Efficient Binary Weight Convolutional Network Accelerator for Speech Recognition.

Speech recognition has progressed tremendously in the area of artificial intelligence (AI). However, the performance of the real-time offline Chinese speech recognition neural network accelerator for edge AI needs to be improved. This paper proposes a configurable convolutional neural network accelerator based on a lightweight speech recognition model, which can dramatically reduce hardware resource consumption while guaranteeing an acceptable error rate. For convolutional layers, the weights are binarized to reduce the number of model parameters and improve computational and storage efficiency. A multichannel shared computation (MCSC) architecture is proposed to maximize the reuse of weight and feature map data. The binary weight-sharing processing engine (PE) is designed to avoid limiting the number of multipliers. A custom instruction set is established according to the variable length of voice input to configure parameters for adapting to different network structures. Finally, the ping-pong storage method is used when the feature map is an input. We implemented this accelerator on Xilinx ZYNQ XC7Z035 under the working frequency of 150 MHz. The processing time for 2.24 s and 8 s of speech was 69.8 ms and 189.51 ms, respectively, and the convolution performance reached 35.66 GOPS/W. Compared with other computing platforms, accelerators perform better in terms of energy efficiency, power consumption and hardware resource consumption.

Prevalence of phase variable epigenetic invertons among host-associated bacteria.

Type I restriction-modification (R-M) systems consist of a DNA endonuclease (HsdR, HsdM and HsdS subunits) and methyltransferase (HsdM and HsdS subunits). The hsdS sequences flanked by inverted repeats (referred to as epigenetic invertons) in certain Type I R-M systems undergo invertase-catalyzed inversions. Previous studies in Streptococcus pneumoniae have shown that hsdS inversions within clonal populations produce subpopulations with profound differences in the methylome, cellular physiology and virulence. In this study, we bioinformatically identified six major clades of the tyrosine and serine family invertases homologs from 16 bacterial phyla, which potentially catalyze hsdS inversions in the epigenetic invertons. In particular, the epigenetic invertons are highly enriched in host-associated bacteria. We further verified hsdS inversions in the Type I R-M systems of four representative host-associated bacteria and found that each of the resultant hsdS allelic variants specifies methylation of a unique DNA sequence. In addition, transcriptome analysis revealed that hsdS allelic variations in Enterococcus faecalis exert significant impact on gene expression. These findings indicate that epigenetic switches driven by invertases in the epigenetic invertons broadly operate in the host-associated bacteria, which may broadly contribute to bacterial host adaptation and virulence beyond the role of the Type I R-M systems against phage infection.

A di-iron protein recruited as an Fe[II] and oxygen sensor for bacterial chemotaxis functions by stabilizing an iron-peroxy species.

Many bacteria contain cytoplasmic chemoreceptors that lack sensor domains. Here, we demonstrate that such cytoplasmic receptors found in 8 different bacterial and archaeal phyla genetically couple to metalloproteins related to ß-lactamases and nitric oxide reductases. We show that this oxygen-binding di-iron protein (ODP) acts as a sensor for chemotactic responses to both iron and oxygen in the human pathogen Treponema denticola (Td). The ODP di-iron site binds oxygen at high affinity to reversibly form an unusually stable µ-peroxo adduct. Crystal structures of ODP from Td and the thermophile Thermotoga maritima (Tm) in the Fe[III]2-O22-, Zn[II], and apo states display differences in subunit association, conformation, and metal coordination that indicate potential mechanisms for sensing. In reconstituted systems, iron-peroxo ODP destabilizes the phosphorylated form of the receptor-coupled histidine kinase CheA, thereby providing a biochemical link between oxygen sensing and chemotaxis in diverse prokaryotes, including anaerobes of ancient origin.

Measuring and modeling energy and power consumption in living microbial cells with a synthetic ATP reporter.

