Kenneth Evans, Rice University

For the first time in American history, quantum computing was mentioned by a candidate during a presidential debate, on Sept. 10, 2024. After Vice President Kamala Harris brought up quantum technology, she and former President Donald Trump went on to have a heated back-and-forth about American chipmaking and China’s rise in semiconductor manufacturing. Science and technology policy usually takes a back seat to issues such as immigration, the economy and health care during election season.

What’s changed for 2024?

From COVID-19 to climate change, ChatGPT to, yes, quantum computers, science-related issues are on the minds of American policymakers and voters alike. The federal government spends nearly US$200 billion each year on scientific research and development to address these challenges and many others. Presidents and Congress, however, rarely agree on how – and how much – money should be spent on science.

With the increasing public focus on global competitiveness, the climate crisis and artificial intelligence, a closer look at Trump’s and Harris’ records on science and technology policy could provide a hint about how they’d approach these topics if elected this fall.

Two distinct visions for science funding

If politics can be described as “who gets what and when,” U.S. science and technology policy can be assessed through the annual budget process for R&D. By this measure, the differences between the Trump and Biden-Harris administrations couldn’t be starker.

In his first budget request to Congress, in 2017, Trump spurned decades of precedent, proposing historic cuts across nearly every federal science agency. In particular, Trump targeted climate-related programs at the Department of Energy, the National Oceanic and Atmospheric Administration and the Environmental Protection Agency.

Trump’s fiscal policy took a page from Reagan-era conservative orthodoxy, prioritizing military spending over social programs, including R&D. Unlike Reagan, however, Trump also took aim at basic research funding, an area with long-standing bipartisan support in Congress. His three subsequent budget proposals were no different: across-the-board reductions to federal research programs, while pushing for increases to defense technology development and demonstration projects.

Congress rebuked nearly all of Trump’s requests. Instead, it passed some of the largest increases to federal R&D programs in U.S. history, even before accounting for emergency spending packages funded as part of the government’s pandemic response.

In contrast, the Biden-Harris administration made science and innovation a centerpiece of its early policy agenda – with budgets to match. Leveraging the slim Democratic majority during the 117th Congress, Biden and Harris shepherded three landmark bills into law: the Infrastructure Investment and Jobs Act, the Inflation Reduction Act and the CHIPS and Science Act. These laws contain significant R&D provisions focused on environmental projects (IIJA), clean energy (IRA) and American semiconductor manufacturing (CHIPS).

CHIPS set up programs within the National Science Foundation and the Department of Commerce to create regional technology hubs in support of American manufacturing. The act also set ambitious funding targets for federal science agencies, especially at NSF, calling for its budget to be doubled from $9 billion to over $18 billion over the course of five years.

Despite its initial push for R&D, the Biden-Harris administration’s final two budget proposals offered far less to science. Years of deficit spending and a new Republican majority in the House cast a cloud of budget austerity over Congress. Instead of moving toward doubling NSF’s budget, the agency suffered an 8% decrease in fiscal year 2024 – its biggest cut in over three decades. For FY2025, which runs from Oct. 1, 2024, through Sept. 30, 2025, Biden and Harris requested a meager 3% increase for NSF, billions of dollars short of CHIPS-enacted spending levels.

An emerging consensus on China

On technology policy, Biden and Harris share more with Trump than they let on.

Their approach to competing with China on tech follows Trump’s lead: They’ve expanded tariffs on Chinese goods and severely limited China’s access to American-made computer chips and semiconductor manufacturing equipment.

Biden and Harris have also ramped up research security efforts intended to protect U.S. ideas and innovation from China. Trump launched the China Initiative as an attempt to stop the Chinese government from stealing American research. The Biden-Harris administration ended the program in 2022, but pieces of it remain in place. Scientific collaborations between the United States and China continue to decline, to the detriment of American scientific leadership.

The Biden-Harris administration has also drawn from Trump-era policy to strengthen America’s leadership in “industries of the future.” The term, coined by Trump’s then-chief science adviser Kelvin Droegemeier, refers to five emerging technology areas: AI, quantum science, advanced manufacturing, advanced communications and biotechnology. This language has been parroted by the Biden-Harris administration as part of its focus on American manufacturing and throughout Harris’ campaign, including during the debate.

