Environment random interaction of rime optimization with Nelder-Mead simplex for parameter estimation of photovoltaic models.

As countries attach importance to environmental protection, clean energy has become a hot topic. Among them, solar energy, as one of the efficient and easily accessible clean energy sources, has received widespread attention. An essential component in converting solar energy into electricity are solar cells. However, a major optimization difficulty remains in precisely and effectively calculating the parameters of photovoltaic (PV) models. In this regard, this study introduces an improved rime optimization algorithm (RIME), namely ERINMRIME, which integrates the Nelder-Mead simplex (NMs) with the environment random interaction (ERI) strategy. In the later phases of ERINMRIME, the ERI strategy serves as a complementary mechanism for augmenting the solution space exploration ability of the agent. By facilitating external interactions, this method improves the algorithm's efficacy in conducting a global search by keeping it from becoming stuck in local optima. Moreover, by incorporating NMs, ERINMRIME enhances its ability to do local searches, leading to improved space exploration. To evaluate ERINMRIME's optimization performance on PV models, this study conducted experiments on four different models: the single diode model (SDM), the double diode model (DDM), the three-diode model (TDM), and the photovoltaic (PV) module model. The experimental results show that ERINMRIME reduces root mean square error for SDM, DDM, TDM, and PV module models by 46.23%, 59.32%, 61.49%, and 23.95%, respectively, compared with the original RIME. Furthermore, this study compared ERINMRIME with nine improved classical algorithms. The results show that ERINMRIME is a remarkable competitor. Ultimately, this study evaluated the performance of ERINMRIME across three distinct commercial PV models, while considering varying irradiation and temperature conditions. The performance of ERINMRIME is superior to existing similar algorithms in different irradiation and temperature conditions. Therefore, ERINMRIME is an algorithm with great potential in identifying and recognizing unknown parameters of PV models.

Wood waste-derived dual-mode materials paving the way for year-round energy saving in buildings.

In the face of the challenges posed by global warming, traditional methods of building heating and cooling contribute significantly to electricity and coal consumption, thereby emitting considerable amounts of greenhouse gases. Here, a dual-mode thermal management structural material is created by processing sustainable cellulose and lignin derived from wood waste into gels, followed by lamination. The cellulose surface of the material exhibits the ability to scatter solar radiation backward while emitting strongly in the mid-infrared wavelengths, whereas the lignin surface absorbs visible and near-infrared light, primarily releasing energy through non-radiative transitions. Consequently, the material can achieve sub-ambient radiative cooling of 6 °C and solar heating of 27.5 °C during the daytime by simply flipping its orientation. This pioneering material showcases the potential to significantly reduce cooling energy consumption by an average of 18% and heating energy consumption by 42%. Moreover, the integration of a thermal-electric generator within the dual-layer structure optimally utilizes the temperature differential between the two layers, converting it into electrical power. Notably, the dual-mode thermal management structural material exhibits impressive mechanical strength, boasting a flexural strength of 102 MPa, surpassing that of natural wood by over 4.8 times. With its dual-mode functionality and embedded thermal-electric generator, this material represents a crucial step towards achieving both thermal comfort and energy autonomy in sustainable building practices, thereby contributing to a more environmentally friendly and efficient future.

Degree of methyl esterification: A key factor for the encapsulation of icaritin with pectin.

Pectin is a promising nano-carrier. The degree of methyl esterification (DM) influences the physiochemical properties of pectin. However, the effect of DM on the encapsulation capacity of pectin remains unclear. In this work, low methyl-esterified pectin (LMP) and high methyl-esterified pectin (HMP) were prepared. The molecular weight, rheological properties of these pectins with various DM levels were determined. Then icaritin/pectin micelles (IPMs) were prepared using HMP and LMP. Notably, higher loading capacities (18.75-20.12 %) were observed in HMP-IPMs compared to LMP-IPMs (15.72-16.64 %). Furthermore, LMP-IPMs demonstrated a DM-dependent reduction in particle sizes, ranging from 449 to 527 nm. In contrast, the particle sizes of HMP-IPMs varied between 342 and 566 nm, with smaller particle sizes observed in HMP-IPMs at higher DM levels. A significant positive correlation was found between DM and the formation of IPMs, including encapsulation efficiency, loading capacity, Zeta potential, and polydispersity index. Alkali de-esterification showed a weak impact on the pectin structure. Hydroxyl groups like 7-OH and 5-OH of icaritin might be involved in the formation of IPMs. The hydrogen-bond interactions between pectin and icaritin could be enhanced as DM increased.

