Grand Challenge In Science Research Articles

Challenges to Public Administration Related to the Implementation of the Scientific and Technological Development Strategy of the Russian Federation

The author considers the requirements of the Decree of the President of Russia “On the Scientific and Technological Development Strategy of the Russian Federation” to the characteristics and principles of functioning of the public administration system in Russia. It is shown that the list of these characteristics and requirements is incomplete and insufficient for the implementation of the Decree. The main gaps in the requirements formed by the Decree relate to limiting the reconfiguration of the management system to only one subsystem, management in the field of scientific and technological development. The article argues that the complex nature of grand scientific and technological challenges implies profound changes in the public administration system as a whole, the transition from a structural and functional management system (a combination of meritocratic and client-oriented models) to a project management system (indicative and public-state models). The changes should affect the nomenclature and the scheme of interaction between structural divisions of state bodies, increase the level of project intra- and interdepartmental coordination. In addition, significant changes must be made in the public service system. We should organize training of specialists capable of using data analytics tools and data-based decision-making technologies as well as of carrying out an indicative assessment of project implementation indicators. The structure of the civil service should be associated with project offices and temporary performance of duties in these offices, and not only with permanent functions, taking into account the specifics of project service activities and project teams within government agencies. Civil servants should actively interact with independent expert structures and with civil society, which is the ultimate beneficiary of science and technology projects.

AlphaFold and Protein Folding: Not Dead Yet! The Frontier Is Conformational Ensembles.

Like the black knight in the classic Monty Python movie, grand scientific challenges such as protein folding are hard to finish off. Notably, AlphaFold is revolutionizing structural biology by bringing highly accurate structure prediction to the masses and opening up innumerable new avenues of research. Despite this enormous success, calling structure prediction, much less protein folding and related problems, "solved" is dangerous, as doing so could stymie further progress. Imagine what the world would be like if we had declared flight solved after the first commercial airlines opened and stopped investing in further research and development. Likewise, there are still important limitations to structure prediction that we would benefit from addressing. Moreover, we are limited in our understanding of the enormous diversity of different structures a single protein can adopt (called a conformational ensemble) and the dynamics by which a protein explores this space. What is clear is that conformational ensembles are critical to protein function, and understanding this aspect of protein dynamics will advance our ability to design new proteins and drugs.

A machine learning model that outperforms conventional global subseasonal forecast models

Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical weather predictions generated by the European Centre for Medium-Range Weather Forecasts (ECMWF), but have not yet surpassed conventional models at subseasonal timescales. This paper introduces FuXi Subseasonal-to-Seasonal (FuXi-S2S), a machine learning model that provides global daily mean forecasts up to 42 days, encompassing five upper-air atmospheric variables at 13 pressure levels and 11 surface variables. FuXi-S2S, trained on 72 years of daily statistics from ECMWF ERA5 reanalysis data, outperforms the ECMWF’s state-of-the-art Subseasonal-to-Seasonal model in ensemble mean and ensemble forecasts for total precipitation and outgoing longwave radiation, notably enhancing global precipitation forecast. The improved performance of FuXi-S2S can be primarily attributed to its superior capability to capture forecast uncertainty and accurately predict the Madden-Julian Oscillation (MJO), extending the skillful MJO prediction from 30 days to 36 days. Moreover, FuXi-S2S not only captures realistic teleconnections associated with the MJO but also emerges as a valuable tool for discovering precursor signals, offering researchers insights and potentially establishing a new paradigm in Earth system science research.

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. This knowledge is used to develop atomistically-informed, high-fidelity continuum and meso‑scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

