Researchers, funders, and industry experts in 2D materials call for science to reward reliability over speed, proposing shared tools and standards to strengthen transparency and reproducibility across research.
(Nanowerk Spotlight) On a good day in a 2D materials lab, the data line up neatly, devices behave as expected, and everything seems to work. On a bad day, identical steps produce different outcomes for reasons that no one can fully explain. The difficulty lies not only in the materials themselves, which are extraordinarily sensitive, but also in how the scientific community records, rewards, and communicates its work.
“Even tiny variations can completely change the result,” Peter Bøggild, a professor at the Technical University of Denmark, tells Nanowerk. “We are not careless. The problem is that our research culture rewards being first rather than being reliable.”
Bøggild is the lead author of a new paper in Nature Reviews Physics (“Protocols and tools to enable reproducibility in 2D materials research”) that deliberately stirs debate about how science measures and rewards reliability. The article is unusual not only for what it says but for who wrote it. The author list includes scientists, funders, industry representatives, and communicators.
“We wanted to make sure this was not just researchers complaining about other researchers,” Bøggild explains. “We spent a long time talking with people from publishing and funding to make sure the perspective was broad and workable.”
The reproducibility gap
The paper focuses on 2D materials such as graphene, molybdenum disulfide, and hexagonal boron nitride, where a single atomic layer can transform the way electrons move. Progress has been spectacular, yet reproducibility often lags behind.
“The field has a culture of showing the best device, the so-called hero sample,” says Bøggild. “But the other ninety percent of the data usually stays in the drawer. That gives a distorted picture of what is possible.”
According to the authors, this pattern wastes enormous amounts of time, money, and human effort. It also harms early career researchers who depend on reproducible results to build their reputations. A recent informal survey Bøggild shared online drew an overwhelming response from colleagues who have seen promising projects stall because results could not be repeated.
Building tools, not just arguments
Instead of publishing a set of principles, the team created practical tools that researchers can adopt right away. The first is STEP, short for Standardised Template for Experimental Procedures. It is a detailed reporting format that helps scientists capture every parameter that might influence an experiment, from gas flows to polymer type or surface treatment conditions, while also recording common failure modes and safety warnings.
“STEP is a recipe card for experiments,” says Bøggild. “It takes a few hours to complete but can save months for someone trying to replicate the work later. Transparency should not be a luxury, it should be normal practice.”
The second tool, ReChart, or Reproducibility Charter, is a checklist that lets researchers declare how reproducibility has been addressed in a paper or funding proposal. It covers topics such as open data, error analysis, reporting of negative results, and willingness to host lab visits for verification.
“ReChart is a declaration of intent,” says Bøggild. “By showing exactly what you have done to make your work reproducible, you help reviewers and readers judge it on its real merits.”
Beyond the lab bench
The article goes further than most discussions of reproducibility. It looks at how incentives from publishers, funders, and institutions shape research behavior.
“Novelty dominates every level of evaluation,” Bøggild says. “We need funding calls that include validation and replication as legitimate goals. Those efforts create scientific value even if they do not make headlines.”
Journal editors, the paper argues, can help by requesting detailed protocols and by giving replication studies more room to be published. “When journals only celebrate record-breaking numbers, they train scientists to chase extremes instead of accuracy,” he adds.
The authors also highlight the role of journalists and science communicators. Instead of treating uncertainty as weakness, stories about verified results should be celebrated. “When something has been independently confirmed, that is when it becomes truly exciting,” says Bøggild.
Changing habits, not imposing rules
The authors acknowledge that new documentation standards can feel like extra work, especially for early career researchers under pressure to publish. “We have designed our approach to be flexible,” Bøggild says. “Exploratory research does not need the same depth of documentation as industrial scale projects. The important thing is to make transparency proportional, not burdensome.”
They also recognise that openness can clash with intellectual property concerns. The paper suggests using secure repositories and temporary embargoes to protect sensitive data while still allowing enough disclosure for others to understand the core methods.
Resistance to change is perhaps the hardest obstacle. “Institutions and journals are comfortable with the way things work,” says Bøggild. “But if 2D materials are to become reliable technologies, our results must be reproducible across laboratories, not just within one group.”
Reproducibility as common ground
What sets this initiative apart is its tone. The authors treat reproducibility as a shared goal rather than a moral demand. “We are not trying to police each other,” Bøggild says. “We are trying to make transparency something everyone benefits from.”
The model could extend beyond 2D materials to many other experimental sciences. Any field that depends on complex fabrication steps or sensitive conditions faces the same pressures. “The tools we developed would work just as well in catalysis, energy storage, or nanofabrication,” he says.
The group even sees a role for artificial intelligence in tracking and comparing experimental methods, though Bøggild stresses that AI will never replace human judgment. “AI can help us spot patterns in data and identify weak documentation, but the responsibility still lies with people. Reproducibility is a cultural issue, not a software problem.”
Looking ahead
Bøggild hopes that these ideas will gradually reshape how scientific success is measured. “At the moment, novelty wins every time. We want robustness to count just as much,” he says. “That shift would let young researchers focus on doing careful, trustworthy science without feeling punished for it.”
If the broader research community adopts that view, the next generation of 2D materials research may not only deliver faster electronics and new quantum devices but also results that any lab can repeat. In a field built on layers one atom thick, that kind of solidity might be the most valuable breakthrough of all.
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