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Abstract The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

Introduction There needs to be more up-to-date evidence on the prevalence of e-cigarette use among Chinese adults. This study aims to investigate the prevalence and associated factors of e-cigarette use among adults aged 18–44 years in China. Methods Cross-sectional design and convenience sampling were used. The data for this study were obtained from an online survey conducted in mainland China from April to May 2023. The target population was adults aged 18–44 years. Descriptive analysis was employed to report the prevalence of e-cigarette use, while adjusted multivariable logistic regression was performed to examine the association between e-cigarette use and related factors. Results A total of 4256 participants were included in this study; 12.9% were current e-cigarette users, 5.9% were frequent users, and 7.0% were occasional users. The descriptive analysis results indicated that males and cigarette users had a higher prevalence of e-cigarette use. Multivariable analysis showed that e-cigarette use was significantly associated with female gender (AOR=0.76, 95% CI: 0.60–0.96), those aged 25–34 years with monthly income 6000–8999 CNY (AOR=2.01; 95% CI: 1.18–3.41), those aged 25–34 years with monthly income ≥9000 CNY (AOR=2.20; 95% CI: 1.26–3.82), college or undergraduate degree (AOR=1.91; 95% CI: 1.22–3.00), urban residence (AOR=1.72; 95% CI: 1.34–2.20), being a current smoker (AOR=3.32; 95% CI: 2.64–4.16), perception of harm (AOR=0.66; 95% CI: 0.60–0.73), and perception of benefit (AOR=2.31; 95% CI: 2.04–2.61). Conclusions The prevalence of current e-cigarette use among adults in China was 12.9% within our sample. In addition to sociodemographic factors, individuals with a higher perception of the harm associated with e-cigarettes were less likely to engage in e-cigarette consumption. Conversely, individuals who perceive the ‘benefits’ of e-cigarettes more favorably use them. Targeted interventions, such as health education, are recommended to help adults develop a correct understanding of e-cigarettes and lower the prevalence of e-cigarette use.

Abstract The advancements in tactile sensor technology have found wide-ranging applications in robotic fields, resulting in remarkable achievements in object manipulation and overall human-machine interactions. However, the widespread availability of high-resolution tactile skins remains limited, due to the challenges of incorporating large-sized, robust sensing units and increased wiring complexity. One approach to achieve high-resolution and robust tactile skins is to integrate a limited number of sensor units (taxels) into a flexible surface material and leverage signal processing techniques to achieve super-resolution sensing. Here, we present a magnetic skin consisting of multi-direction magnetized flexible films and a contactless Hall sensor array. The key features of the proposed sensor include the specific magnetization arrangement, K-Nearest Neighbors (KNN) clustering algorithm and convolutional neural network (CNN) model for signal processing. Using only an array of 4*4 taxels, our magnetic skin is capable of achieving super-resolution perception over an area of 48400 mm2, with an average localization error of 1.2 mm. By employing neural network algorithms to decouple the multi-dimensional signals, the skin can achieve multi-point and multi-scale perception. We also demonstrate the promising potentials of the proposed sensor in intelligent control, by simultaneously controlling two vehicles with trajectory mapping on the magnetic skin.

Abstract The rapid development of ocean exploration and underwater robot technology has put forward new requirements for underwater sensing methods, which can be used for hydrodynamic characteristics perception, underwater target tracking, and even underwater cluster communication. Here, inspired by the specialized undulated surface structure of the seal whisker and its ability to suppress vortex‐induced vibration, a multidirectional hydrodynamic sensor based on biomimetic whisker array structure and magnetic 3D self‐decoupling theory is introduced. The magnetic‐based sensing method enables wireless connectivity between the magnetic functional structures and electronics, simplifying device design and endowing complete watertightness. The 3D self‐decoupling capability enables the sensor, like a seal or other organisms, to perceive arbitrary whisker motions caused by the action of water flow without complex calibration and additional sensing units. The whisker sensor is capable of detecting a variety of hydrodynamic information, including the velocity (RMSE