BACKGROUND: Adenosine triphosphate (ATP) is the main energy carrier in living organisms, critical for metabolism and essential physiological processes. In humans, abnormal regulation of energy levels (ATP concentration) and power consumption (ATP consumption flux) in cells is associated with numerous diseases from cancer, to viral infection and immune dysfunction, while in microbes it influences their responses to drugs and other stresses. The measurement and modeling of ATP dynamics in cells is therefore a critical component in understanding fundamental physiology and its role in pathology. Despite the importance of ATP, our current understanding of energy dynamics and homeostasis in living cells has been limited by the lack of easy-to-use ATP sensors and the lack of models that enable accurate estimates of energy and power consumption related to these ATP dynamics. Here we describe a dynamic model and an ATP reporter that tracks ATP in E. coli over different growth phases. RESULTS: The reporter is made by fusing an ATP-sensing rrnB P1 promoter with a fast-folding and fast-degrading GFP. Good correlations between reporter GFP and cellular ATP were obtained in E. coli growing in both minimal and rich media and in various strains. The ATP reporter can reliably monitor bacterial ATP dynamics in response to nutrient availability. Fitting the dynamics of experimental data corresponding to cell growth, glucose, acetate, dissolved oxygen, and ATP yielded a mathematical and circuit model. This model can accurately predict cellular energy and power consumption under various conditions. We found that cellular power consumption varies significantly from approximately 0.8 and 0.2 million ATP/s for a tested strain during lag and stationary phases to 6.4 million ATP/s during exponential phase, indicating ~ 8-30-fold changes of metabolic rates among different growth phases. Bacteria turn over their cellular ATP pool a few times per second during the exponential phase and slow this rate by ~ 2-5-fold in lag and stationary phases. CONCLUSION: Our rrnB P1-GFP reporter and kinetic circuit model provide a fast and simple way to monitor and predict energy and power consumption dynamics in bacterial cells, which can impact fundamental scientific studies and applied medical treatments in the future.

UIO-66-NH2 -Derived Mesoporous Carbon Catalyst Co-Doped with Fe/N/S as Highly Efficient Cathode Catalyst for PEMFCs.

Efficient, low-cost catalysts are desirable for the sluggish oxygen reduction reaction (ORR). Herein, UIO-66-NH2 -derived multi-element (Fe, S, N) co-doped porous carbon catalyst is reported, Fe/N/S-PC, with an octahedral morphology, a well-defined mesoporous structure, and highly dispersed doping elements, synthesized by a double-solvent diffusion-pyrolysis method (DSDPM). The morphology of the UIO-66-NH2 precursor is perfectly inherited by the derived carbon material, resulting in a high surface area, a well-defined mesoporous structure, and atomic-level dispersion of the doping elements. Fe/N/S-PC demonstrates outstanding catalytic activity and durability for the ORR in both alkaline and acidic solutions. In 0.1 m KOH, its half-potential reaches 0.87 V (vs reversible hydrogen electrode (RHE)), 30 mV more positive than that of a 20 wt% Pt/C catalyst. In 0.1 m HClO4 , it reaches 0.785 V (vs RHE), only 65 mV less than that of Pt/C. The catalyst also exhibits excellent performance in acidic hydrogen/oxygen proton exchange membrane fuel cells. A membrane electrode assembly (MEA) with the catalyst as the cathode reaches 700 mA·cm-2 at 0.6 V and a maximum power density of 553 mW·cm-2 , ranking it among the best MEAs with a nonprecious metal catalyst as the cathode.

Zinc-motivated Fe/Fe5C2/Fe1-xS@Fe-N-C active sites grown on N-doped porous carbon toward efficient oxygen reduction reaction in zinc-air batteries.

The development of efficient non-precious metal oxygen reduction reaction catalysts to replace Pt-based catalysts is of great significance to accelerate the commercial application of fuel cells. In this study, a hierarchical porous carbon oxygen reduction reaction catalyst with Fe/Fe5C2/Fe1-xS@Fe-N-C active sites was developed via a simple and efficient solid-phase synthesis method. The introduction of zinc inhibited the growth and agglomeration of the nanoparticles and induced the formation of active nitrogen species and porosity, thus boosting the catalytic activity. The optimal FeZn-N-C-1 catalyst exhibited a high half-wave potential of 0.846 V, which is 24 mV higher than that of the commercial Pt/C, with a 4-e- reaction path under alkaline conditions. When the FeZn-N-C-1 catalyst is employed as a cathode in a zinc-air battery, it achieves a high open circuit voltage of 1.54 V, power density of 143.6 mW cm-2 and specific capacity of 804 mA h g-1.

Drug Cocktail Formulation via Circuit Design.

