighted for the filler reaction of NT−NC=π2(NF(func)+NE,2+2)+2π(1−π)(NF(func)+NE,1+1)+(1−π)2 (NF(func)+NE,0) for the probability (π) that a chain end reacts with the filler;
and
v. optimizing the probability (π2) that a polymer has reacted at both ends with filler by selecting the type of functional group, filler type, accelerator type, mixing and curing conditions to give the lowest values for abrasion resistance and rolling resistance.

187 more elements

Dependencies are inferred from the claim text.

Facts

Application

11/098,952Filed 5 Apr 2005

Published

5 Oct 2006

Term ends

Not estimatedThe source records don’t support an estimate.

Classification7 codes

B60C 1/0016
Tyres characterised by the chemical composition or the physical arrangement or mixture of the composition: compositions of the tread
B60C 99/006
Subject matter not provided for in other groups of this subclass: computer aided tyre design or simulation
C08K 3/013
Characterized by their specific function: fillers, pigments or reinforcing additives
C08C 19/44
Reacting with metals or metal-containing groups: of polymers containing metal atoms exclusively at one or both ends of the skeleton

Abstract

Claims35

Dependent claims

A method of optimizing a tread compound, comprising:

a. providing a rubber composition comprising at least one functionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, wherein said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
and
c. calculating rubber composition factors from the set of tensile retraction curves, wherein the rubber composition factors comprise a trapped entanglements value (NE), a chemical crosslink value (NC), and a filler-filler-polymer interaction value (NF).

1 more element

A method of preparing an optimized tread compound, the method comprising:

a. providing a rubber composition comprising at least one functionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, wherein said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
c. calculating the molecular weight between chain restrictions (Mr) from the equation
M
r
=
ρ
⁢
⁢
RT
⁡
(
Λ
-
Λ
-
2
)
σ
,
for each maximum individual elongation used, wherein ρ is the compound density, σ is stress, R is the gas constant, T is temperature, and Λ is 1+Xε, wherein X is the Guth-Gold equation and the strain, ε, is (l−lset)/lset, wherein l is the specimen length at any point on the retraction curve, and lset is the specimen length after retraction to zero stress;
d. plotting a smooth curve from the data sets of Mr and maximum elongation that have all been adjusted to the same testing rate;
e. fitting the data from the tensile retraction curve to the equation
M
r
=
1
1
β
⁢
(
10
m
⁡
(
Λ
⁢
⁢
max
-
1
)
)
+
1
γ
⁢
(
10
n
⁡
(
Λ
max
-
1
)
)
+
1
M
C
+
S
⁡
(
Λ
max
-
1
)
wherein Mr and Λmax−1 are described above, and the parameters β, γ and Mc, and m, n and S, correspond to intercepts and slopes, respectively, for linearized segments of three regions of the curve represented by the equation above, to obtain values for the β, γ, and Mc intercepts;
f. varying filler content, state of cure, and presence of end-functionality and determining the effect of each β, γ, and Mc to isolate contributions resulting from trapped entanglements (NE), chemical crosslinks (NC), filler-filler-polymer interactions (NF), the number of end-functionality attachments to filler (NR);
and the probability π that an end is attached to the filler;
g. employing NR, NE, NC and NF to calculate the probability (π2) that a difunctional polymer is reacted at both ends;
and
h. providing an optimized tread compound.

74 more elements

A method of optimizing a tread compound, the method comprising the steps of:

