22 papers · ranked by Valyu relevance
Sarah J. Boddington
Lower-carbon practices are socially complex-something that can challenge traditional disciplinary approaches. Researchers can find single disciplines inadequate in capturing the range of factors affecting how different groups engage with these practices. The present study addresses a critical gap in climate research…
Merel Talbi, Roosmarijn van Woerden
Oftentimes, interdisciplinary research is heralded as an effective way to approach complex problems from a diverse range of disciplinary perspectives. However, many scholars of interdisciplinary research agree that doing interdisciplinary work is difficult and prone to failure. In this paper, we argue that this…
Bagyasree Sudharsan, Alexandria Leto, Maria Leonor Pacheco
With the rising popularity of interdisciplinary work and increasing institutional incentives in this direction, there is a growing need to understand how resulting publications incorporate ideas from multiple disciplines. Existing computational approaches, such as affiliation diversity, keywords, and citation patterns…
Diya Mirji, Tiffany Degbotse, Sharmil Nanjappa, Jiayi Zhou + 8 more
Scientific discovery increasingly depends on interdisciplinary teams whose members contribute distinct expertise, conceptual frameworks, vocabularies, assumptions, and standards of evidence. Today's AI research assistants are largely designed to support individual researchers through literature review, writing…
Elina Apine, Marta Payo Payo, Amani Becker, Marta Meschini + 2 more
Despite facing multiple challenges, ECRs strongly acknowledge the benefits of interdisciplinary research for addressing complex problems and for their own professional development. The current overall research and funding landscape in the United Kingdom encourages interdisciplinary research. However, our research…
Jiyuan Xu, Yurui Mou, Lei Yuan
Cultivating adolescents' interdisciplinary innovation capability has become a central concern in secondary education, yet the psychological mechanism through which abstract conceptual resources are transformed into authentic innovative practice remains insufficiently understood. Drawing on theories of self-regulated…
Zeyu Li, Yalan Jin, Shuyu Chen, Tingxin Jiang + 2 more
Recent artificial intelligence has developed rapidly with significant interdisciplinary expansion, yet existing studies often treat it as a whole, lacking systematic long-term subfield comparisons and structural analyses, thereby limiting understanding of internal differences and evolutionary mechanisms. To address…
Authors not listed
We describe a collaborative research project spanning the disciplines of quantum hardware, quantum algorithms, conventional computational chemistry, synthetic medicinal chemistry and life sciences. Our project seeks to demonstrate an impact of quantum computing on human health. It is one of several funded by Wellcome…
Georgia Vesma
Background Despite critiques from across academia, double-anonymised peer review is still considered the ‘gold standard’ quality-assurance tool for the publication of academic research. While some journals make use of ‘open’ peer-review practices to make elements of academic publishing more transparent, anonymised is…
Dylan Riffle, Paul Rubery
Biodesign is an interdisciplinary research domain that incorporates principles from design and the life sciences to develop new systems, processes, and objects. Collegiate biodesign educators face unique pedagogical challenges, including an absence of relevant scholarship on curriculum design and instructional best…
Ghimire, Apekshya, Singh, Chandralekha
The second quantum revolution focuses on quantum information science and technology (QIST). It promises to bring about unprecedented improvements in computing, communication and sensing due to our ability to exquisitely control and manipulate quantum systems [1, 2]. This fast-growing field presents equally…
Fahimeh Orvati Nia, Joshua Peeples, Seth C. Murray, Andrew McFarland + 10 more
Advances in automation, imaging, and artificial intelligence have enabled researchers to capture large volumes of high-quality plant data for understanding crop growth, stress, and genotype-by-environment interactions. While genomics has achieved remarkable throughput, phenotypic data acquisition remains a critical…
Authors not listed
Chemistry curricula often separate “wet” experimental work from “dry” computation, yet modern discovery increasingly demands both. This Perspective offers an instructor-ready roadmap to train “hybrid chemists” within existing courses. We distill recent advances in machine learning, automation, and real-time analytics…
Okechukwu Kalu Iroha, Dauda Wadzani Palnam, Peter Abraham, Israel Ogwuche Ogra + 14 more
Bioscience encompasses studies on living organisms, their components, and their interactions, with the main aim of translating research into useful applications for medical, clinical, industrial, and environmental uses. The broad field of bioscience has witnessed tremendous growth in research output. This study was…
Zhanshan (Sam) Ma, Aaron M. Ellison
The concepts of heterogeneity and diversity are related but distinct, and are often conflated. 63 crystallized this distinction with the phrase “a zoo is diverse, whereas an ecosystem is heterogeneous”: while diversity quantifies discrete objects (e.g., species), heterogeneity captures the interactions among them as…
Authors not listed
As the utilization of artificial intelligence (AI) and generative AI (GenAI) is expanding in the educational field, presenting significant implications for STEM disciplines, it is bringing opportunities to enhance how chemistry and chemical engineering are taught and learned. This perspective critically explores the…
Georg Macher, Omar Veledar, Suad Krilašević, Raluca Coscodaru + 11 more
Europe faces a critical "translation gap" where doctoral excellence in academia often fails to convert into industrial impact. While Industry 5.0 demands a blend of technical depth, sustainability, and human-centric design, traditional higher academic education remains siloed. This paper presents an approach from the…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Authors not listed
Molecular dynamics (MD) and hybrid quantum–classical (QM/MM) methods provide powerful tools for simulating chemical and biological systems, yet their application to long-timescale, strongly coupled processes remains limited by non-integrability, chaotic sensitivity, and extreme time-scale separation. These limitations…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Matthew T. Davis, Brad L. Busse, Salsabil Arabi, Payam Meyer + 5 more
The ability to predict scientific breakthroughs at scale would accelerate the pace of discovery and improve the efficiency of research investments. Recent advances in artificial intelligence, graph theory, and computing power have provided new ways to pursue this elusive goal. We have identified a common signature…
Authors not listed
For decades, molecular visualization software has been fundamental to education and research in chemistry, structural biology, and materials science. These tools have enabled the inspection of structures, dynamics, and interactions, yet their reliance on two-dimensional (2D) interfaces imposes persistent limitations.…