Electronic circuits intuitively visualize and quantitatively simulate biological systems with nonlinear differential equations that exhibit complicated dynamics. Drug cocktail therapies are a powerful tool against diseases that exhibit such dynamics. We show that just six key states, which are represented in a feedback circuit, enable drug-cocktail formulation: 1) healthy cell number; 2) infected cell number; 3) extracellular pathogen number; 4) intracellular pathogenic molecule number; 5) innate immune system strength; and 6) adaptive immune system strength. To enable drug cocktail formulation, the model represents the effects of the drugs in the circuit. For example, a nonlinear feedback circuit model fits measured clinical data, represents cytokine storm and adaptive autoimmune behavior, and accounts for age, sex, and variant effects for SARS-CoV-2 with few free parameters. The latter circuit model provided three quantitative insights on the optimal timing and dosage of drug components in a cocktail: 1) antipathogenic drugs should be given early in the infection, but immunosuppressant timing involves a tradeoff between controlling pathogen load and mitigating inflammation; 2) both within and across-class combinations of drugs have synergistic effects; 3) if they are administered sufficiently early in the infection, anti-pathogenic drugs are more effective at mitigating autoimmune behavior than immunosuppressant drugs.

Sorption of Cellulases in Biofilm Enhances Cellulose Degradation by Bacillus subtilis.

Biofilm commonly forms on the surfaces of cellulosic biomass but its roles in cellulose degradation remain largely unexplored. We used Bacillus subtilis to study possible mechanisms and the contributions of two major biofilm components, extracellular polysaccharides (EPS) and TasA protein, to submerged biofilm formation on cellulose and its degradation. We found that biofilm produced by B. subtilis is able to absorb exogenous cellulase added to the culture medium and also retain self-produced cellulase within the biofilm matrix. The bacteria that produced more biofilm degraded more cellulose compared to strains that produced less biofilm. Knockout strains that lacked both EPS and TasA formed a smaller amount of submerged biofilm on cellulose than the wild-type strain and also degraded less cellulose. Imaging of biofilm on cellulose suggests that bacteria, cellulose, and cellulases form cellulolytic biofilm complexes that facilitate synergistic cellulose degradation. This study brings additional insight into the important functions of biofilm in cellulose degradation and could potentiate the development of biofilm-based technology to enhance biomass degradation for biofuel production.

Rapid modeling of experimental molecular kinetics with simple electronic circuits instead of with complex differential equations.

Kinetic modeling has relied on using a tedious number of mathematical equations to describe molecular kinetics in interacting reactions. The long list of differential equations with associated abstract variables and parameters inevitably hinders readers' easy understanding of the models. However, the mathematical equations describing the kinetics of biochemical reactions can be exactly mapped to the dynamics of voltages and currents in simple electronic circuits wherein voltages represent molecular concentrations and currents represent molecular fluxes. For example, we theoretically derive and experimentally verify accurate circuit models for Michaelis-Menten kinetics. Then, we show that such circuit models can be scaled via simple wiring among circuit motifs to represent more and arbitrarily complex reactions. Hence, we can directly map reaction networks to equivalent circuit schematics in a rapid, quantitatively accurate, and intuitive fashion without needing mathematical equations. We verify experimentally that these circuit models are quantitatively accurate. Examples include 1) different mechanisms of competitive, noncompetitive, uncompetitive, and mixed enzyme inhibition, important for understanding pharmacokinetics; 2) product-feedback inhibition, common in biochemistry; 3) reversible reactions; 4) multi-substrate enzymatic reactions, both important in many metabolic pathways; and 5) translation and transcription dynamics in a cell-free system, which brings insight into the functioning of all gene-protein networks. We envision that circuit modeling and simulation could become a powerful scientific communication language and tool for quantitative studies of kinetics in biology and related fields.

Movable type printing method to synthesize high-entropy single-atom catalysts.

The controllable anchoring of multiple isolated metal atoms into a single support exhibits scientific and technological opportunities, while the synthesis of catalysts with multiple single metal atoms remains a challenge and has been rarely reported. Herein, we present a general route for anchoring up to eleven metals as highly dispersed single-atom centers on porous nitride-doped carbon supports with the developed movable type printing method, and label them as high-entropy single-atom catalysts. Various high-entropy single-atom catalysts with tunable multicomponent are successfully synthesized with the same method by adjusting only the printing templates and carbonization parameters. To prove utility, quinary high-entropy single-atom catalysts (FeCoNiCuMn) is investigated as oxygen reduction reaction catalyst with much more positive activity and durability than commercial Pt/C catalyst. This work broadens the family of single-atom catalysts and opens a way to investigate highly efficient single-atom catalysts with multiple compositions.