Deep Fusion of Multi-Template Using Spatio-Temporal Weighted Multi-Hypergraph Convolutional Networks for Brain Disease Analysis.

Conventional functional connectivity network (FCN) based on resting-state fMRI (rs-fMRI) can only reflect the relationship between pairwise brain regions. Thus, the hyper-connectivity network (HCN) has been widely used to reveal high-order interactions among multiple brain regions. However, existing HCN models are essentially spatial HCN, which reflect the spatial relevance of multiple brain regions, but ignore the temporal correlation among multiple time points. Furthermore, the majority of HCN construction and learning frameworks are limited to using a single template, while the multi-template carries richer information. To address these issues, we first employ multiple templates to parcellate the rs-fMRI into different brain regions. Then, based on the multi-template data, we propose a spatio-temporal weighted HCN (STW-HCN) to capture more comprehensive high-order temporal and spatial properties of brain activity. Next, a novel deep fusion model of multi-template called spatio-temporal weighted multi-hypergraph convolutional network (STW-MHGCN) is proposed to fuse the STW-HCN of multiple templates, which extracts the deep interrelation information between different templates. Finally, we evaluate our method on the ADNI-2 and ABIDE-I datasets for mild cognitive impairment (MCI) and autism spectrum disorder (ASD) analysis. Experimental results demonstrate that the proposed method is superior to the state-of-the-art approaches in MCI and ASD classification, and the abnormal spatio-temporal hyper-edges discovered by our method have significant significance for the brain abnormalities analysis of MCI and ASD.

Using Machine Learning to Identify Risk Factors and Establishing a Clinical Prediction Model to Predict Atherosclerosis Complications in Idiopathic Membranous Nephropathy.

BACKGROUND: Clinically, it has been observed that patients with idiopathic membranous nephropathy (IMN) have a higher probability of coronary heart disease. We aim to investigate the risk factors associated with coronary heart disease in IMN patients using a mechanomics approach and establish a clinical diagnosis model. METHODS: We collected sixty-nine clinical data points from patients undergoing phospholipase A2 receptor (anti-PLA2R) tests at the Affiliated Hospital of Qingdao University between July 9, 2019 and March 15, 2021. We excluded patients with cancer, hepatitis B, recent injuries or surgeries, and those under 18. Finally, 162 patients were considered for our study, which included 73 patients with coronary heart disease. The patients were split into test and validation groups at a 7:3 ratio. We utilized the Mann-Whitney U test for initial factor screening and the least absolute shrinkage and selection operator (LASSO) regression for further index screening. Eventually, the effectiveness of the clinical model was evaluated through visual statistical methods. RESULTS: Age, lymphocyte count, the sum of high-density lipoprotein (HDL) and low-density lipoprotein (LDL), serum creatinine, and antithrombin III were risk factors for coronary heart disease in patients with idiopathic membranous nephropathy in a multivariate regression (p < 0.1). In the training group, 14 clinical features were finally screened by the LASSO regression, and the area under the curve (AUC) of the training group was 0.90 (95% CI 0.877-0.959), accuracy (ACC) was 0.85, sensitivity was 0.76, specificity was 0.91, and precision was 0.85. F1 scored 0.80. In the verification group, AUC was 0.84 (0.743-0.927), ACC was 0.80, sensitivity was 0.67, specificity was 0.87, precision was 0.75, and F1 scored 0.71. We then visualized them using a nomogram based on multivariate regression. The C index and clinical decision curve evaluated them. The C index was 83.8%, and the clinical decision curve was also excellent. CONCLUSIONS: We've established an effective clinical prediction model for patients with IMN who also have coronary heart disease. This model holds significant potential for enhancing clinical decision-making.

Personal Microenvironment Management by Smart Textiles with Negative Oxygen Ions Releasing and Radiative Cooling Performance.

