CiteScore: 4.7 / Journal Citation Indicator (JCI): 1.06
These journal metrics put Research in the top 10% of the Scopus multidisciplinary category and the top 12% of the Web of Science multidisciplinary category!Journal Indexing Information
The open access journal Research, published in association with CAST, publishes innovative, wide-ranging research in life sciences, physical sciences, engineering and applied science.
Research's Editorial Board includes international experts in fields ranging from life sciences to physical sciences. Tianhong Cui of University of Minnesota and Wei Huang of Northwestern Polytechnical University, China serve as the Editors-in-Chief of the journal.
Latest ArticlesMore articles
Highly Robust and Wearable Facial Expression Recognition via Deep-Learning-Assisted, Soft Epidermal Electronics
The facial expressions are a mirror of the elusive emotion hidden in the mind, and thus, capturing expressions is a crucial way of merging the inward world and virtual world. However, typical facial expression recognition (FER) systems are restricted by environments where faces must be clearly seen for computer vision, or rigid devices that are not suitable for the time-dynamic, curvilinear faces. Here, we present a robust, highly wearable FER system that is based on deep-learning-assisted, soft epidermal electronics. The epidermal electronics that can fully conform on faces enable high-fidelity biosignal acquisition without hindering spontaneous facial expressions, releasing the constraint of movement, space, and light. The deep learning method can significantly enhance the recognition accuracy of facial expression types and intensities based on a small sample. The proposed wearable FER system is superior for wide applicability and high accuracy. The FER system is suitable for the individual and shows essential robustness to different light, occlusion, and various face poses. It is totally different from but complementary to the computer vision technology that is merely suitable for simultaneous FER of multiple individuals in a specific place. This wearable FER system is successfully applied to human-avatar emotion interaction and verbal communication disambiguation in a real-life environment, enabling promising human-computer interaction applications.
Highly Dynamic Polynuclear Metal Cluster Revealed in a Single Metallothionein Molecule
Human metallothionein (MT) is a small-size yet efficient metal-binding protein, playing an essential role in metal homeostasis and heavy metal detoxification. MT contains two domains, each forming a polynuclear metal cluster with an exquisite hexatomic ring structure. The apoprotein is intrinsically disordered, which may strongly influence the clusters and the metal-thiolate (M-S) bonds, leading to a highly dynamic structure. However, these features are challenging to identify due to the transient nature of these species. The individual signal from dynamic conformations with different states of the cluster and M-S bond will be averaged and blurred in classic ensemble measurement. To circumvent these problems, we combined a single-molecule approach and multiscale molecular simulations to investigate the rupture mechanism and chemical stability of the metal cluster by a single MT molecule, focusing on the Zn4S11 cluster in the α domain upon unfolding. Unusual multiple unfolding pathways and intermediates are observed for both domains, corresponding to different combinations of M-S bond rupture. None of the pathways is clearly preferred suggesting that unfolding proceeds from the distribution of protein conformational substates with similar M-S bond strengths. Simulations indicate that the metal cluster may rearrange, forming and breaking metal-thiolate bonds even when MT is folded independently of large protein backbone reconfiguration. Thus, a highly dynamic polynuclear metal cluster with multiple conformational states is revealed in MT, responsible for the binding promiscuity and diverse cellular functions of this metal-carrier protein.
Efficient and Stable Large-Area Perovskite Solar Cells with Inorganic Perovskite/Carbon Quantum Dot-Graded Heterojunction
This work reports on a compositionally graded heterojunction for photovoltaic application by cooperating fluorine-doped carbon quantum dots (FCQDs in short) into the CsPbI2.5Br0.5 inorganic perovskite layer. Using this CsPbI2.5Br0.5/FCQDs graded heterojunction in conjunction with low-temperature-processed carbon electrode, a power conversion efficiency of 13.53% for 1 cm2 all-inorganic perovskite solar cell can be achieved at AM 1.5G solar irradiation. To the best of our knowledge, this is one of the highest efficiency reported for carbon electrode based all-inorganic perovskite solar cells so far, and the first report of 1 cm2 carbon counter electrode based inorganic perovskite solar cell with PCE exceeding 13%. Moreover, the inorganic perovskite/carbon quantum dot graded heterojunction photovoltaics maintained over 90% of their initial efficiency after thermal aging at 85° for 1056 hours. This conception of constructing inorganic perovskite/FCQDs graded heterojunction offers a feasible pathway to develop efficient and stable photovoltaics for scale-up and practical applications.
A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping
Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor’s applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.
Interwrapping Distinct Metal-Organic Frameworks in Dual-MOFs for the Creation of Unique Composite Catalysts
Incorporating metal nanoparticles (MNPs) inside metal-organic frameworks (MOFs) demonstrates superior catalytic properties in numerous reactions; however, the size and distribution of MNPs could not be well controlled, resulting in low product selectivity in catalysis by undergoing different catalytic reaction pathways. We report herein a facile strategy for integrating lattice-mismatched MOFs together to fabricate homogeneously distributed “dual-MOFs,” which are the ideal precursors for the preparation of MNPs@MOFs with unique catalytic properties. As a proof of concept, we successfully synthesize a dual-MOF HKUST-1/ZIF-8 for in situ creation of redox-active Cu NPs inside hierarchical porous ZIF-8 under controlled pyrolytic conditions. Combining the advantages of size-tunable Cu NPs in the molecular sieving matrix of ZIF-8, Cu@ZIF-8 demonstrates high activity and selectivity for transformation of alkynes into alkenes without overhydrogenation, which surpasses most of the catalysts in the literature. Therefore, this work paves a new pathway for developing highly efficient and selective heterogeneous catalysts to produce highly value-added chemicals.
Single-Cell Microwell Platform Reveals Circulating Neural Cells as a Clinical Indicator for Patients with Blood-Brain Barrier Breakdown
Central nervous system diseases commonly occur with the destruction of the blood-brain barrier. As a primary cause of morbidity and mortality, stroke remains unpredictable and lacks cellular biomarkers that accurately quantify its occurrence and development. Here, we identify NeuN+/CD45−/DAPI+ phenotype nonblood cells in the peripheral blood of mice subjected to middle cerebral artery occlusion (MCAO) and stroke patients. Since NeuN is a specific marker of neural cells, we term these newly identified cells as circulating neural cells (CNCs). We find that the enumeration of CNCs in the blood is significantly associated with the severity of brain damage in MCAO mice (). Meanwhile, the number of CNCs is significantly higher in stroke patients than in negative subjects (). These findings suggest that the amount of CNCs in circulation may serve as a clinical indicator for the real-time prognosis and progression monitor of the occurrence and development of ischemic stroke and other nervous system disease.