Bodipy and Dipyrrin as Unexpected Robust Anchoring Groups on TiO2 Nanoparticles

Devising cost effective methods for efficiently capturing and storing solar energy is among the grand challenges of science (1). We are using insights from studies of natural photosynthetic systems (2) to develop bioinspired materials for photo-electrochemical water oxidation and solar fuel production by using molecular catalysts and dyes attached to mesoporous metal oxide photoanodes. Covalent attachment of molecules to metal oxide surfaces typically demands the presence of an anchoring group that in turn requires synthetic steps to introduce (3). BODIPY (4,4-difluoro-4-bora-3a,4a-diaza-s-indacene) chromophores have long been used in dye-sensitized solar cells, but carboxylic acid groups typically had to be installed to act as surface anchors. We now find that even without the introduction of such anchors, the unmodified BODIPY can bind to TiO2 surfaces via its BF2 group through boron–oxygen surface bonds. Dipyrrin, the parent molecule of BODIPY, is also capable of binding directly to TiO2 surfaces, likely through its chelating nitrogen atoms. These binding modes prove to be even more robust than that of an installed carboxylate and offer a new way to attach molecular complexes to surfaces for (photo)electrocatalytic applications since, once bound, we show that surface bound BODIPY and dipyrrin derivatives exhibit ultrafast photoinjection of electrons into the conduction band of TiO2 (4). Directing Matter and Energy: Five Challenges for Science and the Imagination, U.S. Department of Energy, Washington, DC, December 2007.D.J. Vinyard and G.W. Brudvig, Annu. Rev. Phys. Chem. (2017) 68, 101.K.L. Materna, R.H. Crabtree and G.W. Brudvig, Chem. Soc. Rev. (2017) 46, 6099.J.A. Jayworth et al., Dalton Trans. (2022) 51, 14260.

(Invited) Water Oxidation Catalysis with Atomically Defined Active Sites on Nanostructured Materials for Solar Energy Applications

Devising cost effective methods for efficiently capturing and storing solar energy is among the grand challenges of science (1). We are using insights from studies of natural photosynthetic systems (2) to develop bioinspired materials for photo-electrochemical water oxidation and solar fuel production by using molecular catalysts and dyes attached to mesoporous metal oxide photoanodes. Molecular catalysts are known for their high activity and tunability, but their solubility and limited stability often restrict their use in practical applications. We are developing anchoring chemistry to attach molecular water-oxidation catalysts to metal oxide surfaces (3), which not only greatly increases the stability of the molecular catalyst but also improves the catalytic performance of the oxide material. Our progress on the development and characterization of molecular iridium, copper and manganese water-oxidation catalysts (4-5), along with their application for photoelectrochemical water oxidation (6) and solar fuel production, will be discussed. Directing Matter and Energy: Five Challenges for Science and the Imagination, U.S. Department of Energy, Washington, DC, December 2007.D.J. Vinyard and G.W. Brudvig, Annu. Rev. Phys. Chem. (2017) 68, 101.J.L. Troiano, R.H. Crabtree and G.W. Brudvig, ACS Appl. Mater. Interfaces (2022) 14, 6582.S.W. Sheehan et al., Nature Comm. (2015) 6, 6469.K.J. Fisher et al., ACS Catalysis (2017) 7, 3384.Y. Zhao et al., Proc. Natl. Acad. Sci. U.S.A. (2018) 115, 2902.

Modelling the film fragmentation of industrial-scale centrifugal granulation of high-temperature molten slag

Centrifugal-granulation-assisted thermal energy recovery (CGATER) is one of the most promising routes to enable waste heat harvest from molten slags. However, it remains a grand scientific and technological challenge to produce fine particles from the bulk high-temperature molten slag, especially at large slag throughput. In this work, we established an improved model to simulate the centrifugal granulation at the large flowrate comparable to the laboratory- pilot-scale trials. For the first time, film fragmentation has been successfully reproduced by modelling. On this basis, we elucidated the intricate film fragmentation by quantifying the off-atomizer film characteristics at various operational conditions, with a strong focus on the metrics of the off-atomizer slag film. The present study provides an important and valuable CFD model to approach the underlying physics of film fragmentation. Most importantly, it opens up new possibilities for predicting slag droplet formation at experimentally unavailable operational conditions.

Heat decarbonization: Toward a sustainable utility system

Heat source decarbonization has not received the same attention as electricity. A recent Joule paper by Gilbert et al. presents a multi-scale study for the selection of the best source and technology depending on the heat temperature level, showing that hydrogen can become competitive with natural gas by 2050. Heat source decarbonization has not received the same attention as electricity. A recent Joule paper by Gilbert et al. presents a multi-scale study for the selection of the best source and technology depending on the heat temperature level, showing that hydrogen can become competitive with natural gas by 2050. Heat source and application-dependent levelized cost of decarbonized heatGilbert et al.JouleDecember 15, 2022In BriefCost-effective decarbonization of heat is a grand scientific and technological challenge. We develop a generalizable technoeconomic framework to calculate the levelized cost of heat (LCOH) for heat that is carbon neutral. We conduct case studies representative of industrial processes and commercial building heating in the United States. Natural gas is likely the cheapest heat source even after paying for carbon capture, and dramatic reductions in the cost and availability of renewable energy are needed for cost- and emissions-favorable electrification. Full-Text PDF

