Instruments That Changed Science

Throughout history, breakthroughs in science have depended on the instruments that made them possible. The tools below opened new windows onto the physical and biological world — and changed what scientists could see, measure, and understand.

Physical Sciences

  • Jerry Nelson designed the Keck Telescope’s primary mirror as 36 hexagonal segments, individually controlled to act as one continuous 10-meter surface. This active-control approach made Keck the world’s largest optical telescope for years and became the template for nearly every large telescope built since.

  • Roger Angel developed a way to cast large telescope mirrors in a spinning furnace, using centrifugal force to shape the curve and a lightweight honeycomb structure that cools faster and needs less material. The technique made large, stiff, low-mass mirrors practical and is used in telescopes worldwide today.

  • Horace Babcock proposed correcting the blur caused by Earth’s atmosphere by rapidly reshaping a telescope’s mirror in real time. Once precision actuators and computing power caught up decades later, adaptive optics let ground-based telescopes match the sharpness of images from space.

  • Item descriptionClaire Max helped pioneer using a laser to create an artificial “guide star” high in the atmosphere, giving adaptive optics a reference point even when no bright natural star is nearby. This freed adaptive optics to sharpen images anywhere in the sky, greatly expanding what ground-based telescopes could observe.

  • Item descriptionUsing the largest digital camera ever built for astronomy, the Rubin Observatory is imaging the entire visible southern sky every few nights to catalog tens of billions of objects. The resulting decade-long time-lapse of the universe is expected to transform the study of asteroids, dark matter, and cosmic explosions.

  • Item descriptionGerd Binnig and Heinrich Rohrer built an instrument that “feels” a surface atom by atom, using a needle-sharp tip and a quantum tunneling current to produce the first images of individual atoms. The invention opened the field of nanotechnology and earned its creators the 1986 Nobel Prize in Physics.

  • Item descriptionTheodore Maiman built the first working laser using a ruby crystal and a flash lamp, producing a tightly focused beam of light unlike anything before it. Lasers went on to become essential tools across science, medicine, communications, and manufacturing.

  • Item descriptionFelix Bloch and Edward Purcell independently discovered that atomic nuclei absorb and re-emit radio waves when placed in a strong magnetic field. The phenomenon became the basis for NMR spectroscopy, used to determine molecular structure, and for MRI, one of medicine’s most important diagnostic tools.

Biological Sciences

  • Marvin Minsky patented a design that uses a pinhole to block out-of-focus light, allowing sharp images of a single thin plane inside a thick, translucent sample. Confocal microscopy became a standard tool for imaging living cells and tissues in three dimensions.

  • Jennifer Doudna and Emmanuelle Charpentier showed that a bacterial immune defense system could be repurposed as a programmable tool to cut DNA at any chosen location. The discovery turned gene editing from a slow, expensive process into a routine lab technique and earned the pair the 2020 Nobel Prize in Chemistry.

  • Kary Mullis devised a simple method to repeatedly copy a specific piece of DNA, doubling it with each heating-and-cooling cycle until a single molecule becomes billions. PCR became the foundation of modern molecular biology, forensics, and diagnostic testing, including COVID-19 tests.

  • Jacques Dubochet, Joachim Frank, and Richard Henderson developed methods to flash-freeze biological samples and reconstruct their 3D structure from electron microscope images, avoiding damage from traditional preparation. A resolution breakthrough around 2013 let researchers see proteins at near-atomic detail, earning the trio the 2017 Nobel Prize in Chemistry.

  • DeepMind’s AlphaFold used deep learning to solve a fifty-year-old challenge in biology — predicting a protein’s 3D shape from its amino acid sequence — with accuracy rivaling years of lab work. Its public database now includes predicted structures for over 200 million proteins, accelerating research from drug design to basic biology.