标签: cells

I think I may have had an epiphany, but I can’t tell for sure because (a) I can’t spell epiphany and (b) I'm not entirely sure what one is. All I know is that whenever I look in a mirror I feel a sense of awe and wonder that is hard to put into words.   What? No! Don’t be silly, I'm not talking about my legendary good looks. It would be immodest of me to do so, and I pride myself on my humility. I'm talking about something much deeper and more meaningful (as hard as this may be for you to believe).     Actually, this has been building for some time. Out of all the books I've read, and I've read a lot of books, one that truly boggled my mind and that stays with me to this day is Wetware: A Computer in Every Living Cell by Dennis Bray.   Dennis does a masterful job. He starts by describing how a single-celled creature like an amoeba functions, including how it creates proteins and how interactions between different proteins can be used to detect external stimuli, perform "computations," make "decisions," and initiate actions. For example, even though an amoeba comprises only a single cell, it can "crawl" around, hunt for food, and respond to external stimuli like lights and sounds and smells … all without muscles or a nervous system.     Next we move to colonies of single-celled creatures that use proteins to detect each other's presence and to communicate. This leads us to simple multi-celled creatures, in which the different cells forming the organism manage to communicate with each other so as to achieve a common goal.   All of which leads us to the current pinnacle of evolution as we know it, which would be me. Well, you too, of course, but mostly me. (Hey, it's my epiphany we're talking about here!)   My head is buzzing with the amazing things we've discovered, such as how the DNA in our cells actually includes virus DNA. (Approximately 8% of the human genome is made up of retrovirus DNA in our genes.) Or the fact that the number of bacterial cells in our bodies outnumber our human cells by a factor of 10 to 1. (Bacterial cells are very much smaller than human cells. The combined weight of all the bacterial cells is approximately 3 lb in an average adult human being.)   And then we have epigenetics, in which the underlying DNA doesn’t change, but small chemical groups and proteins can attach themselves to the DNA and affect gene expression (i.e., which genes are active or inactive). This is one of the mechanisms behind the way in which our cells differentiate themselves into skin, muscles, nerves, etc. More recently, it's been recognized that an organism's epigenome can be modified by changes in its external environment, and that these changes can passed down to that organism's offspring, all without mutating the underlying DNA. As an aside, I would also highly recommend Life's Ratchet: How Molecular Machines Extract Order From Chaos by Peter M. Hoffmann. One of questions that has baffled philosophers and scientists since time began is how could life arise from lifelessness. Life's Ratchet explains how inanimate matter can spontaneously construct complex processes such as those inherent to living systems.     Have you ever seen animations showing how the molecular mechanisms in cells function? These animations give the impression that everything is orderly and peaceful inside the cell, and that the individual molecular machines are quietly trundling around performing their tasks without a care in the world. In reality, at the molecular level, the inside of a cell is like the heart of a hurricane. The molecular machines have to do things like transcribing DNA and creating proteins in a maelstrom of activity. Once again, Life's Ratchet provides mind-boggling insights into how all of this works.   But, as is so often the case when I start to waffle on about something, we digress … The other day, after quaffing a pint or three of a rather robust beer that was not without a sense of humor, I was standing in front of a toilet having a pee when I came to contemplate the myriad cells forming my bladder.   Whichever way you look at it, these stalwart fellows don’t have the most glamorous of jobs, but they plow on performing their allotted task without complaint for the good of the rest of us (by which I mean the rest of the cells forming my body). This isn’t a one-way street, of course. I think it's safe to say that the cells forming the bladder would look a tad foolish if they weren't backed up by the rest of us in turn.   The point of all this is that each of the trillions of cells in my body (estimates range between 15 and 70 trillion, depending on who you are talking to and how you count them) can be considered to be a separate entity. When you come to think about it, the fact that all of these little rascals manage to play together nicely and march to the same metaphorical drum beat to "make me" is absolutely mind-boggling.   I'm sure that some people simply don’t think about this at all. They just perceive their bodies as being a single entity and focus on other things. Contrariwise, I'm pretty confident that other people would say that I'm stating the obvious.   I guess this is where the epiphany part comes in. I just have an overwhelming sense of wonder about how this all hangs together: the fact that I started as a single cell that divided and divided, and that each of the subsequent cells communicated with others and elected (or were guided) to adopt different functions. I also wonder at the fact that the cells forming my body communicate with the others using such an amazing variety of mechanisms. Cells in proximity to each other communicate by passing proteins back and forth. Other cells forming remote organs communicate with the rest of the body using signaling molecules like hormones.   My nerve cells are also sending electrical impulses throughout my body, including those neurons forming my brain, which I would like to go on the record as saying is one of my three favorite organs.   Am I just rambling on here? Is it just me, or are you also sometimes washed over by a wave of wonder when you come to contemplate how truly amazing I am we all are?    