Physically-based interpretation of abnormal stress relaxation response in glassy polymers

Understanding the mechanical responses of glassy polymers remains a grand scientific challenge for many decades, which plays a central role in the application of these materials. In this work, we have performed stress relaxation tests on a series of glassy polymers. An abnormal rate-dependent stress relaxation response is revealed, featuring as a larger stress drop and smaller quasi-steady-state stress with increasing the initial loading rate. To explore the underlying deformation mechanism, we further carry out a coarse-grained molecular dynamics simulation on glassy polymers, which qualitatively demonstrates the experimental observations. The underlying physical mechanism is revealed to be that a larger initial loading rate can lead to a more-activated structure state of polymers. Based on these findings, we develop a physically-based model by introducing the effective temperature model into the shear transformation zone (STZ) theory. The effective temperature, as an internal variable, can describe the deformation-induced structural evolution of amorphous polymers. The Adam–Gibbs model is then adopted to relate the effective temperature with the transformation rates of STZ sites. Comparison with experimental results shows that the micro-mechanical model can capture the rate-dependent stress–strain relationship in the loading process as well as the abnormal stress relaxation responses. In comparison, it is challenging to rationalize this abnormal behavior based on classic viscoplastic models due to a lack of physical mechanisms. Thus, this work promotes our understanding of the origin of complex mechanical responses of glassy polymers that are strongly related to the evolution of microstructure upon deformation.

Barotropic energy conversion during Indian summer monsoon: implication of Central Indian Ocean Mode Simulation in CMIP6

The simulation and prediction of the Indian summer monsoon (ISM) and its intraseasonal component in climate models remain a grand scientific challenge for numerical simulations. Recently, an intraseasonal mode was proposed over the tropical Indian Ocean, named central Indian Ocean (CIO) mode. The CIO mode index and the monsoon intraseasonal oscillations (MISO) have a high correlation. In this study, the simulations of the CIO mode in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models are examined. Although the coupled ocean–atmosphere feedbacks associated with the CIO mode are not fully reproduced, the results show that a better depiction of the CIO mode in CMIP6 models is favorable for a better simulation of northward-propagating MISO and heavy rainfall during the ISM. Dynamic diagnostics unveil that the rendition of the CIO mode is dominated by kinetic energy conversion from the background to the intraseasonal variability. Furthermore, kinetic energy conversion is controlled by the meridional shear of background zonal winds (\(\frac{\partial \overline{u}}{\partial y }\)), which is underestimated in most CMIP6 models, leading to a weak barotropic instability. As a result, a better simulation of \(\frac{\partial \overline{u}}{\partial y }\) is required for improving the CIO mode simulation in climate models, which helps to improve the simulation and prediction skill of northward-propagating MISO and monsoonal precipitation.

A reduced level of consciousness affects non-conscious processes

Being conscious is a profound aspect of human existence, and understanding its function and its inception is considered one of the truly grand scientific challenges. However, the nature of consciousness remains enigmatic, to a large part because “being conscious” can refer to both the content (phenomenology) and the level (arousal) of consciousness, and how these different aspects are related remains unclear. To empirically assess the relation between level and content of consciousness, we manipulated these two aspects by presenting stimuli consciously or non-consciously and by using Propofol sedation, while brain activity was measured using fMRI. We observed that sedation affected both conscious and non-conscious processes but at different hierarchical levels; while conscious processing was altered in higher-order regions (the intraparietal sulcus) and spared sensory areas, the opposite effect was observed for non-conscious processing. The observation that Propofol affected non-conscious processing calls for a reconsideration of what kind of information one can gain on “consciousness” from recording neural responses to sedation without considering both (content) conscious and (content) non-conscious processing.

