Low-Temperature Solders: Niche No More?


It surprises many people that the foundation metal of almost all solder alloys is tin. Alloy elements such as lead, silver, copper, indium, etc., are extremely important, as they lower the solder melting temperature below tin’s relatively high 232°C and often improve wetting and other process or performance properties.

Figure 1. Bismuth metal. (Source: Indium)

As an example, tin-bismuth near-eutectic solders have a melting range around 140°C with a processing temperature of about 170°C, putting tin-bismuth solders 50°C or so below most common lead-free solders such as SAC 305. A while ago, I posted on tin-bismuth solders, asking if their time had come. This post generated follow-on questions that were answered in a second post.

iNEMI predicts that low-temperature solders, such as these tin-bismuth solders, may become main stream as soon as 2017. In light of this situation, my colleague and friend, Dr. Ning-Cheng Lee, is presenting a workshop on “Properties and Applications of Low Temperature Solders” at SMTAI on Sept. 29, from 8:30-12 noon in room 54.

The course summary is: Since the dawn of the electronic industry, the soldering process has encompassed mainly component manufacturing and printed circuit board assembly, with a hierarchic solder melting range. Components are made using solder alloys with melting temperatures around 300°C, which will not melt in the subsequent PCB assembly process, where the solders typically melt around 200°C. Low-temperature solders, with melting temperatures less than 170°C, are currently used mainly for niche applications. However, the iNEMI roadmap predicts low-temperature soldering to become a mainstream processes by 2017. Low-temperature soldering is greatly desired for assemblies such as heat-sensitive devices, systems with more hierarchic levels, parts with significant differences in their coefficients of thermal expansion, components exhibiting severe thermal warpage, or products with highly miniaturized design. This course will cover several varieties of low-temperature solders with an emphasis on lead-free alloys, their physical, mechanical, and soldering properties, and the applications involved with those alloys.

And the topics covered will be:

· Design of low-temperature solder alloys.

· Indium-bearing solder systems and their properties.

· Bismuth-bearing solder systems and their properties.

· Recent development in bismuth-bearing low-temperature solder alloys.

· Mechanisms of reliability enhancement of new bismuth-bearing solder alloys.

· Applications of low-temperature solders.

Be sure to add this workshop to your list of things to do at SMTAI.


Dr. Ron

Measuring Alloy Density


In the category of interesting requests, Ron, a gold worker, from Guyana, sent me the following note:

Dr. Ron,

My colleagues use a “wet” gold technique to measure gold alloy density.  Is this valid?  Where does the formula come from?



Well, to tell the truth, I had never heard of it and was skeptical. How can you measure density (mass/volume) by only measuring weight? So, I investigated. The technique claims that one can measure density with only a scale, by measuring the alloy’s weight in air and in water.

I could find no derivation, so I thought about it and derived it on my own. As far as measurements go, as stated, you only have to measure the weight in air and water. If you don’t have a scale that can handle being immersed in water, you can use a hanging scale (think weighing a fish). So, after weighing the alloy in air, you immerse it in water. It will weigh the amount of water it displaces less.  The derivation is below:

As an example, let’s say you have a gold alloy ingot that weighs 1,000 grams (OK, I know grams is mass, but we are all sloppy and use it as weight, too) in air.  You weigh it in water and it weighs 930 grams. From the formula below, the alloys density is:

r = 1000/(1000-930) = 14.29g/cc

Since the density of gold is 19.3g/cc, the alloy is not pure gold.  If you knew the alloying element, say copper, you could use a Solder Alloy Density Calculator to determine that the alloy was 69.8% gold, 30.2% copper. If there are multiple alloying elements, since most of the common elements have a density of about 9 g/cc, you can even estimate the fineness of the gold.

Could this technique be used to measure the alloy density of say a handful of solder preforms? Sure, you could put them in a woven bag of non-hygroscopic material and weigh them in air and water. Admittedly, measuring the density of solder paste, with this technique, would be a challenge.

Next posting, I will show how this technique is used to measure the quantity of gold in gold/quartz ore.


Dr. Ron

Weibull Analysis II: The Curse of the Early First Failure


In continuing our discussion on Weibull Analysis, let’s assume we assembled some SMT and through-hole PCBs with lead-free solder paste. On this board are also some bottom-side terminated (BTC) components (often called QFNs), that are also assembled with solder preforms.  A stress test is performed to test the BTCs. In such a test, the first fail in Weibull analysis is the most important data point. No matter the results of remainder of the data, these later fails cannot undo the effect of a very early first fail.

To understand this concept, let’s look at the Weibull chart below. In many high reliability applications, there may be a requirement that some small percentage of the components under test have at least some minimum reliability.


Figure 1.  Weibull Analysis with an Early Fail.

As an example, let’s say that 1% of the components cannot have less than 500 cycles of life.  By looking at Figure 1, we see that 1% have less than 150 cycles of life (see arrow.)  This one early outlier dramatically affects the Weibull Analysis.

However, if that outlier was removed, as seen in Figure 2, the data suggest that 1% of the components will have a life of 900 cycles. We can see the dramatic effect the first fail has on this result. Note that the first fail does not affect the “scale” or characteristic life much (2647 vs 2682). Hence, the characteristic life, is not a robust metric to use in a high reliability environment. However, the shape or slope is dramatically affected by the early fail as it changes from 2.22 to 4.23 when the early fail is “censored.”

Figure 2. Weibull analysis with the early fail removed (censored).

Why might an outlier like this exist? Almost certainly there is something unusual about the early fail. It might be something like an oxidized pad preventing good wetting of the solder. Perhaps something like this failure mode might be discovered in root cause failure analysis. However, I am typically opposed to censoring data, even with supportive failure analysis. I think the test should be done over. It is often too easy to talk yourself into accepting inconclusive failure analysis.

What is your opinion?


Dr. Ron

Interpreting Weibull Plots: I


A while ago I discussed the Weibull Distribution and its importance in electronics reliability analysis. This distribution has been used to evaluate the life of solder joints whether formed in SMT, wave, or even using solder preforms. In the next few posts, I would like to discuss how to interpret Weibull plots.

Let’s consider two Weibull plots from thermal cycle testing of lead-free solder joints as seen in Figure 1.

Figure 1. A Weibull plot of thermal cycle data for Alloy 2 and Alloy 4.

Both alloys have almost exactly the same scale, or characteristic life. You will remember that characteristic life is the number of cycles at which 63% of the test subjects fail. For Alloy 2 it is 2,593 cycles and for Alloy 4 it is slightly better at 2,629 cycles. However, these two alloys performed dramatically differently. The most striking difference is in their “spread.” We see this much greater spread for Alloy 4, when we plot a fit to the data as a normal distribution, as in Figure 2 below.

Figure 2. The best fit normal distribution plot for Alloy 2 and Alloy 4.

In the Weibull plot, the data for Alloy 2 has a very steep slope or shape factor, this indicates a tight distribution. A tight distribution is desirable as it facilitates more accurate prediction of thermal cycle life. Alloy 2 is clearly superior. So, in a Weibull distribution, not only is a large scale factor or characteristic life desired, but so is a steep slope or larger shape factor.

Next time we will talk about outliers.

Dr. Ron