In recent years, significant strides have been made in the development of smart clothing, which combines traditional apparel with advanced technology. As our climate and environment undergo continuous changes, it has become critically important to invent and refine sophisticated textiles that enhance thermal comfort and human health. In this study, we present a "wearable forest-like textile". This textile is based on helical lignocellulose-tourmaline composite fibers, boasting mechanical strength that outperforms that of cellulose-based and natural macrofibers. This wearable microenvironment does more than generate approximately 18625 ions/cm3 of negative oxygen ions; it also effectively purifies particulate matter. Furthermore, our experiments demonstrate that the negative oxygen ion environment can slow fruit decay by neutralizing free radicals, suggesting promising implications for aging retardation. In addition, this wearable microenvironment reflects solar irradiation and selectively transmits human body thermal radiation, enabling effective radiative cooling of approximately 8.2 °C compared with conventional textiles. This sustainable and efficient wearable microenvironment provides a compelling textile choice that can enhance personal heat management and human health.

Interaction between ultrasound-modified pectin and icaritin.

Pectin can improve the bioaccessibility of icaritin as a nanocarrier, and ultrasound can modify the pectin structure. However, the interaction between ultrasound-modified pectin (UMP) and icaritin remains unclearly. In this work, the effects of UMP on the physiochemical properties of icaritin/pectin micelles (IPMs) were investigated. The IPMs prepared with UMP (UMP-IPMs) showed lower encapsulation efficiencies and loading capacities, comparing with native IPMs. UMP-IPMs had smaller particle sizes (325-399 nm) than native IPMs (551 nm). The Mw, viscosity, G' and G" of pectin were determined. NMR spectra indicated that the repeating unit in pectins remained consistently before and after ultrasound treatment, and 7-OH of icaritin was involved in hydrogen bond formation with pectin. The larger chemical shift movement of 6-H and 7-OH for U3-IPMs than P0-IPMs suggested that stronger hydrogen bond interaction between icaritin and pectin. UMP-IPMs exhibited stronger anti-proliferation activities against HepG2 cells than native IPMs.

Dual-Network Structured Nanofibrous Membranes with Superelevated Interception Probability for Extrafine Particles.

Airborne particulate matter (PM) pollution has caused a public health threat, including nanoscale particles, especially with emerging infectious diseases and indoor and vehicular environmental pollution. However, most existing indoor air filtration units are expensive, energy-intensive, and bulky, and there is an unavoidable trade-off between low-efficiency PM0.3/pathogen interception, PM removal, and air resistance. Herein, we designed and synthesized a two-dimensional continuous cellulose-sheath/net with a unique dual-network corrugated architecture to manufacture high-efficiency air filters and even N95 particulate face mask. Combined with its sheath/net structured pores (size 100-200 nm) consisting of a cellulose framework (1-100 nm diameter), the cellulose sheath/net filter offers high-efficiency air filtration (>99.5338%, Extrafine particles; >99.9999%, PM2.5), low-pressure drops, and a robustness quality factor of >0.14 Pa-1, utilizing their ultralight weight of 30 mg/m2 and physical adhesion and sieving behaviors. Simultaneously, masks prepared with cellulose-sheath/net filters are more likely to capture and block smaller particles than the N95 standard. The synthesis of such materials with their nanoscale features and designed macrostructures may suggest new design criteria for a novel generation of high-efficiency air filter media for different applications such as personal protection products and industrial dust removal.

The structure characteristics, biosynthesis and health benefits of naturally occurring rare flavonoids.

Rare flavonoids, a special subclass of naturally occurring flavonoids with diverse structures including pterocarpans, aurones, neoflavonoids, homoisoflavones, diphenylpropanes, rotenoids and 2-phenylethyl-chromones. They are mainly found in legumes with numerous health benefits. Rare flavonoids are regarded as minor flavonoids due to their very limited abundance in nature. This review gives an overview of the natural occurrences of rare flavonoids from previous literatures. Recent findings on the biosynthesis of rare flavonoids have been updated by describing their structural characteristics and classifications. Recent findings on the health benefits of rare flavonoids have also been compiled and discussed. Natural rare flavonoids with various characteristics from different subclasses from plant-based food sources are stated. They show a wide range of health benefits, including antibacterial, anticancer, anti-osteoporosis and antiviral activities. Studies reviewed suggest that rare flavonoids possessing different skeletons demonstrate different characteristic bioactivities by discussing their mechanism of actions and structure-activity relationships. Besides, recent advances on the biosynthesis of rare flavonoids, such as pterocarpans, rotenoids and aurones are well-known, while the biosynthesis of other subclasses remain unknown. The perspectives and further applications of rare flavonoids using metabolic engineering strategies also be expected.

The bioactivity of prenylated stilbenoids and their structure-activity relationship.