Bee Venom Induces Acute Inflammation through a H2O2-Mediated System That Utilizes Superoxide Dismutase.

Venoms from venomous arthropods, including bees, typically induce an immediate local inflammatory response; however, how venoms acutely elicit inflammatory response and which components induce an inflammatory response remain unknown. Moreover, the presence of superoxide dismutase (SOD3) in venom and its functional link to the acute inflammatory response has not been determined to date. Here, we confirmed that SOD3 in bee venom (bvSOD3) acts as an inducer of H2O2 production to promote acute inflammatory responses. In mouse models, exogenous bvSOD3 rapidly induced H2O2 overproduction through superoxides that are endogenously produced by melittin and phospholipase A2, which then upregulated caspase-1 activation and proinflammatory molecule secretion and promoted an acute inflammatory response. We also showed that the relatively severe noxious effect of bvSOD3 elevated a type 2 immune response and bvSOD3 immunization protected against venom-induced inflammation. Our findings provide a novel view of the mechanism underlying bee venom-induced acute inflammation and offer a new approach to therapeutic treatments for bee envenoming and bee venom preparations for venom therapy/immunotherapy.

Cytomorphic Electronic Systems: A review and perspective.

Boltzmann-exponential thermodynamic laws govern noisy molecular flux in chemical reactions as well as noisy subthreshold electron current flux in transistors. These common mathematical laws enable one to map and simulate arbitrary stochastic biochemical reaction networks in highly efficient cytomorphic systems built on subthreshold analog circuits. Such simulations can accurately model noisy, nonlinear, asynchronous, stiff, and non-modular feedback dynamics in interconnected networks in the physical circuits, automatically. The scaling in simulation time for stochastic networks with the number of reactions or molecules is constant in cytomorphic systems. In contrast, it grows rapidly in digital systems, which are not parallelizable. Therefore, cytomorphic systems enable large-scale supercomputing systems-biology simulations of arbitrary and highly computationally intensive biochemical reaction networks that can nevertheless be compiled to them via digitally programmable parameters and connectivity. We outline how cytomorphic systems can be utilized for rapid drug-cocktail formulation and discovery in future pandemics like COVID-19; can simulate networks important in cancer; and can help automate the design of synthetic biological circuits, e.g. a synthetic biological operational amplifier for robust and precise drug delivery. Thus, just as neuromorphic systems have enabled multiple applications in A.I., cytomorphic systems will enable multiple applications in biology and medicine.

Early Warning Value of ASL-MRI to Estimate Premorbid Variations in Patients With Early Postoperative Cognitive Dysfunctions.

Background: Postoperative cognitive dysfunction (POCD) is a general complication following cardiac and major non-cardiac surgery amongst the elderly, yet its causes and mechanisms are still unknown. The present study aimed to detect whether regional cerebral blood flow (CBF) is altered in the brain before surgery in POCD patients compared with non-POCD (NPOCD) patients, thus, CBF variation may potentially predict the occurrence of early POCD. Methods: Fifty patients scheduled for spinal stenosis surgery were enrolled in the study. All study participants completed a battery of neuropsychological tests (NPTs) by a well-trained neuropsychologist before the surgery and 1 week after the surgery. POCD was defined when the preoperative to postoperative difference of at least two of the NPTs' |Z|-scores with reference to a control group exceeded 1.96. Pulsed arterial spin-labeling (ASL) MRI was scanned at least 1 day before surgery. The ASLtbx toolkit and SPM12 were applied to preprocess and correct the images, which were then normalized to the MNI brain template space to obtain standardized cerebral perfusion images. Results: POCD was identified in 11 out of 50 patients (22%). The CBF of the right superior temporal lobe, right and left middle cingulate gyrus, and the right hippocampus, and parahippocampal gyrus in POCD group was lower than that in NPOCD group (P < 0.001). The CBF of the pars triangularis of inferior frontal gyrus in POCD group was higher than that in NPOCD group (P < 0.001). Conclusions: These preliminary findings suggest that CBF premorbid alterations may happen in cognitively intact elderly patients that develop early POCD. Alterations of preoperative CBF might be a bio-marker for early POCD that can be detected by noninvasive MRI scans.

