A new DNA computer developed at Maynooth University (MU) offers significant advances in the speed and complexity of molecular computing while potentially requiring far less energy than traditional silicon computers.
The MU team described its DNA computer in a recent paper published in Nature, revealing how researchers used DNA strands to perform mathematical operations, including multiplication, division, and addition.
The computer differs dramatically from conventional silicon-based systems. Instead of relying on electronic chips, it uses DNA strands interacting while suspended in a saline solution. One of the technology’s potential advantages is its low energy requirement, an increasingly important consideration amid growing concerns over the enormous power demands of data centers.
DNA Computers and Energy
“Silicon-based computers use so much energy – 23% of Ireland’s electricity goes into computing and data storage,” said co-author Professor Damien Woods of Maynooth University’s Hamilton Institute. “We’ve been blinkered by only seeing one type of computer, but there are other examples around us, including our brain.”
Silicon computers, like the device you are probably reading this on right now, require a continuous supply of electrical power while operating. The DNA computer works differently, using heating and cooling to initiate molecular interactions that perform computations without requiring a continuous energy input throughout the process.
“The molecules interact, form a structure, and that structure is the answer,” said Professor Woods. “One key innovation is that the system naturally finds that answer without needing continuous energy inputs.”
Developing a DNA Computer
The work is part of the DNA-based Infrastructure for Storage and Computation (DISCO) project, led by Professor Woods with support from a €4 million grant from the European Innovation Council. Through the project, MU researchers are developing new methods for using DNA to perform computation and data storage.
The computer consists of short DNA strands assembled on a larger DNA scaffold and suspended in a saline solution inside a test tube. By heating and cooling the solution, researchers can drive molecular interactions that perform mathematical operations.
Because DNA-based computation occurs at the molecular level, the technology could also eventually lend itself to biological or medical applications, including systems designed to operate within cells or detect signs of disease.
“A small droplet of liquid contains billions, and sometimes trillions, of DNA strands,” said co-first author Dr Abeer Eshra, Assistant Professor and computer scientist at MU’s Hamilton Institute. “These strands interact with one another to produce a result.”
DNA Math
The calculations are impressive for such a radically different computing system, although they remain far slower than those performed by conventional silicon computers. Across the ten programs the MU team ran on its DNA computer, computation times varied widely. A simple addition problem of ten plus three took around half a minute, while 100-bit computations involving numbers between 11 million and 34 million took up to 14 hours to complete.
While the system cannot match the speed of conventional computers, researchers demonstrated that it could reliably perform a series of calculations, including solving 25 problems in succession. Despite its limitations compared with silicon systems, the results represent a significant advance in the speed and capabilities of DNA computing.
“The reaction happens fast in the test tube, but not as fast as silicon, nor is it intended to be. But compared to other DNA computers, ours is the fastest,” said co-first author Dr Eshra.
“This is blue skies science,” Professor Woods concluded. “We don’t know where the future is going to take us.”
The paper, “A Thermodynamically Favoured Molecular Computer: Robust, Fast, Renewable, Scalable,” appeared in Nature on September 17, 2026.
Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.