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The LTV is part of NASA’s efforts to explore the lunar surface as part of the Artemis campaign and is the first crew-driven vehicle to operate on the Moon in more than 50 years. Designed to hold up to two astronauts, as well as operate remotely without a crew, this surface vehicle will enable NASA to achieve more of its science and exploration goals over a wide swath of lunar terrain.

“The Artemis Lunar Terrain Vehicle will transport humanity farther than ever before across the lunar frontier on an epic journey of scientific exploration and discovery,” said Nicky Fox, associate administrator, Science Mission Directorate at NASA Headquarters in Washington. “By combining the best of human and robotic exploration, the science instruments selected for the LTV will make discoveries that inform us about Earth’s nearest neighbor as well as benefit the health and safety of our astronauts and spacecraft on the Moon.”

The Artemis Infrared Reflectance and Emission Spectrometer (AIRES) will identify, quantify, and map lunar minerals and volatiles, which are materials that evaporate easily, like water, ammonia, or carbon dioxide. The instrument will capture spectral data overlaid on visible light images of both specific features of interest and broad panoramas to discover the distribution of minerals and volatiles across the Moon’s south polar region. The AIRES instrument team is led by Phil Christensen from Arizona State University in Tempe.

The Lunar Microwave Active-Passive Spectrometer (L-MAPS) will help define what is below the Moon’s surface and search for possible locations of ice. Containing both a spectrometer and a ground-penetrating radar, the instrument suite will measure temperature, density, and subsurface structures to more than 131 feet (40 meters) below the surface. The L-MAPS instrument team is led by Matthew Siegler from the University of Hawaii at Manoa.

When combined, the data from the two instruments will paint a picture of the components of the lunar surface and subsurface to support human exploration and will uncover clues to the history of rocky worlds in our solar system. The instruments also will help scientists characterize the Moon’s resources, including what the Moon is made of, potential locations of ice, and how the Moon changes over time.

In addition to the instruments selected for integration onto the LTV, NASA also selected the Ultra-Compact Imaging Spectrometer for the Moon (UCIS-Moon) for a future orbital flight opportunity. The instrument will provide regional context to the discoveries made from the LTV. From above, UCIS-Moon will map the Moon’s geology and volatiles and measure how human activity affects those volatiles. The spectrometer also will help identify scientifically valuable areas for astronauts to collect lunar samples, while its wide-view images provide the overall context for where these samples will be collected. The UCIS-Moon instrument will provide the Moon’s highest spatial resolution data of surface lunar water, mineral makeup, and thermophysical properties. The UCIS-Moon instrument team is led by Abigail Fraeman from NASA’s Jet Propulsion Laboratory in Southern California.

“Together, these three scientific instruments will make significant progress in answering key questions about what minerals and volatiles are present on and under the surface of the Moon,” said Joel Kearns, deputy associate administrator for Exploration, Science Mission Directorate at NASA Headquarters. “With these instruments riding on the LTV and in orbit, we will be able to characterize the surface not only where astronauts explore, but also across the south polar region of the Moon, offering exciting opportunities for scientific discovery and exploration for years to come.”

Leading up to these instrument selections, NASA has worked with all three lunar terrain vehicle vendors – Intuitive Machines, Lunar Outpost, and Venturi Astrolab – to complete their preliminary design reviews. This review demonstrates that the initial design of each commercial lunar rover meets all of NASA’s system requirements and shows that the correct design options have been selected, interfaces have been identified, and verification methods have been described. NASA will evaluate the task order proposals received from each LTV vendor and make a selection decision on the demonstration mission by the end of 2025.

Through Artemis, NASA will address high priority science questions, focusing on those that are best accomplished by on-site human explorers on and around the Moon by using robotic surface and orbiting systems. The Artemis missions will send astronauts to explore the Moon for scientific discovery, economic benefits, and build the foundation for the first crewed missions to Mars.

More than a year ago, computational scientists at the Department of Energy’s Oak Ridge National Laboratory published a study in the Journal of Chemical Theory and Computation that raised a serious question about a long-standing methodology used by researchers who conduct molecular dynamics simulations involving water. What if using the standard 2 femtosecond (2 quadrillionths of a second) time step — the time interval at which computer simulations are analyzed — leads to inaccurate results?