In short, both candidates align with the emerging Washington bipartisan consensus on China: innovation policy at home, strategic decoupling abroad.

Science advice not always a welcome resource

Trump’s dismissal of and at times outright contempt for scientific consensus is well documented. From “Sharpiegate,” when he mapped his own projected path for Hurricane Dorian, to pulling out of the Paris climate agreement, World Health Organization and the Iran nuclear deal, Trump has demonstrated an unwillingness to accept any advice, let alone from scientists.

Indeed, Trump took over two years to hire Droegemeier as director of the White House Office of Science and Technology Policy, or OSTP, doubling the previous record for the length of time a president has gone without a scientific adviser. This absence was no doubt reflected in Trump’s short-on-science budget requests to Congress, especially during the beginning of his administration.

On the other hand, the Biden-Harris administration has promoted science and innovation as a core part of its broader economic policy agenda. It elevated the role of OSTP: Biden is the first president to name his science adviser – a position currently held by Arati Prabhakar – as a member of his Cabinet.

By law, the president is required to appoint an OSTP director. But it is up to the president to decide how and when to use their advice. If the new White House wants the U.S. to remain a global leader in R&D, the science adviser will need to continue to fight for it.

Kenneth Evans, Scholar in Science and Technology Policy, Baker Institute for Public Policy, Rice University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Julie Sullivan, Emory University and Wilbur Lam, Georgia Institute of Technology

A scratchy, sore throat, a relentless fever, a pounding head and a nasty cough – these symptoms all scream upper respiratory illness. But which one?

Many of the viruses that cause upper respiratory infections such as influenza A or B and the virus that causes COVID-19 all employ similar tactics. They target the same areas in your body – primarily the upper and lower airways – and this shared battleground triggers a similar response from your immune system. Overlapping symptoms – fever, cough, fatigue, aches and pains – make it difficult to determine what may be the underlying cause.

Now, at-home rapid tests can simultaneously determine whether someone has COVID-19 or the flu. Thanks in part to the National Institutes of Health‘s Rapid Acceleration of Diagnostics, or RADx, program, the Food and Drug Administration has provided emergency use authorization for seven at-home rapid tests that can distinguish between COVID-19, influenza A and influenza B.

Our team in Atlanta – composed of biomedical engineers, clinicians and researchers at Emory University, Children‘s Healthcare of Atlanta and Georgia Institute of Technology – is part of the RADx Test Verification Core. We closely collaborate with other institutions and agencies to determine whether and how well COVID-19 and influenza diagnostics work, effectively testing the tests. Our center has worked with almost every COVID and flu diagnostic on the market, and our data helped inform the instructions you might see in many of the home test kits on the market.

While no test is perfect, to now be able to test for certain viruses at home when symptoms begin can help patients and their doctors come up with appropriate care plans sooner.

A new era of at-home tests

Traditionally, identifying the virus causing upper respiratory illness symptoms required going to a clinic or hospital for a trained medical professional to collect a nasopharyngeal sample. This involves inserting a long, fiber-tipped swab that looks like a skinny Q-tip into one of your nostrils and all the way to the back of your nose and throat to collect virus-containing secretions. The sample is then typically sent to a lab for analysis, which could take hours to days for results.

Thanks to the COVID-19 pandemic, the possibility of using over-the-counter tests to diagnose respiratory illnesses at home became a reality. These tests used a much gentler and less invasive nasal swab and could also be done by anyone, anytime and in their own home. However, these tests were designed to diagnose only COVID-19 and could not distinguish between other types of illnesses.

Since then, researchers have developed over-the-counter multiplex tests that can screen for more than one respiratory infection at once. In 2023, Pfizer’s Lucira test became the first at-home diagnostic test for both COVID-19 and influenza to gain emergency use authorization.

What are multiplex rapid tests?

There are two primary forms of at-home COVID-19 and COVID-19/flu combination tests: molecular tests such as PCR that detect genetic material from the virus, and antigen tests – commonly referred to as rapid tests – that detect proteins called antigens from the virus.

