Lattice Power Calculator Download

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Thedigital/FPGA section will need to be calculated using the Lattice Power Calculator software. This software can be launched from the FPGA Logic window in PAC-Designer, under the tools->Power Calculator menu item. Alternatively, the Power Calculator can be launched from Lattice Diamond FPGA software. For more details on working with the power calculator and the FPGA section of Platform Manager, see this technical note: Power Estimation and Management for MachXO Devices. This technical note covers the basics of working with the Lattice Power Calculator and can be directly applied to the Platform Manager FPGA.

You can either construct a Born-Haber cycle or use a lattice energy equation to find lattice energy. The Born-Haber cycle is more accurate as it is derived experimentally, but requires a larger amount of data. Lattice energy formulas, such as the Kapustinskii equation, are easy to use but are only estimates.

So, regardless of whether you've been asked to find the lattice energy of CaO\textCaOCaO for a test or want to work out the lattice energy of NaCl\textNaClNaCl to aid in dinner conversation, learning how to calculate lattice energy will aid in your understanding of the physical world.

Before we get to grips with finding the lattice energy, it's important to know the lattice energy definition as it is quite peculiar. Chemists, for various reasons, like to have exact and sometimes unintuitive definitions, but they do serve a purpose, we assure you. In this case, the lattice energy definition isn't the change in energy when any two atoms form an ionic bond that is part of an ionic lattice, but instead:

That the ions are in their gaseous state is important; in this form, they are thought to be infinitely far apart, i.e., there are no interactions between them. This ensures that the complete lattice energy is found, not merely the enthalpy of formation.

Perhaps surprisingly, there are several ways of finding the lattice energy of a compound. In fact, there are five. We will discuss one briefly, and we will explain the remaining four, which are all slight variations on each other, in more detail. You can calculate the last four using this lattice energy calculator.

As one might expect, the best way of finding the energy of a lattice is to take an amount of the substance, seal it in an insulated vessel (to prevent energy exchange with the surroundings), and then heat the vessel until all of the substance is gas. After this, the amount of energy you put in should be the lattice energy, right?

So, how to calculate lattice energy experimentally, then? The trick is to chart a path through the different states of the compound and its constituent elements, starting at the lattice and ending at the gaseous ions. If we then add together all of the various enthalpies (if you don't remember the concept, visit our enthalpy calculator), the result must be the energy gap between the lattice and the ions. This kind of construction is known as a Born-Haber cycle. For example, we can find the lattice energy of CaO\textCaOCaO using the following information:

There are, however, difficulties in getting reliable energetic readings. This has led many people to look for a theoretical way of finding the lattice energy of a compound. The first attempt was to find the sum of all of the forces, both attractive and repulsive, that contribute to the potential lattice energy.

While the hard-sphere model is a useful approximation, it does have some issues. The truth is that atoms do not exist as single points that are either wholly positive or wholly negative, as in the hard-sphere model. They are instead surrounded by a number of electron orbitals regardless of charge (unless you have managed to remove all of the electrons, as in the case of H+\textH^+H+, of course). Because there is actually some element of repulsion between the anion and cation, the hard-sphere model tends to over-estimate the lattice energy. To correct for this, Born and Land (yes, the same Born as in the Born-Haber cycle, prolific, we know) proposed an equation to describe this repulsive energy:

Unfortunately, some of the factors for both the Born-Land and Born-Mayer equations require either careful computation or detailed structural knowledge of the crystal, which are not always easily available to us. Kapustinskii, a Soviet scientist, also noticed this and decided to make some improvements to the Born-Mayer equation to make it more fit for general purposes.

However, with battery operated equipment I would like standby consumption an order of magnitude less than that. Microcontrollers with sub-microamp standby currents are now common and with watchdogs taking less than 1A. While the CPLD could be powered down, it adds a complexity.

Dynamic power of the IGLOO Nano is design dependent like any other FPGA but uses around 5 to 10mA for the 512 macrocell AGLN060 at 1.2V for a typical design at 50MHz, based on their power calculator spreadsheet. This compares very favorably with the CoolRunner-II.

That is a 22mm IC on a 28mm wide PCB. While smaller packages are now available, it seems that they often still try to give a large number of I/O pins in a small package instead of a smaller number of pins in a small package. The iCE40 seems to be an improvement in that regard. Whereas with the CoolRunner-II the smallest package you can get the 512 macrocell device in is a PQ208 which is over 30mm square, the 1280 macrocell iCE40 can be bought in 16WLCSP package which is only 1.41.5mm. It has only 16 pins so maybe is a little extreme but is also available in various packages up to 6x6mm 121csBGA (or 5x5mm 121ucBGA). An 84 pin QFN at 7x7mm makes a simpler PCB option for a reasonable size. The Microsemi IGLOO nano options for 1024 macrocells start at CS81 at 5x5mm so if space is tight the iCE40 gives a lot more choices. It is only when you get down to 256 macrocells with the IGLOO that you can get smaller packages although not much smaller because other than the UC81 at 4x4mm the lower pin count devices are QFN and actually larger than the CS81.

The iCE40 seems to lose out in the static power consumption compared to the Microsemi IGLOO but wins on pin count, size and cost. It seems to be similar for dynamic power consumption as well but would need a complete design for both the IGLOO and iCE40 to find out for certain. The Xilinx is probably only really for existing designs as it seems to have nothing unique to offer and is expensive and large. Altera and Xilinx seem to really be chasing the bigger, better, faster devices rather than the small, low power portion of the market. The iCE40 is a welcome new addition to the lower power market, and if they could get the static power down a bit would be a clear winner.

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My max hang (7s, 20mm edge, half crimp) is 32 lbs @ 135lbs, max outdoor grade 5.12c, V7. Lattice and the like (e.g. this online finger strength calculator) always claim that my fingers are very weak for the grades I climb. According to my Lattice results (screenshot here) I'm one standard deviation in finger strength below the average of people climbing my grades, and hanging 60lbs would put me at average, which seems like ridiculously much. If I could hang 60lbs I'd probably be sending 13s. I would actually say crimpy climbs are my strength, and I wouldn't describe myself as having particularly good technique, so who knows.

The Lattice data is probably the "best" you'll find, but is skewed by people who are good at training and bad at climbing. My results were pretty similar to Prav's. They think V6 climber should only climb 12-, which is just another reason to be skeptical.

These companies test large amounts of people who have already sent these grades, then roast you that your fingers need to be X to send Y, sell you a cookie cutter max hang program to get X fingers, then when you don't send Y this season, sell you another premium coaching package to tell you that you "wow you're already strong enough to do this, you just need to climb more, footwork, better tactics, yada yada"

I'd agree with others that the power company climbing and lattice data are way off as predictors of redpoint ability via strength metrics. There was recently a good article along those lines: -metrics-really-matter-for-climbing/

Who knows, but my money is that their data set is mostly made up of their clients. People who hire coaches for strength training are probably more likely to be stronger than they are savvy (technique, tactics, grit, etc) for various reasons and therefor using their metrics, you need to be way stronger than actual reality would suggest. (I've got pretty much identical metrics to the OP and I'm pretty sure Lattice and Power Company both say I should be sending somewhere in the 5.12 range) I'd agree to that geography plays a huge role too because certain types of strength are more or less relevant depending on the area we're talking about.

However, my max redpoint was 12c and it was quite hard for me (last summer). This seems in line with Power Company charts, but I do get an impression that it's more than typical and I need to learn to climb...

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