Now, the same ORNL team has published a new study in the Royal Society of Chemistry’s journal Chemical Science that reaffirms their original observations by showing how using these “standard” time steps can affect simulations of liquid water. The team’s calculations reveal that the potential for errors caused by using a 2 (or more) femtosecond time step is even greater than they had anticipated.

“I was a little bit surprised. I was hoping for much more subdued effects, but the errors can be big,” said co-author Dilip Asthagiri, a senior computational biomedical scientist in ORNL’s Advanced Computing for Life Sciences and Engineering group. “What we are saying is, ‘With the benefit of knowledge gained over the last 50 years of studies on water, let’s do the statistical mechanics at the most accurate, converged level so that we can better assess the errors in the simulation and focus on issues that we should address.’ It’s an evolution of science.”

Previous research

Water is the most prevalent component of biomolecular simulations — from protein ensembles to nucleic acids — and inaccurately simulating it can lead to errors for research results in biomolecular structure, function, dynamics and assembly. Industries ranging from pharmaceutical to petroleum rely on accurate water simulations to attain a competitive edge for their products and operations.

According to the team’s findings, using anything greater than a 0.5 femtosecond time step can lead to violations of equipartition — the requirement for simulations that the average kinetic energy for each type of motion should be the same. This lack of equipartition can introduce errors in both dynamics and thermodynamics when simulating water using a rigid-body description.

Treating water as a rigid body rather than as a flexible bond between hydrogen and oxygen allows scientists to use longer time steps. The technique dates to 1977, when complex computations were more time-consuming and expensive. The longer the time step, the greater the total physical time that can be modeled in the simulation. Although the Oak Ridge Leadership Computing Facility’s Frontier and other modern supercomputers can reduce the time to solution enough to enable fewer approximations, using a smaller time step inevitably increases the computational cost.

“Sometimes with this kind of study, people may not know how to deal with the conclusions. Eventually, people become aware of it, and then it gradually gets adopted down the road,” said co-author Tom Beck, section head of Science Engagement in the National Center for Computational Sciences at ORNL. “But the point is to say, ‘If we’re going to really do predictive science for a given model — in order to test that model versus experiment — we need to accurately represent the underlying thermodynamics and dynamics.’”

New findings

In their new study, the team — Asthagiri, Beck and Arjun Valiya Parambathu — used Frontier to simulate samples of liquid water, and they explored various system sizes and different combinations of temperature and pressure. They conducted these simulations at time steps that ranged from 0.5 to 3.5 femtoseconds in intervals of 0.5 femtoseconds.

“One of the issues in capturing the physics of water is to accurately capture the pressure and volume behavior,” Asthagiri said. “What our study shows is, using the same pressure, doing the simulation at longer time steps will give you different volumes or give you alternatively different densities. But if you go to very short time steps, the results all converge, and you get a consistent prediction.”

The ORNL team has also been investigating the role of hydration in the thermodynamics of protein folding. Understanding protein folding is a crucial area of study in biology, particularly for research into the molecular basis of diseases and drug discovery. The winners of the 2024 Nobel Prize in Chemistry were researchers in protein structure prediction and computational protein design whose work was assisted by ORNL’s High Flux Isotope Reactor. An important physical effect in protein folding is the change in the volume of the protein-water system.

“What we find is that in the simulation of neat liquid water, the error in total system volume that one makes in using a long time step can be as high as or higher than the typical volume change in protein folding. The same goes for the hydration free energy. While the implications of this finding will need to be worked out for actual protein folding and assembly processes in liquid water, our results suggest the need for much care,” Asthagiri said.

Although the team did hear from some skeptical peers about the findings of their initial study, it was also cited as a reference in papers published in Molecular Physics, Physical Chemistry Chemical Physics, ACS Nano and the Journal of Chemical Theory and Computation.

“Why are we even doing this? Our eventual goal is going to much larger simulations of biological molecules and of cellular systems, and that’s really what we want to go and study,” Asthagiri said. “But we’ve been sidetracked into this because we just want to get the basics right before we go and do these extremely large simulations. We need to know how to simulate the matrix of life better so that we can study the biological processes better.”

ORNL houses the Frontier supercomputer at the OLCF, a DOE Office of Science user facility.

UT-Battelle manages ORNL for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit energy.gov/science. — Coury Turczyn