Using Robinson-Foulds supertrees in divide-and-conquer phylogeny estimation

One of the Grand Challenges in Science is the construction of the Tree of Life, an evolutionary tree containing several million species, spanning all life on earth. However, the construction of the Tree of Life is enormously computationally challenging, as all the current most accurate methods are either heuristics for NP-hard optimization problems or Bayesian MCMC methods that sample from tree space. One of the most promising approaches for improving scalability and accuracy for phylogeny estimation uses divide-and-conquer: a set of species is divided into overlapping subsets, trees are constructed on the subsets, and then merged together using a “supertree method”. Here, we present Exact-RFS-2, the first polynomial-time algorithm to find an optimal supertree of two trees, using the Robinson-Foulds Supertree (RFS) criterion (a major approach in supertree estimation that is related to maximum likelihood supertrees), and we prove that finding the RFS of three input trees is NP-hard. Exact-RFS-2 is available in open source form on Github at https://github.com/yuxilin51/GreedyRFS.

Simulation of Central Indian Ocean Mode in S2S Models

AbstractSimulation of monsoon intraseasonal oscillations (MISO) during the Indian summer monsoon (ISM) is a grand scientific challenge. The Subseasonal‐to‐Seasonal (S2S) prediction project provides a unique way to examine the key dynamics of MISO. Recently, a Central Indian Ocean (CIO) mode was proposed as an intrinsic climate mode over the Indian Ocean, and it has a close relation with MISO during the ISM. In this study, the simulations of the CIO mode events in S2S models are examined. The results confirm that a better rendition of the CIO mode in S2S models tends to result in a better simulation of northward propagating MISO and leads to stronger subseasonal rainfall during the ISM. The positive CIO mode cases are classified into well‐simulated and poorly simulated groups. It is shown that the barotropic energy conversion due to the meridional shear of background zonal winds ( ) enhances the kinetic energy at subseasonal timescales during the CIO mode in the well‐simulated group, which also agrees with observations. As a result, the enhanced meridional wind anomalies transport moisture from the tropics to the subtropics and reinforce midtropospheric moisture loading in the subtropics, which nourishes the northward propagating MISO. Therefore, a better simulation of and moisture transport by subseasonal meridional wind anomalies are required to improve the CIO mode simulation, which is expected to benefit the simulation and prediction of MISO during the ISM.

Tackling the Challenges of 21st-Century Open Science and Beyond: A Data Science Lab Approach

SummaryIn recent years, there has been a drive toward more open, cross-disciplinary science taking center stage. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop methods, and disseminate their results to stakeholders and decision makers. We present our vision of a “data science lab” as a collaborative space where scientists (from different disciplines), stakeholders, and policy makers can create data-driven solutions to environmental science's grand challenges. We set out a clear and defined research roadmap to serve as a focal point for an international research community progressing toward a more data-driven and transparent approach to environmental data science, centered on data science labs. This includes ongoing case studies of good practice, with the infrastructural and methodological developments required to enable data science labs to support significant increase in our cross- and trans-disciplinary science capabilities.

Direct transformation of dinitrogen: synthesis of N-containing organic compounds via N-C bond formation.

N-containing organic compounds are of vital importance to lives. Practical synthesis of valuable N-containing organic compounds directly from dinitrogen (N2), not through ammonia (NH3), is a holy-grail in chemistry and chemical industry. An essential step for this transformation is the functionalization of the activated N2 units/ligands to generate N−C bonds. Pioneering works of transition metal-mediated direct conversion of N2 into organic compounds via N−C bond formation at metal-dinitrogen [N2-M] complexes have generated diversified coordination modes and laid the foundation of understanding for the N−C bond formation mechanism. This review summarizes those major achievements and is organized by the coordination modes of the [N2-M] complexes (end-on, side-on, end-on-side-on, etc.) that are involved in the N−C bond formation steps, and each part is arranged in terms of reaction types (N-alkylation, N-acylation, cycloaddition, insertion, etc.) between [N2-M] complexes and carbon-based substrates. Additionally, earlier works on one-pot synthesis of organic compounds from N2 via ill-defined intermediates are also briefed. Although almost all of the syntheses of N-containing organic compounds via direct transformation of N2 so far in the literature are realized in homogeneous stoichiometric thermochemical reaction systems and are discussed here in detail, the sporadically reported syntheses involving photochemical, electrochemical, heterogeneous thermo-catalytic reactions, if any, are also mentioned. This review aims to provide readers with an in-depth understanding of the state-of-the-art and perspectives of future research particularly in direct catalytic and efficient conversion of N2 into N-containing organic compounds under mild conditions, and to stimulate more research efforts to tackle this long-standing and grand scientific challenge.