Abstract The Health Action Process Approach (HAPA) is a two-stage (pre-intentional and post-intentional) behavioral change model that distinguishes between motivation and volition in behavior change process. This study aims to develop HAPA-based assessments for smoking cessation among current smokers. The HAPA-based measures were developed and the draft measures included nine constructs, namely, risk perception in smoking-induced cancer, risk perception in smoking-induced systemic disease, positive outcome expectancy, negative outcome expectancy, self-efficacy in quitting smoking, self-efficacy in maintaining, self-efficacy in re-initiating, quitting planning and coping planning in smoking cessation, with a total of 26 items. A cross-sectional survey was conducted in China in 2022. Principal Component Analysis was used for Exploratory Factor Analysis (EFA). Cronbach’s α coefficient was calculated to evaluate the internal consistency. Variables such as severity of smoking addiction were selected to evaluate the correlation between the HAPA scale and these variables. Of the 928 participants, 76.4% (709/928) were male and the median age was 35 years. Five factors were extracted by EFA. The factor loadings of each item were all greater than 0.60, and the cumulative variance contribution rate was 90.15%. The Cronbach’s α coefficient of each HAPA-based subscales was 0.929–0.986. The HAPA-based measurements are comprehensive, reliable and valid in the assessment of smokers’ smoking cessation cognition, which can be used to guide the design and implementation of intervention and the development of theory.

Cancer cell line is commonly used for discovery and development of anti-cancer drugs. It is generally considered that drug response remains constant for a certain cell line due to the identity of genetics thus protein patterns. Here, we demonstrated that cancer cells continued dividing even after reaching confluence, in that the proteomics was changed continuously and dramatically with strong relevance to cell division, cell adhesion and cell metabolism, indicating time-dependent intrinsically reprogramming of cells during expansion. Of note, the inhibition effect of most anti-cancer drugs was strikingly attenuated in culture cells along with cell expansion, with the strongest change at the third day when cells were still expanding. Profiling of an FDA-approved drug library revealed that attenuation of response with cell expansion is common for most drugs, an exception was TAK165 that was a selective inhibitor of mitochondrial respiratory chain complex I. Finally, we screened a panel of natural products and identified four pentacyclic triterpenes as selective inhibitors of cancer cells under prolonged growth. Taken together, our findings underscore that caution should be taken in evaluation of anti-cancer drugs using culture cells, and provide agents selectively targeting overgrowth cancer cells.

The successful exploration of the Mariana Trench, Earth's deepest trench, by soft robots inspired by deep-sea organisms, showcasing the potential of soft robots for extreme deep-sea exploration. However, deep-sea extreme pressure significantly alters the structure and properties of robot materials, affecting their detectability. In this study, to ensure soft robots maintain excellent performance even in such extreme environments, meticulous attention is devoted to these pressure-induced changes before designing them. The results demonstrate that applying pressure (416.67 MPa) can induce the glass transition in silicone rubber (SR) even at room temperature. Unlike the traditional realization mechanism (cooling material to its glass transition temperature (Tg)), the realization mechanism through pressurizing is reported that adjusting the Tg of target material to approach a specific temperature. Furthermore, the different transition mechanisms under the two realizations are also revealed. Based the dynamic analysis of SR under extremely low temperature and high pressure, the glass transition pressure (Pg) is proposed, and the glass transition strategy by jointly regulating temperature and pressure to construct equivalent extreme pressure environment is also investigated. This study, taking SR as the case study, holds significant importance for the future development of extreme pressure-resistant soft robots for extreme environment exploration.

Abstract Lithium (Li) is a prototypical simple metal at ambient conditions, but exhibits remarkable changes in structural and electronic properties under compression. There has been intense debate about the structure of dense Li, and recent experiments offered fresh evidence for yet undetermined crystalline phases near the enigmatic melting minimum region in the pressure-temperature phase diagram of Li. Here, we report on an extensive exploration of the energy landscape of Li using an advanced crystal structure search method combined with a machine-learning approach, which greatly expands the scale of structure search, leading to the prediction of four complex Li crystal structures containing up to 192 atoms in the unit cell that are energetically competitive with known Li structures. These findings provide a viable solution to the observed yet unidentified crystalline phases of Li, and showcase the predictive power of the global structure search method for discovering complex crystal structures in conjunction with accurate machine learning potentials.