Lipolytic Activity of a Carboxylesterase from Bumblebee (Bombus ignitus) Venom.

Bee venom is a complex mixture composed of peptides, proteins with enzymatic properties, and low-molecular-weight compounds. Although the carboxylesterase in bee venom has been identified as an allergen, the enzyme's role as a venom component has not been previously elucidated. Here, we show the lipolytic activity of a bumblebee (Bombus ignitus) venom carboxylesterase (BivCaE). The presence of BivCaE in the venom secreted by B. ignitus worker bees was confirmed using an anti-BivCaE antibody raised against a recombinant BivCaE protein produced in baculovirus-infected insect cells. The enzymatic activity of the recombinant BivCaE protein was optimal at 40 °C and pH 8.5. Recombinant BivCaE protein degrades triglycerides and exhibits high lipolytic activity toward long-chain triglycerides, defining the role of BivCaE as a lipolytic agent. Bee venom phospholipase A2 binds to mammalian cells and induces apoptosis, whereas BivCaE does not affect mammalian cells. Collectively, our data demonstrate that BivCaE functions as a lipolytic agent in bee venom, suggesting that BivCaE will be involved in distributing the venom via degradation of blood triglycerides.

Engineering the electronic and strained interface for high activity of PdMcore@Ptmonolayer electrocatalysts for oxygen reduction reaction.

Alloyed nanoparticles with core-shell structures provide a favorable model to modulate interfacial interaction and surface structures at the atomic level, which is important for designing electrocatalysts with high activity and durability. Herein, core-shell structured Pd3M@Pt/C nanoparticles with binary PdM alloy cores (M = Fe, Ni, and Co) and a monolayer Pt shell were successfully synthesized with diverse interfaces. Among these, Pd3Fe@Pt/C exhibited the best oxygen reduction reaction catalytic performance, roughly 5.4 times more than that of the commercial Pt/C catalyst used as reference. The significantly enhanced activity is attributed to the combined effects of strain engineering, interfacial electron transfer, and improved Pt utilization. Density functional theory simulations and extended X-ray absorption fine structure analysis revealed that engineering the alloy core with moderate lattice mismatch and alloy composition (Pd3Fe) optimizes the surface oxygen adsorption energy, thereby rendering excellent electrocatalytic activity. Future researches may use this study as a guide on the construction of highly effective core-shell electrocatalysts for various energy conversions and other applications.

Coupling hollow Fe3O4 nanoparticles with oxygen vacancy on mesoporous carbon as a high-efficiency ORR electrocatalyst for Zn-air battery.

Designing a low-cost, high-efficiency and robust doped-carbon-based oxygen reduction reaction electrocatalyst for large-scale implementations of fuel cells is highly desirable but challenging. In this work, we report a new type of hollow Fe3O4 with oxygen vacancy incorporating on mesoporous carbon prepared by pyrolyzing mesoporous carbon enriched with oxygen-containing functional groups, in combination with ferric acetylacetonate. The catalysts possess high specific surface area with predominantly mesoporous architecture and ultrahigh nitrogen content (up to 7.47 wt%). Benefiting from the integration of abundant active nitrogen and Fe-Nx species, and synergistic effect between Fe3O4 nanoparticles cooperated with oxygen vacancy and N-doped carbon, the half-wave potential of the preparing hybrid catalyst is 30 mV more positive than that of the commercial Pt/C catalyst in alkaline medium, and exhibits a high selectivity (4 e- process), and outstanding long-term stability. More importantly, the C-FePPDA-900 catalyst displays a high power density (106 mW cm-2) and specific capacity of 724 mAh gzn-1 when it is used as an air cathode catalyst in a specifically assembling Zn-air cell, superior to those of most reported catalysts.

A Novel Bioelectronic Reporter System in Living Cells Tested with a Synthetic Biological Comparator.

