IP Library › Granted Patent US 12,546,693
Granted Patent B2
US 12,546,693 · App. 18/098,107 · Granted Feb 10, 2026

Determining intrinsic viscosity and Huggins constant of an unknown sample

Inventor: Steven P. Trainoff (Santa Barbara, CA)
Assignee: Wyatt Technology, LLC
G01N11/08G06F17/11
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,546,693
App. No.
18/098,107
Granted
Feb 10, 2026
Kind
B2
Abstract

The present disclosure describes a computer implemented method, a system, and a computer program product of determining intrinsic viscosity and Huggins constant of an unknown sample. In an embodiment, the method, system, and computer program product include, receiving specific viscosity values over time from a viscometer corresponding to a series of aliquots of an unknown sample injected into an instrument chain where the instrument chain includes the viscometer, calculating a total mass of each of the aliquots, calculating a first intermediate viscosity value of each of the aliquots, calculating a second intermediate viscosity value of each of the aliquots, and fitting the total mass, the first intermediate viscosity value, and the second intermediate viscosity value to a fitting, resulting in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample.

Claims (166)

1 . A computer implemented method comprising:

receiving, by a the computer system from a viscometer integrated into an instrument chain, specific viscosity values over time, η sp (t), from a viscometer,

wherein the specific viscosity values correspond to a series of aliquots of an unknown sample injected into the instrument chain,

executing, by the computer system, a set of logical operations calculating a total mass of each of the aliquots, m i , as a function of a volume of the each of the aliquots, v i , and a concentration of the each of the aliquots, c i ; wherein the total mass of each of the aliquots, mi, is further calculated by numerically integrating concentration detector signal values, cmeas(t), received from a concentration detector over a defined time interval corresponding to each aliquot as a first integral function;

executing, by the computer system, a set of logical operations calculating a first intermediate viscosity value of the each of the aliquots, I η i , as a second integral function of the received specific viscosity values, η sp (t), corresponding to the each of the aliquots;

executing, by the computer system, a set of logical operations calculating a second intermediate viscosity value of the each of the aliquots, I2η i , as a third integral function of the received specific viscosity values, η sp (t), corresponding to the each of the aliquots; and

executing, by the computer system, a set of logical operations fitting the total mass of the each of the aliquots, m i , the first intermediate viscosity value of the each of the aliquots, Iη i , and the second intermediate viscosity value of the each of the aliquots, I2η i , to a fitting function comprising the first integral function, a floating intrinsic viscosity of the unknown sample, [η], the second integral function, a floating Huggins constant of the unknown sample, K h , and the third integral function, resulting in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample, wherein the method is performed by a special-purpose system configured to analyze sensor data from physical laboratory instrumentation and the specific viscosity values are based on time-varying physical measurements.

2 . The method of claim 1 wherein the viscometer is a differential viscometer.

3 . The method of claim 1 wherein the total mass of the each of the aliquots, m i , is

m i =v i c i .

4 . The method of claim 1 wherein the second integral function is

I

⁢

η

i

=

∫

peak

,

i

η

sp

(

t

)

⁢

dt

.

5 . The method of claim 1 wherein the third integral function is

I

⁢

2

⁢

η

i

∫

peak

,

i

⁢

η

sp

2

(

t

)

⁢

dt

.

6 . The method of claim 1 wherein the fitting comprises a least squares fitting.

7 . The method of claim 6 wherein the least squares fitting comprises a non-linear least squares fitting algorithm executed by the computer system to fit the total mass of each of the aliquots, m i , to the fitting function comprising a multi-parameter fitting function comprising the floating intrinsic viscosity of the unknown sample, [η], and the floating Huggins constant of the unknown sample, K h .

8 . The method of claim 1 wherein the fitting function is

m

i

=

1

[

η

]

⁢

I

⁢

η

i

-

1

[

η

]

⁢

I

⁢

2

⁢

η

i

.

9 . The method of claim 1 further comprising

executing, by the computer system, a set of logical operations calculating a figure of merit, FOM, characterizing a contribution of K h to fitting, as a ratio function of K h , the second intermediate viscosity value of the each of the aliquots, I2η i , and the first intermediate viscosity value of the each of the aliquots, Iη i .

10 . The method of claim 9 wherein the ratio function is

FOM=( K h I 2η i )/ Iη i .

11 . The method of claim 1 further comprising

executing, by the computer system, a set of logical operations calculating a ratio of the first intermediate viscosity value of the each of the aliquots, Iη i , to the total mass of the each of the aliquots, m i ; and

displaying, by the computer system, a plot of the calculated ratio of the each of the aliquots versus the total mass, m i , of the each of the aliquots.