The majority of over-the-counter COVID-19 and COVID-19/flu tests on the market are antigen tests. They detect the presence of antigens in your nasal secretions that act as a biological signature for a specific virus. If viral antigens are present, that means you’re likely infected.

To detect these antigens, rapid tests have paper-like strips coated with specially engineered antibodies that function like a molecular Velcro, sticking only to a specific antigen. Scientists design and manufacture specialized strips to recognize specific viral antigens, like those belonging to influenza A, influenza B or the virus that causes COVID-19.

The antibodies for these viral targets are placed on the strip, and when someone’s nasal sample has viral proteins that are applied to the test strip, a line will appear for that virus in particular.

Advancing rapid antigen tests

Like all technologies, rapid antigen tests have limitations.

Compared with lab-based PCR tests that can detect the presence of small amounts of pathogen by amplifying them, antigen tests are typically less sensitive than PCR and could miss an infection in some cases.

All at-home COVID-19 and COVID-19/flu antigen tests are authorized for repeat use. This means if someone is experiencing symptoms – or has been exposed to someone with COVID-19 but is not experiencing symptoms – and has a negative result for their first test, they should retest 48 hours later.

Another limitation to rapid antigen tests is that currently they are designed to test only for COVID-19, influenza A and influenza B. Currently available over-the-counter tests aren’t able to detect illnesses from pathogens that look like these viruses and cause similar symptoms, such as adenovirus or strep.

Because multiplex texts can detect several different viruses, they can also produce findings that are more complex to interpret than tests for single viruses. This may increase the risk of a patient incorrectly interpreting their results, misreading one infection for another.

Researchers are actively developing even more sophisticated tests that are more sensitive and can simultaneously screen for a wider range of viruses or even bacterial infections. Scientists are also examining the potential of using saliva samples in tests for bacterial or viral infections.

Additionally, scientists are exploring integrating multiplex tests with smartphones for rapid at-home diagnosis and reporting to health care providers. This may increase the accessibility of these tests for people with vision impairment, low dexterity or other challenges with conducting and interpreting at-home tests.

Faster and more accurate diagnoses lead to more targeted and effective treatment plans, potentially reducing unnecessary antibiotic use and improving patient outcomes. The ability to rapidly identify and track outbreaks can also empower public health officials to better mitigate the spread of infectious diseases.

Julie Sullivan, Chief Operating Officer of RADx Tech, Emory University and Wilbur Lam, Chief Innovation Officer, Children’s Healthcare of Atlanta Pediatric Technology Center; Professor of Biomedical Engineering, Georgia Institute of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Artemis Spyrou, Michigan State University and Sean Liddick, Michigan State University

The word magic is not often used in the context of science. But in the early 1930s, scientists discovered that some atomic nuclei – the center part of atoms, which make up all matter – were more stable than others. These nuclei had specific numbers of protons or neutrons, or magic numbers, as physicist Eugene Wigner called them.

The race to figure out what made these nuclei so stable began. Understanding these magic numbers would allow scientists to predict the properties of other nuclei, such as their mass or how long they are expected to live. With that, scientists could also predict which combinations of protons and neutrons can result in a nucleus.

The solution to the puzzle came in 1949 from two directions simultaneously. In the U.S., physicist Maria Goeppert Mayer published an explanation, at the same time as a group of scientists led by J. Hans D. Jensen in Germany found the same solution.

For their discovery, the two physicists each got a quarter of the 1963 Nobel Prize in physics. We’re two nuclear scientists whose work is built on Goeppert Mayer’s and Jensen’s discoveries 75 years ago. These magic numbers continue to play an important role in our research, only now we can study them in nuclei that live for just a fraction of a second.

Stability in the atom

The atom is a complex system of particles. It’s made up of a central nucleus consisting of protons and neutrons, called nucleons, with electrons orbiting around the nucleus.

Nobel prize-winning physicist Niels Bohr described these electrons in the atom as existing in a shell structure. The electrons circulate around the nucleus in particular energy levels, or orbits. These orbits have specific energies, and each orbit can hold only so many electrons.