Detectability of Life Using Oxygen on Pelagic Planets and Water Worlds

Abstract The search for life on exoplanets is one of the grand scientific challenges of our time. The strategy to date has been to find (e.g., through transit surveys like Kepler) earthlike exoplanets in their stars’ habitable zone, then use transmission spectroscopy to measure biosignature gases, especially oxygen, in the planets’ atmospheres (e.g., using James Webb Space Telescope (JWST)). Already there are more such planets than can be observed by JWST, and missions like the Transiting Exoplanet Survey Satellite and others will find more. A better understanding of the geochemical cycles relevant to biosignature gases is needed, to prioritize targets for costly follow-up observations and to help design future missions. We define a Detectability Index to quantify the likelihood that a biosignature gas could be assigned a biological versus nonbiological origin. We apply this index to the case of oxygen gas, O2, on earthlike planets with varying water contents. We demonstrate that on earthlike exoplanets with 0.2 weight percent (wt%) water (i.e., no exposed continents) a reduced flux of bioessential phosphorus limits the export of photosynthetically produced atmospheric O2 to levels indistinguishable from geophysical production by photolysis of water plus hydrogen escape. Higher water contents >1 wt% that lead to high-pressure ice mantles further slow phosphorus cycling. Paradoxically, the maximum water content allowing use of O2 as a biosignature, 0.2 wt%, is consistent with no water based on mass and radius. Thus, the utility of an O2 biosignature likely requires the direct detection of both water and land on a planet.

Forgotten Legacies: Understanding and Mitigating Historical Human Alterations of River Corridors

AbstractLegacies are persistent changes in natural systems resulting from human activities. Legacies that affect river ecosystems can result from human alterations outside of the river corridor, such as timber harvest or urbanization, or from alterations within the river corridor, including flow regulation, river engineering, and removal of large wood and beaver dams. Human alterations of river ecosystems have been occurring for thousands of years in some parts of the world and are now ubiquitous, yet both river scientists and the public may be unaware of the persistent effects of historical activities. Failure to recognize the legacy of historical activities that no longer occur can skew perceptions of river process and form and the natural range of variability in river ecosystems. Examples come from rivers of the Mid‐Atlantic Piedmont and the Pacific Northwest regions of the United States. Mid‐Atlantic Piedmont streams in which legacy sediment accumulated behind now‐abandoned mill dams experienced a complete transformation from wide, shallow, marshy valleys to sinuous rivers lined with tall cutbanks, but the existence and the cause of this river metamorphosis was not widely recognized until the first decade of the 21st century. Rivers of the Pacific Northwest from which large wood was removed have changed during the past century from spatially heterogeneous, multichannel systems closely connected to their floodplains via frequent channel avulsion and lateral migration to single‐thread channels with more homogeneous floodplains and less lateral connectivity. Again, this river metamorphosis has only been recognized within the past two decades. In each of these regional examples, river process and form have changed so substantially that the river ecosystems can be described as having assumed an alternative state. In these and many other examples, the alternative state provides lower levels of ecosystem services such as habitat, biodiversity, and attenuation of downstream fluxes of water, sediment, organic carbon, and nutrients. River management designed to enhance and restore these ecosystem services can be more effective if the continuing effects of these historical legacies are recognized. The grand scientific challenges resulting from historical human alterations of river ecosystems include the following: (1) to recognize the existence of a legacy that continues to affect river ecosystem process and form; (2) to understand the source of the legacy with respect to chronology, type, spatial extent, and intensity of human activities; (3) to understand the implications of the legacy regarding how river process and form and river ecosystem services have changed; and (4) to design management or restoration strategies that can mitigate the loss of river ecosystem services. In summary, the existence of forgotten legacies challenges river scientists to recognize the continuing effects of human activities that have long since ceased and also poses challenges for the application of scientific understanding to resource management. Societal expectations for attractive, simple, stable rivers are commonly at odds with scientific understanding of rivers as dynamic, spatially heterogeneous, nonlinear ecosystems. Knowledge of how human actions, including historical actions that have long since ceased, continue to alter river ecosystems can help to bridge the gap between societal and scientific perceptions of rivers.

