The seven stages of chemical technology from idea to industrialization (Issue 4/100) -- Unintended observations in the laboratory

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This post was last edited by xiouxingzhe on 2026-6-23 at 15:21. Seven stages of chemical technology from idea to industrialization (Issue 4/100). One source of inspiration: unexpected observations from experiments. Dear friends: Hello everyone! In the previous issue, we discussed the nature of inspiration—it isn’t something that waits to be found; it emerges from collisions within a prepared mind. In this issue, we enter the first source of inspiration: accidental observations from experiments. Those who have spent time in the laboratory may have had this experience: you conduct a set of experiments, and the results do not match those reported in the literature, nor do they match those from previous attempts. What’s the first thing that comes to mind at that moment? I guess it’s most likely three words—“Failed again”. But what I want to say is that truly valuable discoveries are sometimes hidden in these “failures”. I. Start the experiment with clear expectations. To detect anomalies, one must first know what is “normal”. Many people, when conducting experiments, have only a vague idea in mind – “I’ll give it a try to see if this condition works.” In this state, your expectations regarding the experiment are not clear enough, and it is also difficult to identify abnormalities when they occur. That’s how it was when I first started in this field. Before conducting an experiment, I don’t really write a plan; after it’s done, I check the yield – if it’s high I’m happy, if it’s low I’m frustrated, and then I adjust a parameter and try again. As for “why high and why low,” it is rarely explored in depth. Later, my mentor said something to me that I still remember well: “If you don’t even write down what you want to see today, how will you know what you’ve seen tomorrow?” ” Later, I developed a habit: before starting each experiment, I would write down three expectations for that experiment on a small piece of paper. What is the feed amount, temperature, and pressure? What is the approximate range for the product distribution? How long is the reaction time expected to be? Write it down on paper, don’t keep it in your mind. The function of this small piece of paper is far more than just “helping you detect abnormalities”. First, it transforms expectations from vague feelings into real data. When the experimental results deviate from expectations, the deviation is quantifiable and visible. You don’t just feel that “something seems off,” but you can say: “At this temperature, the yield of product A should be between 85% and 88%, but in reality it’s only 72%, which is a deviation of over ten percentage points.” ” Second, the accumulated records of expected deviations constitute a very useful data asset. For the preparation of subsequent process packages and the determination of operating windows, references can often be found in these early records. Third, the act of writing on small pieces of paper forces you to think carefully before taking action: What exactly do I want to prove through this experiment? When you have to write down three expectations, things that are not clear become apparent. I later learned that some people call this method an “experimental expectation card”. The format does not need to be complicated; it should generally include several items: experiment number, purpose of the experiment, reaction conditions, specific expectations (conversion rate, selectivity, possible phenomena), actual results, and analysis of deviations. Over the years, I’ve collected quite a few such cards; when I flip through them from time to time, I can discover some patterns that I hadn’t noticed before. II. Maintain sensitivity to anomalies throughout the process. While the experiment is running, what are you focusing on? Most people focus only on the one metric they care about most—the yield. The yield is obtained; whether it’s good or not, the experiment is then complete. But the truly valuable anomalies are often not in the indicator you are focusing on. It might be during the reaction process—the timing of the color change isn’t as expected. It might be related to temperature control – at a certain stage, the amount of heat that needs to be removed is much greater than estimated. It might be in the discharge state – there are precipitates or bubbles that you didn’t expect to appear. My own experience is: use all your senses to observe. Color, odor, temperature changes, bubbles, precipitation, viscosity—any phenomenon that doesn’t match your expectations is worth recording. I’ve seen it more than once: signals that were initially regarded as “noise” later turned out to be key clues for understanding the entire reaction system. There is an aspect of observation that is easily overlooked: the dimension of time. Don’t just look at the final result; focus on the process of the reaction. How long did it take for the temperature to rise from room temperature to the reaction temperature? Is the temperature rise curve smooth or does it have an inflection point? Was there an instantaneous temperature rise at the moment of feeding? When does the backflow start to form? The phenomena on these timelines contain more information than the final yield figure. When I was young, an experienced teacher told me something that I still remember to this day: \"Pay attention to those phenomena that you think ‘shouldn’t’ exist.\" Scientific discoveries often lie hidden in these ‘should nots’. ” III. Record first, then ask questions; don’t rush to label it as a “failure.” This is the step that I think is most easily overlooked. When an anomaly occurs, a person’s first reaction is usually “the experiment failed.” Then start looking for your own problem—was it an operational error? Is the reagent expired? Is the device broken? I was the same way at that time. But later, I gradually learned one thing: anomalies do not equal failure. An anomaly is simply a \"result that does not meet expectations.\" It may stem from an operational error, or it may be due to your insufficient understanding of this system. The latter case refers to new discoveries. So, when an exception occurs, I have set out a three-step procedure for myself. The first step is to record. Record all details of the abnormal phenomenon: When did it occur? What are the specific phenomena? What were the values of temperature, pressure, and feed rate at that time? Keep the records detailed enough so that you can reconstruct that scene in your mind in the future. Step two, reproduce. If conditions permit, conduct a repeat experiment immediately to confirm whether this anomaly can be reproduced. Once might be a coincidence, but twice is a signal. This step is crucial — I’ve seen people treat a random mistake as a major discovery, only to realize months later that it was just a blunder. Step three: ask follow-up questions. Ask yourself: What does this exception mean? If it’s true, what adjustments does that require to my previous understanding? After completing these three actions, then determine whether it is an operational error or a new phenomenon. The order must not be disrupted—first record, then reproduce, and finally ask questions. IV. Two Classic Cases: There are two famous cases of “accidental observations” in history that are often cited; although they are not related to the chemical industry, the principles behind them are similar. One is penicillin. In 1928, while cleaning his laboratory bench, Fleming noticed that no bacteria grew around the mold in one of the petri dishes. This was not an experiment he carried out on purpose—he was originally studying the cultivation of staphylococci. He just took one extra look while cleaning up. In that glance, he noticed something unusual: the bacteria around the mold were no longer growing. He didn’t throw away that \"contaminated\" petri dish right away; instead, he stopped, recorded this phenomenon, and then asked a question: Did the mold release some substance that killed the bacteria? Penicillin was born out of this “accident”. The other one is Teflon. In 1938, Plankert was conducting an experiment on tetrafluoroethylene gas. He opened the valve of a gas cylinder, but no gas came out. A technician’s first reaction might be, “The gas cylinder is leaking; this experiment was done for nothing.” But Plankert didn’t. He weighed the gas cylinder – its weight hadn’t decreased. He sawed open the gas cylinder and found a layer of white waxy substance inside—tetrafluoroethylene had polymerized on its own. This “accidental” polymer later became polytetrafluoroethylene. These two stories have one thing in common: neither was obtained in a planned experiment. In the face of abnormal phenomena, some people choose to stop and observe, rather than rushing past it by considering it an \"experiment failure\". Of course, there are many similar examples in the chemical industry as well. I have experienced some of these myself, and I will go into detail about them when discussing specific cases later. Preview for the next issue: Issue 5 – Another gateway to inspiration: Insights from theoretical reasoning. Is it possible to find innovative directions without conducting experiments? Based on established scientific principles, systematically conducting \"if... then...\" type reasoning can sometimes be more efficient than heading to the laboratory blindly. Next time, I’ll talk about how I use a few pieces of paper and a pen to rule out some unviable ideas in advance. Table of Contents link: Seven-Stage Model of Chemical Technology from Idea to Industrialization (Issue 100) – Table of Contents (updated in real time)