As the fields of biotechnology and synthetic biology expand, cheap and sensitive tools are needed to measure increasingly complicated genetic circuits. In order to bypass some drawbacks of optical fluorescent reporting systems, we have designed and created a co-culture microbial fuel cell (MFC) system for electronic reporting. This system leverages the syntrophic growth of Escheriachia. coli (E. coli) and an electrogenic bacterium Shewanella oneidensis MR-1 (S. oneidensis). The fermentative products of E. coli provide a carbon and electron source for S. oneidensis MR-1, which then reports on such activity electrically at the anode of the MFC. To further test the capability of electrical reporting of complicated synthetic circuits, a novel synthetic biological comparator was designed and tested with both fluorescent and electrical reporting systems. The results suggest that the electrical reporting system is a good alternative to commonly used optical fluorescent reporter systems since it is a non-toxic reporting system with a much wider dynamic range.

Complex carbohydrates reduce the frequency of antagonistic interactions among bacteria degrading cellulose and xylan.

Bacterial competition for resources is common in nature but positive interactions among bacteria are also evident. We speculate that the structural complexity of substrate might play a role in mediating bacterial interactions. We tested the hypothesis that the frequency of antagonistic interactions among lignocellulolytic bacteria is reduced when complex polysaccharide is the main carbon source compared to when a simple sugar such as glucose is available. Results using all possible pairwise interactions among 35 bacteria isolated from salt marsh detritus showed that the frequency of antagonistic interactions was significantly lower on carboxymethyl cellulose (CMC)-xylan medium (7.8%) than on glucose medium (15.5%). The two interaction networks were also different in their structures. Although 75 antagonistic interactions occurred on both media, there were 115 that occurred only on glucose and 20 only on CMC-xylan, indicating that some antagonistic interactions were substrate specific. We also found that the frequency of antagonism differed among phylogenetic groups. Gammaproteobacteria and Bacillus sp. were the most antagonistic and they tended to antagonize Bacteroidetes and Actinobacteria, the most susceptible groups. Results from the study suggest that substrate complexity affects how bacteria interact and that bacterial interactions in a community are dynamic as nutrient conditions change.

From Chlorella to Nestlike Framework Constructed with Doped Carbon Nanotubes: A Biomass-Derived, High-Performance, Bifunctional Oxygen Reduction/Evolution Catalyst.

The development of effective bifunctional catalysts for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is significant for energy conversion systems, such as Li-air batteries, fuel cells, and water splitting technologies. Herein, a Chlorella-derived catalyst with a nestlike framework, composed of bamboolike nanotubes that encapsulate cobalt nanoparticles, has been prepared through a facile pyrolysis process. It achieves perfect bifunctional catalysis both in ORR and OER on a single catalyst. For our optimal catalyst Co/M-Chlorella-900, its ORR half-wave potential is positively shifted by 40 mV compared to that of a commercial Pt/C catalyst, and the overpotential at 10 mA cm-2 for the OER is 23 mV lower than that of a commercial IrO2/C catalyst in an alkaline medium. This superior bifunctional catalytic performance is benefited from the simultaneous increase of pyridinic N sites for ORR and graphitic N sites for OER. In addition, N-doped carbon-encapsulated Co nanoparticles improve both ORR and OER performance by forming new active centers. The unique nestlike carbon nanotube framework not only afforded highly dense ORR and OER active sites but also promoted the electron and mass transfer. Our catalyst also displays notable durability during the ORR and OER, making it promising for use in ORR/OER-related energy conversion systems.

Well-Defined ZIF-Derived Fe-N Codoped Carbon Nanoframes as Efficient Oxygen Reduction Catalysts.

A series of ZIF-derived Fe-N codoped carbon materials with a well-defined morphology, high surface area, tunable sizes and porous nanoframe structure was successfully prepared by synthesizing Fe-doped ZIF-8 through the assembly of Zn2+ ions with 2-methylimidazole in the presence of iron(III) acetylacetonate, followed by pyrolysis at a high temperature and in an Ar atmosphere. The prepared optimum catalyst materials exhibited excellent activity for the oxygen reduction reaction (ORR) and outstanding durability in both acidic and alkaline solutions. We found that Fe doping during the ZIF-8 synthesis stage was crucial to achieve the materials' well-defined morphology, tunable size, good particle dispersion, and high performance. XPS revealed that Fe doping greatly enhanced the fractions of graphitic-N and pyridinic-N and decreased the fraction of oxidized-N. We suggest that the porosity and high surface area of the nanoframe structure originated from the metal-organic frameworks, the high dispersion of Fe in the nanoframe, and the enhanced proportions of active N species, all of which were responsible for the materials' significantly enhanced ORR performance.