Author:Train, Tyler
  1. INTRODUCTION 193 II. PARKER V. FLOOK 194 A. Catalytic Conversion 196 B. Smooth Adjustments for Transient States 197 C. Flook's Claimed Method 199 III. DIAMOND v. DIEHR 201 A. Vulcanization (i.e. Rubber Curing) 202 B. Tire Curing 203 C. Diehr's Claimed Method 204 IV. FLOOK VERSUS DIEHR 207 V. CONCLUSION 209 I. INTRODUCTION

    As far back as the 1970s, the Supreme Court has wrestled with the issue of whether patents should be granted for computer software and mathematical algorithms. By statute, 35 U.S.C. [section]101 defines patentable subject matter rather broadly as "any new and useful process, machine, manufacture, or composition of matter." (1) However, the Supreme Court tailored this definition through three landmark decisions, which have colloquially become known as the '"patent eligibility trilogy."' (2) In the first of its three decisions, Gottschalk v. Benson, the Supreme Court carved an exception out of Section 101 determining that "[p]henomena of nature, though just discovered, mental processes, and abstract intellectual concepts are not patentable." (3) The Court further refined this exception in its third decision, Diamond v. Diehr, stating, "an algorithm, or mathematical formula, is like a law of nature, which cannot be the subject of a patent." (4) While the Court's intention may have been to add clarity to a broad statute, the patent eligibility trilogy has long been the source of confusion and frustration among practitioners. (5) Further contributing to the confusion has been the seemingly inconsistent holdings in the latter two decisions, Diehr and Parker v. Flook. (6) Much has been written in response to this confusion, from demanding the Court to perform "judicial housecleaning" (7) to suggesting an alternative test for determining patent eligible subject matter. (8) This article also intends to respond to the frustration, but from a technical perspective. It has become common when discussing these decisions for authors to take a cursory look at the underlying technical aspects of the cases and advance straight into the legal aspects. Conversely, this article will give a brief history of the well-documented legal progression in order to go in-depth exploring the technology behind the two contrasting holdings in Flook and Diehr in the aims of furthering the discussion and understanding of the Court's precedent.


    In 1978, the Supreme Court, building on the precedent it set six years before in Benson, held in Flook that a mathematical algorithm was not patentable. (10) Giving rise to the case, a year prior, the United States Court of Customs and Patent Appeals ("CCPA") overturned the denial by the United States Patent and Trademark Office ("USPTO") to grant Dale R. Flook's ("Flook") patent application to protect a method for updating alarm limits during a catalytic conversion of hydrocarbons." The CCPA decided that Benson did not exclude Flook's application from patentability because it would not '"wholly pre-empt the mathematical formula.'" (12) The Supreme Court granted review, and Flook defended that his application did not claim an entire mathematical formula, but rather a post-solution application of the formula to produce a specific activity - the adjustment of alarm limits. (13) While the Supreme Court acknowledged that "a process is not unpatentable simply because it contains a law of nature or a mathematical algorifhm[,]" (14) it disagreed with Flook's argument opining that each aspect of his method was established and well known. (15) This was an important decision coming off the heels of the same holding in Benson, because it seemed as though the Supreme Court was unwilling to extend patent protection to computer software applications. (16) However, as discussed infra, the Court would come to a different conclusion three years later in Diehr. (17) The remainder of this section will focus on the technology behind Flook's method for updating alarm limits during a catalytic conversion.

    1. Catalytic Conversion

      One of the most common types of catalytic conversions occurs in the catalytic converter of a car's exhaust system. (1) This converter will serve as a simple example to explain how catalytic conversion operates. During the combustion process in a car's engine, the engine emits a gas mixture of harmful pollutants consisting of carbon monoxides (CO), hydrocarbons (HC), and nitrogen oxides (N[O.sub.X]). (19) The exhaust system sends this gas mixture through the catalytic converter before emitting them into the air so that the pollutants can be converted into a mixture of less harmful gasses consisting of nitrogen gas ([N.sub.2]), carbon dioxide (C[O.sub.2]), and water vapor ([H.sub.2]O). (20)

      As can be implied by its name, a catalytic converter operates through the use of two catalysts - an oxidation catalyst and a reduction catalyst each coated with metal palladium, platinum, and/or rhodium - that accelerate the chemical reactions for converting the harmful pollutants into benign emissions. (21) As the pollutants pass through the reduction catalyst, the N[O.sub.X] molecules break down into [N.sub.2] and [O.sub.2] by (22)

      2NO [right arrow] [N.sub.2] + [O.sub.2]; 2N[O.sub.2] [right arrow] [N.sub.2][O.sub.2] + [O.sub.2]

      Then as they continue to pass through the oxidation catalyst, the CO and HC molecules react with [O.sub.2] molecules in the converter to create [H.sub.2]O and C[O.sub.2] by (23)

      2CO + [O.sub.2] [right arrow] 2C[O.sub.2]; C[H.sub.4] + 2[O.sub.2] [right arrow] 2[H.sub.2]O + C[O.sub.2]

      Although the process is never perfect, and some harmful gasses are still emitted, the catalytic converter is meant to greatly reduce the total amount of harmful emissions from a car's engine. (24) A measure of a converter's efficiency is how close the air-to-fuel ratio is to the stoichiometric point. (25) In theory, at this point all of the oxygen in the system would burn up all of the fuel and the final emissions would contain no pollutants. (26) However in practice, a converter's efficiency varies based on changes in process variables such as temperature and pressure. (27) For this reason, cars are equipped with an oxygen sensor to detect and adjust the oxygen pressure in the exhaust. (28) Further, a problem arises when starting a car after it has cooled down, because the catalytic conversion must be performed at high temperatures. (29) Therefore, in some vehicles that take a while to heat up such as diesel trucks, their converters are far less effective at reducing pollution upon start up. (30)

    2. Smooth Adjustments for Transient States

      Due to the importance of the levels of these process variables, some catalytic converters will have alarm limits set around the normal operating window of the system to alert whenever a variable measurement rises too high or drops too low for the converter to be operating efficiently. (31) Setting fixed limits would be effective if the system constantly operated in a steady state, (32) but recurrent transient states (33) require these limits to be updated periodically. Without such updates, fixed limits would encounter too much noise (34) to function properly. (35) The need for updating alarm limits had been well established by the time Flook applied for his patent, but Flook's method contained an arguably novel mathematical algorithm for calculating the updated limit. (36) The method was meant to help a system in transient state make smooth adjustments to its updated limits by factoring in its previous alarm limits. (37) To revisit the example of a catalytic converter in the exhaust system of a car, when the car is started its converter is in a transient state until it heats up to an efficient steady state.[TM] The converter's initial temperature would fall below any normal operating window for a catalytic converter causing a fixed alarm to sound anytime the car was turned on. (39) Flook's algorithm took this into account by ramping up the limits as the converter was heating up. (40) Therefore, an alarm would only sound for abnormal inefficient or...

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