For about a year now, I have on-going experiments to identify how coin cells behave. This was motivated by what I consider outrageous claims made by a number of MCU vendors that their processors can run for several decades from a single CR2032 cell. Some vendors take their MCU’s sleep currents and divide those into the battery’s 225 mAh capacity to get these figures. Of course, no battery vendor I’ve found specifies a shelf life longer than a decade (at least one was unable to define “shelf life”) so it’s folly, or worse, to suggest to engineers that their systems can run for far longer than the components they’re based on last. Conservative design means recognizing that ten years is the max life one can expect from a coin cell. In practice, even that will not be achievable. There’s also a war raging about which MCUs have the lowest sleep currents. Sleep current is, to a first approximation, irrelevant. But how do coin cells really behave in these low-power applications? I’ve been discharging CR2032s with complex loads applied for short periods of time and have acquired millions of data points.   My CR2032 experiment. A small ARM controller applies various loads to batteries being discharged and logs the results. The following results are for 42 batteries from Duracell, Energizer, and Panasonic. For each vendor I ran two groups of cells, each group purchased months apart from distributors located in distant states, in hopes that these represent different batches. (The devices are not marked with any sort of serial or batch numbers). First, the weird part. Our local grocery store sells these cells for up to $5 each. Yet Digi-Key only wants $0.28 for a Panasonic and $0.40 for an Energizer – in singles. Duracells are harder to find from commercial distributors, but I paid about a buck each from on-line sources (e.g., Amazon). I found little battery-to-battery variability (other than one obviously bad Panasonic and one bad Duracell), little vendor-to-vendor difference, and likewise different batches gave about the same results. What parameters matter? Chiefly, capacity (how many milliamp hours one can really get from a cell), and internal resistance, which varies with capacity used. All of the vendors say “dead” is at 2.0 volts. The following graph shows the average voltage for the batteries from each vendor, as well as the worst-case voltage from each vendor, as they discharge at a 0.5 mA rate. The curve ascending from left to right is the cumulative capacity used. By the time 2.0 volts is reached the capacity variation is in the noise. I found it averaged 233 mAh with a standard deviation between all results of 5 mAh. Energizer and Duracell’s datasheets are, uh, a bit optimistic; Panasonic says we can expect to get 225 mAh from a cell, which seems, given this data, a good conservative value to use.   Battery discharge data But in practice you won’t get anything near that 225 mAh. As cells discharge, their internal resistance (IR) goes up. Actually, this is not quite correct, despite the claims of all of the published literature I have found. Other results I’ll report on in a later column shows that there’s something more complex than simple resistance going on, but for now IR is close enough. The next chart shows average IR for each vendor’s products, plus the IR’s standard deviation. Internal resistance and its standard deviation So what does this all mean to a cautious engineer? The IR grows so quickly that much of the battery’s capacity can’t be used! First, the average IR is not useful. Conservative design means using worst case figures, which we can estimate using the measured standard deviation. By using three sigma our odds of being “right” are .997. The following graph combines the IR plus three sigma IR to show what voltage the battery will deliver, depending on load. Voltage delivered from battery depending on load If a system, when awake, draws just 10 mA, 88% of the battery’s capacity is available before the voltage delivered to the load drops to 2.0. It’s pretty hard to build a useful system that needs only 10 mA. Some ultra-low-power processors are rated at 200 uA/MHz with a 48 MHz max – almost 10 mA just for the CPU. With higher loads, like any sort of communications, things get much worse. Bluetooth could take 80 mA, and even Bluetooth LE can suck nearly 30 mA. At 30 mA only 39% of the battery’s rated capacity can be used. An optimist might use two sigma and suffer from 5% of his system not working to spec, but that only increases the useful capacity to 44%. The battery will not be able to power the system long before it is really “dead,” and long before the system’s design lifetime. And long before the time MCU vendors cite in their white papers. (Some MCUs will run to 1.8 volts, so vendors might say my cutoff at 2.0 is unfair. Since battery vendors say that 2.0 is “dead”, I disagree. And, even if one were to run to 1.8V there’s less than a 5% gain in useful capacity.)