a. providing a rubber composition comprising an end-difunctionalized polymer and at least one filler;
b. creating at least one set of tensile retraction curves, each set comprising at least two tensile retraction curves from the rubber composition, where said curves are generated from elongation values ranging from about 0.5% elongation to a maximum elongation of about 10% less than the elongation at break;
c. calculating the molecular weight between chain restrictions (Mr) from the equation
M
r
=
ρ
⁢
⁢
RT
⁡
(
Λ
-
Λ
-
2
)
σ
for each maximum individual elongation used wherein ρ is the compound density, σ is stress, R is the gas constant, T is temperature, and Λ is 1+Xε, wherein X is the Guth-Gold equation and the strain, ε, is (l−lset)/lset, wherein l is the specimen length at any point on the retraction curve, and lset is the specimen length after retraction to zero stress;
d. plotting a smooth curve from the data sets of Mr and maximum elongation after they have all been adjusted to the same testing rate;
e. statistically fitting a Mr=S(Λmax−1)+Mc line to the highest elongation region (Region I) by successively adding the next lowest elongation data set of the curve obtained in step (d), such that R (squared) is greater than 0.98;
f. subtracting the crosslink density (νe) predicted from the equation fitted to Region I from the measured νe corresponding to the remainder of the low elongation region of the data curve plotted in step (d) to obtain (Δνe);
g. plotting a smooth curve from the logarithm of Δνe of the data set vs. the remaining elongations;
h. statistically fitting a log Δνe=s(Λmax−1)+m line by starting at the highest remaining elongation region (Region II) and successively adding the next lowest elongation data set of the curve such that R (squared) is greater than 0.98;
i. subtracting the values of Δνe calculated from the equation fitted in Region II from the Δνe measured for the remainder of the low elongation region of the data set (ΔΔνe);
j. plotting a smooth curve from the logarithm of ΔΔνe determined in step (i) vs. the remaining elongations;
k. statistically fitting a log ΔΔνe=t(Λmax−1)+n starting with the highest remaining elongation region (Region III) by successively adding the next lowest elongation data set of the curve such that R (squared) is greater than 0.98;
l. calculating the total number of effective network strands, NT, from the number average molecular weight of the original polymer (Mn) and density (ρ), wherein NT=νeMn/ρ from each Mc intercepts of Region I;
m. plotting the NT for each filler level used vs. the concentration of accelerator [acc];
n. plotting the log ΔΔνe intercepts from Region III of the gum cured rubbers vs. [acc] and determining the molecular weight between entanglements, Me by statistically fitting the equation of y=dx2+ex+f wherein the zero [acc] intercept f is used to calculate Me= 1/10f;
o. calculating the trapped entanglements value for the cured unfilled polymer as
N
E
=
(
n
-
1
n
+
1
)
2
⁢
(
M
n
M
e
-
1
)
wherein n is the number of chemical bounds formed during cure;
p. plotting
N
T
=
(
n
-
1
)
+
(
M
n
M
e
-
1
)
⁢
(
n
-
1
n
+
1
)
2
vs. [acc] the value of n as a function of [acc] can be determined by fitting to the equation n=a[acc]b;
q. subtracting the sum value of NT from the filled value of NT to generate the contribution of the filler NF(H) to the cured rubber;
r. repeating the above steps with an α,ω-difunctional polymer and the equation NT=NC+NE+NF(func)+NR to account for the end group reacting with filler, NR, the change that this reaction causes in the contribution to the filler on crosslinking, NF(func), and the three different contributions of NE that account for trapping of entanglements;
wherein, for one and two end groups reacting with filler, the new equations become
N
T
,
1
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
⁢
(
n
n
+
1
)
2
+
1
⁢
⁢
and
⁢
⁢
N
T
,
2
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
+
2
,
respectively, and use the equation
N
T
,
0
-
N
C
=
N
F
⁡
(
func
)
+
(
M
n
M
e
-
1
)
⁢
(
n
-
1
n
+
1
)
2
where no polymer end groups react with filler;
s. calculating β= 1/10m from Region II as a measure of the filler contribution to the crosslinked network;
t. calculating the new NF(func) as the beta ratio of the non-functional polymer to the α,ω-difunctional polymer times the NF(H);
u. solving the equation weighted for the filler reaction of NT−NC=π2(NF(func)+NE,2+2)+2π(1−π)(NF(func)+NE,1+1)+(1−π)2 (NF(func)+NE,0) for the probability (π) that a chain end reacts with the filler;
and
v. optimizing the probability (π2) that a polymer has reacted at both ends with filler by selecting the type of functional group, filler type, accelerator type, mixing and curing conditions to give the lowest values for abrasion resistance and rolling resistance.

187 more elements

Dependencies are inferred from the claim text.

Method of optimizing a tire tread compound, and a tire tread compound made by said method

Life of this patent

Abstract

Claims35

Method of optimizing a tire tread compound, and a tire tread compound made by said method

Life of this patent

Abstract

Claims35