Chemical reactions result from interactions between the electrons in two atoms. In Bohr’s model, if an electron orbit is not already filled, then it’s easier for the atoms to exchange or share those electrons and induce chemical reactions.

One class of elements, the noble gases, hardly ever react with other elements. In noble gases, the electrons occupy completely filled orbits, and as a result the atoms greedily hold onto their electrons instead of sharing and undergoing a chemical reaction.

In the 1930s, scientists wondered whether protons and neutrons might also occupy orbits, like electrons. But nobody could show this conclusively. For more than a decade, the scientific community was unable to describe the nucleus in terms of individual protons and neutrons. Scientists used a more simplified picture, one that treated protons and neutrons as one single system, like a drop of water.

Magic numbers

In 1949, Goeppert Mayer and Jensen developed the so-called shell model of the nucleus.
Protons and neutrons occupy particular orbits, analogous to electrons, but they also have a property called spin – similar to a spinning top. Goeppert Mayer and Jensen found that when combining the two properties in their calculations, they were able to reproduce the experimental observations.

Through some experiments, they found that nuclei with certain magic numbers of neutrons or protons are unusually stable and hold onto their nucleons more than researchers previously expected, just like how noble gases hold onto their electrons.

The magic numbers known to scientists are 2, 8, 20, 28, 50, 82 and 126. They are the same for both protons and neutrons. When a nucleus has a magic number of protons or neutrons, then the particular orbit is filled, and the nucleus is not very reactive, similar to the noble gases.

For example, the element tin has a magic number of protons. Tin always has 50 protons, and its most common isotope has 70 neutrons. Isotopes are atoms of the same element that have a different number of neutrons.

There are nine other stable isotopes of tin that can exist – it’s the element with the largest number of stable isotopes. A stable isotope will never spontaneously change into a different element, which is what happens to radioactive isotopes.

Helium, with two protons and two neutrons, is the lightest “doubly magic” nucleus. Both its neutron count and its proton count are a magic number. The forces that hold the helium-4 nucleus together are so strong that it’s impossible to attach another proton or neutron. If you tried to add another proton or neutron, the resulting atom would fall apart instantaneously.

On the other hand, the heaviest stable nucleus in existence, lead-208, is also a doubly magic nucleus. It has magic numbers of 82 protons and 126 neutrons.

Examples of magic numbers and stable nuclei exist everywhere – but scientists couldn’t explain them without the introduction of the shell model.

Stable nuclei in nature

The shell structure in nuclei tells researchers about how elements are distributed across the Earth and throughout the universe.

One of the most abundant elements on our planet and in the human body is oxygen, in particular the isotope oxygen-16.

With eight protons and eight neutrons, oxygen-16 has an extremely stable nucleus. A nearby star produced the oxygen we find on Earth through nuclear reactions in its core sometime before the solar system was formed.

Since oxygen nuclei are doubly magic, these nuclei in the star did not interact very much with other nuclei. So more oxygen was left around to eventually act as an essential ingredient for life on Earth.

In her Nobel lecture, Maria Goeppert Mayer talked about the work she did with physicist Edward Teller. The two had attempted to describe how these elements formed in stars. In the 1930s, it was impossible for them to explain why certain elements and isotopes were more abundant in stars than others. She later found that the increased abundances corresponded to nuclei with something in common: They all had magic numbers of neutrons.

With the shell model and the explanation of magic numbers, the production of elements in stars was possible and was published in 1957.

Scientists today continue to use ideas from the nuclear shell model to explain new phenomena in nuclear science. A few accelerator facilities, such as the Facility for Rare Isotope Beams, where we work, aim to create more exotic nuclei to understand how their properties change compared with their stable counterparts.

At the Facility for Rare Isotope Beams, scientists produce new isotopes by accelerating stable isotopes to about half the speed of light and smashing them at a target. Out of the pieces, we select the rarest ones and study their properties.

Possibly the most profound modern discovery is the fact that the magic numbers change in exotic nuclei like the type we create here. So, 75 years after the original discovery, the race to discover the next magic number is still on.

Artemis Spyrou, Professor of Nuclear Physics, Michigan State University and Sean Liddick, Associate Professor of Chemistry, Michigan State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.