Dietary prenylated stilbenoids present in many food resources, and have good bioactivities. However, their structure-activity relationships are rarely reported. In this work, eighteen C- and O-prenylated stilbenoids were chemically semisynthesized using one-step approach. They all could inhibit sugar digestive enzymes, including α-glucosidase and α-amylase. 4-Geranyl piceatannol from jackfruit showed the strongest activity by suppressing dipeptidyl peptidase-IV (DPP-IV) activity. The enzyme inhibition kinetics were measured and the inhibition mechanism was revealed. Evaluation of antioxidant activity highlighted that the introduction of prenyl with increasing prenyl chain length can significantly increase the antioxidant activity of stilbenoids. Our results suggested that prenylated stilbenoids could be used as functional food additives to decrease postprandial blood sugar levels by inhibiting sugar digestive enzymes and DPP-IV. Prenylated stilbenoids present remarkable DPP-IV inhibitory activity, providing more useful information for the prevention of type 2 diabetes.

Bioinspired Construction of Micronano Lignocellulose into an Impact Resistance "Wooden Armor" With Bouligand Structure.

The demand for advanced safeguards has increased with a rise in terrorism and international conflicts. Traditional impact-resistant glass and ceramics have relatively high performance but have several drawbacks as well, such as inflexibility, heaviness, and high processing energy consumption. Herein, we propose sustainable lignocellulosic duplicates: the Pirarucu scale-inspired structures that can serve as "wood armor" with impressive damage tolerance. By accurately assembling a rigid laminated lignocellulose, with a soft shear-thickened fluid interlayer, into a Bouligand-like structure, the artificial wooden armor exhibits a 10-fold increase in impact resistance. This observation is similar to that of typical engineering materials (e.g., ceramics, glass, and alloys). However, our proposed material structure has the capability of blocking the enormous impact of a bullet while notably having approximately half the density of typical engineering materials. The high durability and damage resistance of wooden armor effectively prevents catastrophic damage when it is impacted upon. The design strategy presents a method for lightweight, high-performance, and sustainable bioinspired materials for special security applications.

Antifungal activity of volatile compounds generated by endophytic fungi Sarocladium brachiariae HND5 against Fusarium oxysporum f. sp. cubense.

The soil-born filamentous fungal pathogen Fusarium oxysporum f. sp. cubense (FOC), which causes vascular wilt disease in banana plants, is one of the most economically important Fusarium species. Biocontrol using endophytic microorganisms is among the most effective methods for controlling banana Fusarium wilt. In this study, volatile organic compounds (VOCs) showed strong antifungal activity against FOC. Seventeen compounds were identified from the VOCs produced by endophytic fungi Sarocladium brachiariae HND5, and three (2-methoxy-4-vinylphenol, 3,4-dimethoxystyrol and caryophyllene) showed antifungal activity against FOC with 50% effective concentrations of 36, 60 and 2900 µL/L headspace, respectively. Transmission electron microscopy (TEM) and double fluorescence staining revealed that 2-methoxy-4-vinylphenol and 3,4-dimethoxystyrol damaged the plasma membranes, resulting in cell death. 3,4-dimethoxystyrol also could induce expression of chitin synthases genes and altered the cell walls of FOC hyphae. Dichloro-dihydro-fluorescein diacetate staining indicated the caryophyllene induced accumulation of reactive oxygen species (ROS) in FOC hyphae. FOC secondary metabolism also responded to active VOC challenge by producing less fusaric acid and expressions of genes related to fusaric acid production were interrupted at sublethal concentrations. These findings indicate the potential of S. brachiariae HND5 as a biocontrol agent against FOC and the antifungal VOCs as fumigants.

Colorimetric immunosensor based on glassy carbon microspheres test strips for the detection of prostate-specific antigen.

Micro-sized glassy carbon microspheres (GCMs, typically 3 µm in diameter) instead of nano-sized gold nanoparticles (AuNPs, typically 20 nm in diameter) were for the first time used as signal markers for the quantitative detection of antigen such as prostate-specific antigen (PSA). After being treated with concentrated HNO3, GCMs bear carboxyl groups at their surfaces, which enables antibodies to be conjugated with GCMs to yield new type of micro-sized material-based colorimetric probes used for immunochromatographic test strips (ICTSs). The captured black GCMs (with strong and wide-band light absorption) on the T-line of ICTS were used both for qualitative and quantitative determination of PSA. In the case of quantitative determination, a lab-assembled optical strip reader system was used to measure the reflected LED light intensity at 550 nm. The sensing performances of the developed GCM-based ICTSs, such as sensitivity, selectivity, reproducibility, stability, and applicability, were investigated in detail. The developed GCM-based ICTSs can have much higher (3 times) detection sensitivity than AuNP-based ICTSs, showing promising applications in sensitive immunoassay.

