Chevron Oronite Company LLC

Chevron Research & Technology Company

Chevron Chemical Company LLC

Robert H Wollenberg

Thomas J Balk

Richard J Nelson

Curtis Bay Campbell

John McDonald

Susanne G Ruelas

Steven Gale Lockett

Kathryn E Matera

William F King

Jeremy Cantor

Methods for determining deposit formation tendencies for a plurality of fluid samples of different compositions is provided. Each sample includes fuel additive compositions containing one or more fuel additives or fuel compositions containing one or more fuels and one or more fuel additives. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of fuel compositions are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

High throughput screening methods for fuel compositions

Methods for determining the compatibility of a plurality of fluid samples of different lubricating oil compositions with elastomers is provided. Each sample includes one or more base oils of lubricating viscosity and one or more lubricating oil additives. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil compositions are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

High throughput screening methods for lubricating oil compositions

A method for determining storage stability for a plurality of fluid lubricant samples of different lubricating oil compositions is provided. Each sample includes a combination of one or more base oils and one or more lubricating oil additives. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil additives or lubricating oil compositions containing such additives is generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

A method for determining oxidation stability for a plurality of different lubricating oil composition samples is provided. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil compositions is generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

Method for determining deposit formation tendencies for a plurality of fluid samples of different compositions is provided. Each sample includes one or more lubricating oil compositions containing at least one or more base oils of lubricating viscosity and one or more lubricating oil additives. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil compositions are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

A method for determining storage stability for a plurality of fluid lubricant samples of different compositions is provided. Each sample includes one or more lubricating oil additives, or a combination of one or more lubricant base oils and one or more lubricating oil additives. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil additives or lubricating oil compositions containing such additives are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

A high throughput preparation of a plurality of different lubricating oil compositions for combinatorial libraries and subsequent high throughput screening for lubricant performance is provided. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil compositions are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

High throughput preparation of lubricating oil compositions for combinatorial libraries

A combinatorial lubricating oil composition library is provided including at least a plurality of different lubricating oil compositions comprising (a) a major amount of a base oil of lubricating viscosity and (b) at least one lubricating oil additive. Methods for preparing same are also provided.

Combinatorial lubricating oil composition libraries

The present invention is directed to a novel process for making Group II metal overbased sulfurized alkylphenols, which process uses alkylene carbonate as both a source of carbon dioxide and alkylene glycol. In particular, under the reaction conditions using ethylene carbonate, carbonation time is reduced to about one quarter the time taught in the prior art to make Group II metal overbased sulfurized alkylphenol compositions. The present invention is also directed to a detergent-dispersant additive composition comprising a Group II metal overbased sulfurized alkylphenols, wherein the Group II metal overbased sulfurized alkylphenols have a reduced color as measured by ASTM Test No. D 6045 and an increased hydrolytic stability as measured by a modified ASTM Test No. 2619. The present invention is also directed to a process using ethylene carbonate or alkyl-substituted ethylene carbonate and water for delivering in situ equimolar quantities of ethylene glycol and carbon dioxide for use as reactants in chemical reactions.

Process for making Group II metal overbased sulfurized alkylphenols

Method for determining dispersancy performance for a plurality of fluid samples of different compositions is provided. Each sample includes one or more base oils of lubricating viscosity and one or more lubricating oil additives and a predetermined amount of an oil-insoluble material. The methods can advantageously be optimized using combinatorial chemistry, in which a database of combinations of lubricating oil compositions are generated. As market conditions vary and/or product requirements or customer specifications change, conditions suitable for forming desired products can be identified with little or no downtime.

This invention is directed to a novel process for making Group II metal carbonated, overbased Mannich condensation products of alkylphenols, which process uses ethylene carbonate as both a source of carbon dioxide and ethylene glycol. In particular, under the reaction conditions using ethylene carbonate in the present invention, carbonation and overbasing Mannich condensation products of alkylphenols is possible while at the same time the viscosity of the carbonated, overbased Mannich condensation products of alkylphenols remains within acceptable levels, typically under 1000 cSt at 100&#xb0; C. The present invention is also directed to carbonation of Mannich condensation products of alkylphenols using a C-Calkaline glycol and carbon dioxide. The present invention is also directed to a detergent-dispersant antioxidant additive composition comprising Group II metal carbonated, overbased Mannich condensation products of alkylphenols, wherein the Group II metal carbonated, overbased Mannich condensation products of alkylphenols have a COto Ca ratio of at least 0.01.

Process for making group II metal carbonated, overbased Mannich condensation products of alkylphenols

A method and system of transforming a product development process to reduce time in bringing a product to market through high throughput experimentation and advanced statistics and informatics, to transform the product development to a level of higher correlation with engine tests, and to develop better commercial products. This is achieved by modeling in Silico a plurality of component molecular models; deriving in Silico molecular characteristics (descriptors) for each of the plurality of compiled molecular models; creating at least one combinatorial library database record for each of the formulations, the at least one record having a plurality fields for storing information about compositional characteristics; receiving specification requirements for a lubricating oil composition; selecting from a database entries corresponding to compositions having specifications comparable to the received specification requirements; formulating a new lubricating oil composition to comply with received specification requirements; testing the new lubricant oil for compliance with received specification requirements; repeating the selecting, formulating, and testing steps until compliance with received specification requirements is achieved; and correlating the new lubricating oil composition to actual engine performance.

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Orinda, CA, United States of America

Robert H Wollenberg