12 . A computer implemented method comprising:

receiving, by a computer system from a viscometer integrated into an instrument chain, specific viscosity values over time, η sp (t), from a viscometer,

wherein the specific viscosity values correspond to a series of aliquots of an unknown sample injected into the instrument chain,

wherein the instrument chain comprises the viscometer,

executing, by the computer system, a set of logical operations calculating a first intermediate viscosity value of the each of the aliquots, Iη i , as a second integral function of the received specific viscosity values, η sp (t), corresponding to the each of the aliquots;

executing, by the computer system, a set of logical operations calculating a second intermediate viscosity value of the each of the aliquots, I2η i , as a third integral function of the received specific viscosity values, η sp (t), corresponding to the each of the aliquots; and

executing, by the computer system, a set of logical operations fitting a total mass of the each of the aliquots, m i , the first intermediate viscosity value of the each of the aliquots, Iη i , and the second intermediate viscosity value of the each of the aliquots, I2η i , to a fitting function comprising the first integral function, a floating intrinsic viscosity of the unknown sample, [η], the second integral function, a floating Huggins constant of the unknown sample, K h , and the third integral function, resulting in a calculated intrinsic viscosity of the unknown sample and a calculated Huggins constant of the unknown sample, wherein the method is performed by a special-purpose system configured to analyze sensor data from physical laboratory instrumentation and the specific viscosity values are based on time-varying physical measurements, and wherein the total mass of each of the aliquots, mi, is further calculated by numerically integrating concentration detector signal values, cmeas(t), received from a concentration detector over a defined time interval corresponding to each aliquot as a first integral function.

13 . The method of claim 12 wherein the viscometer is a differential viscometer.

14 . The method of claim 12 wherein the second integral function is

I

⁢

η

i

=

∫

peak

,

i

η

sp

(

t

)

⁢

dt

.

15 . The method of claim 12 wherein the third integral function is

I

⁢

2

⁢

η

i

∫

peak

,

i

⁢

η

sp

2

(

t

)

⁢

dt

.

16 . The method of claim 12 wherein the fitting comprises a least squares fitting.

17 . The method of claim 16 wherein the least squares fitting comprises a non-linear least squares fitting algorithm executed by the computer system to fit the total mass of each of the aliquots, m i to the fitting function comprising a multi-parameter fitting function comprising the floating intrinsic viscosity of the unknown sample, [η], and the floating Huggins constant of the unknown sample, K h .

18 . The method of claim 12 wherein the fitting function is

m

i

=

1

[

η

]

⁢

I

⁢

η

i

-

1

[

η

]

⁢

I

⁢

2

⁢

η

i

.

19 . The method of claim 12 further comprising

executing, by the computer system, a set of logical operations calculating a figure of merit, FOM, characterizing a contribution of K h to fitting, as a ratio function of K h , the second intermediate viscosity value of the each of the aliquots, I2η i , and the first intermediate viscosity value of the each of the aliquots, Iη i .

20 . The method of claim 19 wherein the ratio function is

FOM=( K h I 2η i )/ Iη i .

21 . The method of claim 12 further comprising

executing, by the computer system, a set of logical operations calculating a ratio of the first intermediate viscosity value of the each of the aliquots, Iη i , to the total mass of the each of the aliquots, m i ; and

displaying, by the computer system, a plot of the calculated ratio of the each of the aliquots versus the total mass, m i , of the each of the aliquots.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 15, 2023
From: TRAINOFF, STEVEN P.
To: WYATT TECHNOLOGY, LLC
Reel/Frame 064597/0588 →
Continuity (2)
Continuation In Part 16840478 · Apr 6, 2020
Related Publication 20230152197A1 · May 18, 2023
References Cited (12)
US 11555770B2 · Trainoff · 2023 [cited by examiner]
US 20170189444A1 · Ismagilov · 2017 [cited by examiner]
US 20170198575A1 · Sandor · 2017 [cited by examiner]
US 20180196778A1 · Glaser · 2018 [cited by examiner]
US 20200040141A1 · Kornfield · 2020 [cited by examiner]
US 20200095850A1 · Preux · 2020 [cited by examiner]
US 20210310921A1 · Trainoff · 2021 [cited by applicant]
JP 2005091368A · 2005 [cited by applicant]
International Search Report and Written Opinion in PCT/US2021/026061 mailed on Jun. 29, 2021. [cited by applicant]
International Search Report and Written Opinion in PCT/US2024/010872 mailed on May 16, 2024. [cited by applicant]
Roche, et al. “Towards an improved prediction of concentrated antibody solution viscosity using the Huggins coefficient” Journal of Colloid and Interface Science, 607, pp. 1813-1824, Sep. 4, 2021. [cited by applicant]
International Preliminary Report on Patentability in PCT/US2024/010872 mailed on Jul. 31, 2025. [cited by applicant]