Autophagy activation promotes the effect of iPSCs-derived NSCs on bladder function restoration after spinal cord injury.

The role of autophagy in the transplantation of induced pluripotent stem cells (iPSCs)-derived neural stem cells (NSCs) to treat spinal cord injury (SCI) and neurogenic bladder was investigated in this study. NSCs derived from human iPSCs were identified by and immunofluorescence assay. To clarify the role of autophagy, iPSCs were treated with either an autophagy inducer (rapamycin), or an autophagy inhibitor (chloroquine). Cell Counting kit-8 (CCK-8), western blot and flow cytometry were used to detect the effect of autophagy on the viability and differentiation of iPSCs. Sixty Wistar rats were selected to establish the SCI model and treated with iPSCs-derived NSCs transplantation. The effect of autophagy on the bladder function of rats with different treatments was evaluated by Basso, Beattie, and Bresnahan (BBB) score, bladder function score, bladder weight measurement, Hematoxylin & Eosin (H&E) staining, and Masson staining. The results of in vitro experiment showed that rapamycin enhanced the cell activity of iPSCs, increased the number of nestin positive cells, up-regulated Beclin-1 and LC3BI/II expressions, and down-regulated p62 expression. And the results of in vivo experiment showed that rapamycin improved exercise ability and bladder function, partially restored bladder weight, and significantly reduced bladder tissue damage in SCI rats. However, chloroquine showed the opposite results. The differentiation of iPSCs into NSCs could be promoted by induced autophagy, while neurogenic bladder of SCI was restored by autophagy activation.

Experimental measurement-device-independent quantum key distribution with the double-scanning method.

The measurement-device-independent quantum key distribution (MDI-QKD) can be immune to all detector side-channel attacks. Moreover, it can be easily implemented combining with the matured decoy-state methods under current technology. It, thus, seems a very promising candidate in practical implementation of quantum communications. However, it suffers from a severe finite-data-size effect in most existing MDI-QKD protocols, resulting in relatively low key rates. Recently, Jiang et al. [Phys. Rev. A103, 012402 (2021).PLRAAN1050-294710.1103/PhysRevA.103.012402] proposed a double-scanning method to drastically increase the key rate of MDI-QKD. Based on Jiang et al.'s theoretical work, here we for the first time, to the best of our knowledge, implement the double-scanning method into MDI-QKD and carry out corresponding experimental demonstration. With a moderate number of pulses of 1010, we can achieve 150 km secure transmission distance, which is impossible with all former methods. Therefore, our present work paves the way toward practical implementation of MDI-QKD.

Genomic Characteristics and Comparative Genomics Analysis of Two Chinese Corynespora cassiicola Strains Causing Corynespora Leaf Fall (CLF) Disease.

Rubber tree Corynespora leaf fall (CLF) disease, caused by the fungus Corynespora cassiicola, is one of the most damaging diseases in rubber tree plantations in Asia and Africa, and this disease also threatens rubber nurseries and young rubber plantations in China. C. cassiicola isolates display high genetic diversity, and virulence profiles vary significantly depending on cultivar. Although one phytotoxin (cassicolin) has been identified, it cannot fully explain the diversity in pathogenicity between C. cassiicola species, and some virulent C. cassiicola strains do not contain the cassiicolin gene. In the present study, we report high-quality gapless genome sequences, obtained using short-read sequencing and single-molecule long-read sequencing, of two Chinese C. cassiicola virulent strains. Comparative genomics of gene families in these two stains and a virulent CPP strain from the Philippines showed that all three strains experienced different selective pressures, and metabolism-related gene families vary between the strains. Secreted protein analysis indicated that the quantities of secreted cell wall-degrading enzymes were correlated with pathogenesis, and the most aggressive CCP strain (cassiicolin toxin type 1) encoded 27.34% and 39.74% more secreted carbohydrate-active enzymes (CAZymes) than Chinese strains YN49 and CC01, respectively, both of which can only infect rubber tree saplings. The results of antiSMASH analysis showed that all three strains encode ~60 secondary metabolite biosynthesis gene clusters (SM BGCs). Phylogenomic and domain structure analyses of core synthesis genes, together with synteny analysis of polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) gene clusters, revealed diversity in the distribution of SM BGCs between strains, as well as SM polymorphisms, which may play an important role in pathogenic progress. The results expand our understanding of the C. cassiicola genome. Further comparative genomic analysis indicates that secreted CAZymes and SMs may influence pathogenicity in rubber tree plantations. The findings facilitate future exploration of the molecular pathogenic mechanism of C. cassiicola.