I worked on some experiments to determine how coin cells behave. This was motivated by what I consider outrageous claims made by a number of MCU vendors that their processors can run for several decades from a single CR2032 cell. Some vendors take their MCU’s sleep currents and divide those into the battery’s 225 mAh capacity to get these figures. Of course, no battery vendor I’ve found specifies a shelf life longer than a decade (at least one was unable to define “shelf life”) so it’s folly, or worse, to suggest to engineers that their systems can run for far longer than the components they’re based on last. Conservative design means recognizing that ten years is the max life one can expect from a coin cell. In practice, even that will not be achievable. There’s also a war raging about which MCUs have the lowest sleep currents. Sleep current is, to a first approximation, irrelevant. But how do coin cells really behave in these low-power applications? I’ve been discharging CR2032s with complex loads applied for short periods of time and have acquired millions of data points.   My CR2032 experiment. A small ARM controller applies various loads to batteries being discharged and logs the results. The following results are for 42 batteries from Duracell, Energizer, and Panasonic. For each vendor I ran two groups of cells, each group purchased months apart from distributors located in distant states, in hopes that these represent different batches. (The devices are not marked with any sort of serial or batch numbers). First, the weird part. Our local grocery store sells these cells for up to $5 each. Yet Digi-Key only wants $0.28 for a Panasonic and $0.40 for an Energizer – in singles. Duracells are harder to find from commercial distributors, but I paid about a buck each from on-line sources (e.g., Amazon). I found little battery-to-battery variability (other than one obviously bad Panasonic and one bad Duracell), little vendor-to-vendor difference, and likewise different batches gave about the same results. What parameters matter? Chiefly, capacity (how many milliamp hours one can really get from a cell), and internal resistance, which varies with capacity used. All of the vendors say “dead” is at 2.0 volts. The following graph shows the average voltage for the batteries from each vendor, as well as the worst-case voltage from each vendor, as they discharge at a 0.5 mA rate. The curve ascending from left to right is the cumulative capacity used. By the time 2.0 volts is reached the capacity variation is in the noise. I found it averaged 233 mAh with a standard deviation between all results of 5 mAh. Energizer and Duracell’s datasheets are, uh, a bit optimistic; Panasonic says we can expect to get 225 mAh from a cell, which seems, given this data, a good conservative value to use.   Battery discharge data But in practice you won’t get anything near that 225 mAh. As cells discharge, their internal resistance (IR) goes up. Actually, this is not quite correct, despite the claims of all of the published literature I have found. Other results I’ll report on in a later column shows that there’s something more complex than simple resistance going on, but for now IR is close enough. The next chart shows average IR for each vendor’s products, plus the IR’s standard deviation. Internal resistance and its standard deviation So what does this all mean to a cautious engineer? The IR grows so quickly that much of the battery’s capacity can’t be used! First, the average IR is not useful. Conservative design means using worst case figures, which we can estimate using the measured standard deviation. By using three sigma our odds of being “right” are .997. The following graph combines the IR plus three sigma IR to show what voltage the battery will deliver, depending on load. Voltage delivered from battery depending on load If a system, when awake, draws just 10 mA, 88% of the battery’s capacity is available before the voltage delivered to the load drops to 2.0. It’s pretty hard to build a useful system that needs only 10 mA. Some ultra-low-power processors are rated at 200 uA/MHz with a 48 MHz max – almost 10 mA just for the CPU. With higher loads, like any sort of communications, things get much worse. Bluetooth could take 80 mA, and even Bluetooth LE can suck nearly 30 mA. At 30 mA only 39% of the battery’s rated capacity can be used. An optimist might use two sigma and suffer from 5% of his system not working to spec, but that only increases the useful capacity to 44%. The battery will not be able to power the system long before it is really “dead,” and long before the system’s design lifetime. And long before the time MCU vendors cite in their white papers. (Some MCUs will run to 1.8 volts, so vendors might say my cutoff at 2.0 is unfair. Since battery vendors say that 2.0 is “dead”, I disagree. And, even if one were to run to 1.8V there’s less than a 5% gain in useful capacity.)