Migrating parallel applications to the cloud: assessing cloud readiness based on parallel design decisions

Parallel applications are the computational backbone of major industry trends and grand challenges in science. Whereas these applications are typically constructed for dedicated High Performance Computing clusters and supercomputers, the cloud emerges as attractive execution environment, which provides on-demand resource provisioning and a pay-per-use model. However, cloud environments require specific application properties that may restrict parallel application design. As a result, design trade-offs are required to simultaneously maximize parallel performance and benefit from cloud-specific characteristics. In this paper, we present a novel approach to assess the cloud readiness of parallel applications based on the design decisions made. By discovering and understanding the implications of these parallel design decisions on an application’s cloud readiness, our approach supports the migration of parallel applications to the cloud. We introduce an assessment procedure, its underlying meta model, and a corresponding instantiation to structure this multi-dimensional design space. For evaluation purposes, we present an extensive case study comprising three parallel applications and discuss their cloud readiness based on our approach.

Dielectric Elastomer Artificial Muscle: Materials Innovations and Device Explorations.

Creating an artificial muscle has been one of the grand challenges of science and engineering. The invention of such a flexible, versatile, and power efficient actuator opens the gate for a new generation of lightweight, highly efficient, and multifunctional robotics. Many current artificial muscle technologies enable low-power mobile actuators, robots that mimic efficient and natural forms of motion, autonomous robots and sensors, and lightweight wearable technologies. They also have serious applications in biomedical devices, where biocompatibility, from a chemical, flexibility, and force perspective, is crucial. It remains unknown which material will ultimately form the ideal artificial muscle. Anything from shape memory alloys (SMAs) to pneumatics to electroactive polymers (EAPs) realize core aspects of the artificial muscle goal. Among them, EAPs most resemble their biological counterparts, and they encompass both ion-infusion and electric field based actuation mechanisms. Some of the most investigated EAPs are dielectric elastomers (DEs), whose large strains, fracture toughness, and power-to-weight ratios compare favorably with natural muscle. Although dielectric elastomer actuators (DEAs) only entered the artificial muscle conversation in the last 20 years, significant technological progress has reflected their high potential. Research has focused on solving the core issues surrounding DEAs, which includes improving their operational ranges with regard to temperature and voltage, adding new functionality to the materials, and improving the reliability of the components on which they depend. Mechanisms designed to utilize their large-strain actuation and low stiffness has also attracted attention. This Account covers important research by our group and others in various avenues such as decreasing viscoelastic losses in typical DE materials, increasing their dielectric constant, and countering electromechanical instability. We also discuss variable stiffness polymers, specifically bistable electroactive polymers, which, notably, open DEAs to structural applications typically unattainable for soft-actuator technologies. Furthermore, we explore advancements related to highly compliant and transparent electrodes, a crucial component of DEAs capable of achieving high actuation strain. We then cover noteworthy applications, including several novel devices for soft robotics and microfluidics, and how those applications fit within other major developments in the field. Finally, we conclude with a discussion of the remaining challenges facing current DEA technology and speculate on research directions that may further advance DE-based artificial muscles as a whole. This Account serves as a stepping stone into the field of EAPs, which, through the work of researchers worldwide, are positioned as a potential challenger to conventional actuator technologies.

Universities’ structural commitment to interdisciplinary research

In recent years, science policy experts have been promoting interdisciplinary research (IDR) in order to foster innovation and address grand scientific challenges. But to date we know little about whether, how, and to what extent universities are committed to fostering this type of research. This paper develops the first measure of university commitment to IDR, which relies on the organizational structuring of research activity into research centers and departments. We extend the previous literature by measuring, rather than assuming, the interdisciplinary nature of research units. Using a large amount of textual data from 157 research universities in the United States, and combining machine learning and confirmatory factor analysis techniques, we develop a continuous and composite measure that taps universities’ structural commitment to IDR. We then examine the commitment exhibited by specific universities and how such commitment varies by university characteristics like size, resources, and region. Results show that the fraction of centers and departments that are interdisciplinary is critical to measuring a university’s structural commitment to IDR and to developing specific research policies aimed at fostering IDR.