Cellulose-Based Hybrid Structural Material for Radiative Cooling.

Structural materials with excellent mechanical properties are vitally important for architectural application. However, the traditional structural materials with complex manufacturing processes cannot effectively regulate heat flow, causing a large impact on global energy consumption. Here, we processed a high-performance and inexpensive cooling structural material by bottom-up assembling delignified biomass cellulose fiber and inorganic microspheres into a 3D network bulk followed by a hot-pressing process; we constructed a cooling lignocellulosic bulk that exhibits strong mechanical strength more than eight times that of the pure wood fiber bulk and greater specific strength than the majority of structural materials. The cellulose acts as a photonic solar reflector and thermal emitter, enabling a material that can accomplish 24-h continuous cooling with an average dT of 6 and 8 °C during day and night, respectively. Combined with excellent fire-retardant and outdoor antibacterial performance, it will pave the way for the design of high-performance cooling structural materials.

Effect of Iron Ion on Corrosion Behavior of Inconel 625 in High-Temperature Water.

The corrosion behavior of an ultralow iron nickel-based alloy Inconel 625 under high-temperature water has been evaluated. The results show that surface oxidation and pitting were the principal corrosion mechanisms of Inconel 625 during the initial immersion period. The surface layer of the oxide film is first Ni-enriched and then Fe-enriched as immersion time increases. The iron ions dissolved from the autoclave could lead to the formation of NiFe2O4 and have a great influence on the oxidation behavior of Inconel 625. The oxides nucleated by solid-state reactions with selective dissolution of Fe and Ni and then grew up through precipitation of cations from solution.

Description of COVID-19 cases along with the measures taken on prevention and control in Zhejiang, China.

Under the outbreak of COVID-19, it was urgent to analyze the cases from clinical features and epidemiological factors, as well as understand the effectiveness of measures taken on disease prevent and control. A retrospective study was applied for descriptive analysis of clinical features and epidemiological factors of confirmed cases in four cities of Zhejiang. The Onset-admission interval was calculated and plotted as well. The provincial measures regarding the response of COVID-19 were summed up and sorted out. The distribution and sex and age were under normality distribution, and the age of 20 to 80 were all in risk of developing the disease. Clinical features of fever and cough were found mostly happen on patients. More than half of the patients had image changed on chest from reported data. The factor of closely contacted with confirmed cases was the most cause to the disease. The median onset-admission interval was 6 days in Zhejiang province. As of the efficient health system, COVID-19 had been successfully prevented and controlled in Zhejiang. Males and females were all vulnerable to COVID-19. Preventing contact with confirmed cases could largely avoid the disease to happen. The government should take emergent and effective measures to prevent and treatment of the pandemic disease.

Artificial Wooden Nacre: A High Specific Strength Engineering Material.

Nacre, an organic-inorganic composite biomaterial that forms an ordered multilayer microstructure after years of slow biomineralization, is known as the strongest and toughest material within the mollusc family. Its unique structure provides inspiration for robust artificial engineering materials. Lignocellulose is ultralightweight, abundant, and possesses a high mechanical performance and has been used for ages as a significant renewable raw material in wooden engineering composites. However, the inherent lack of mechanical properties of current wooden composites associated with the fragile microstructure has limited their applications in advanced engineering materials. Here, we develop a large-size ultralightweight artificial "wood nacre" with an ordered layer structure through a fast and scalable "mechanical/chemical mineralization and assembly" approach. The millimeter-thick artificial wooden nacre mimics the stratified construction of natural nacre, resulting in a bulk hybrid material that can achieve almost the same strength as natural nacre while consisting of only one-sixth of the total inorganic content of natural nacre. The specific strength and toughness of the artificial wooden nacre is even superior to engineering alloy materials (such as Cu and Fe). This approach represents an efficient strategy for the mass production of lightweight sustainable structural materials with high strength and toughness.