In this study, a post-treatment method was carried out to increase the tensile strength of poly ether ketone (PEEK) fibers, with a maximum increase of 69%. The effects of the post-treatment process parameters on the diameter shrinkage ratio, mechanical properties of PEEK fibers, and the aggregated state structure were also quantitatively investigated by optical measurements, uniaxial tensile tests, differential scanning calorimetry, and two-dimensional-wide angle X-ray diffraction. These studies revealed that the enhanced orientation of PEEK fibers with increasing post-treatment temperature and constant tensile force is the major reason for the significant increase in uniaxial tensile strength. The diameter shrinkage ratio can be used as an indicator of the degree of fiber orientation. More critically, this study also presented mathematical models that described the high linearity of the increase in diameter shrinkage ratio and uniaxial tensile strength of fibers with post-treatment temperature and constant tensile force, respectively. That also revealed the equivalence of temperature and constant tensile force in the post-treatment process and obtained the conversion factor. These in-depth understandings provided positive guidance for improving the strength of PEEK fibers and achieving controllable morphology and mechanical properties in PEEK fiber production.

Magnetic actuation has emerged as a prominent method in soft robots due to its charming advantages on diverse magnetization designs, which heavily rely on the microstructures formed by hard magnetic particles (NdFeB) inside the robot. However, the contradiction between the need for multiple orientations of the particles and the issue of particle agglomeration caused by repeated orientation during fabrication has not been effectively resolved. This limitation prevents additive manufacturing of high-performance magnetic soft robots and hinders further diversification of robot magnetization structures. In this study, we proposed a method that utilizes a dynamic magnetic field to re-disperse agglomerated particles. This method is able to effectively disperse the agglomerates uniformly and enhance the re-oriented particle chains in multiple aspects, including compactness, orientation (∼200 %), and maintenance time (>120 min). Furthermore, this method was utilized to improve the magneto-induced deformation (from 7.71° to 13.89°) of the Magneto-Rheological Elastomer (MRE) samples, which were fabricated with repeatedly orientated magnetizations using magnetic field-assisted Stereo-lithography (SLA). Overall, the proposed method lays the groundwork for the structural complexity of magnetic soft robots and holds significant potential for broadening the fabrication methods of magnetic soft robots.

Bovine respiratory disease (BRD) causes morbidity and mortality in cattle. The critical roles of the respiratory microbiota in BRD have been widely studied. The nasopharynx was the most popular sampling niche for BRD pathogen studies. The oral cavity and other niches within the respiratory tract, such as nostrils and lung, are less assessed. In this study, oropharyngeal swabs (OS), nasal swabs (NS), nasopharyngeal swabs (NP), and bronchoalveolar lavage (BAL) were collected from calves located in four countries and analyzed for investigation of the dissimilarities and connections of the respiratory microbiota. The results showed that the microbial diversity, structure, and composition in the upper and lower respiratory tract in beef cattle from China, the USA, Canada, and Italy were significantly different. The microbial taxa for each sampling niche were specific and associated with their local physiology and geography. The signature microbiota for OS, NS, NP, and BAL were identified using the LEfSe algorithm. Although the spatial dissimilarities among the respiratory niches existed, the microbial connections were observed in beef cattle regardless of geography. Notably, the nostril and nasopharynx had more similar microbiomes compared to lung communities. The major bacterial immigration patterns in the bovine respiratory tract were estimated and some of them were associated with geography. In addition, the contribution of oral microbiota to the nasal and lung ecosystems was confirmed. Lastly, microbial interactions were characterized to reveal the correlation between the commercial microbiota and BRD-associated pathogens. In conclusion, shared airway microbiota among niches and geography provides the possibility to investigate the common knowledge for bovine respiratory health and diseases. In spite of the dissimilarities of the respiratory microbiota in cattle, the spatial connections among these sampling niches not only allow us to deeply understand the airway ecosystem but also benefit the research and development of probiotics for BRD.

Given the global pressure of climate change and ecological equilibrium, there is an urgent need to develop effective carbon dioxide (CO2) capture technology. Due to its comprehensiveness and flexibility, Direct Air Capture (DAC) technology has emerged as a vital supplement to traditional emission reduction methods. This study aims to innovate Direct Air Capture (DAC) technology by utilizing the ultrasonic impregnation method to load Tetraethylenepentamine (TEPA) onto alumina (Al2O3) as the adsorbent. Furthermore, high gravity adsorption technology is integrated to significantly enhance the efficiency of DAC. Characterization tests, including BET, FTIR, TG, XRD, and SEM-EDS, confirm the structural stability and high capture capacity of the adsorbent. Additionally, this study demonstrates the rapid and efficient capture of CO2 from the air using TEPA-Al2O3 adsorbent under high gravity conditions for the first time. Under optimal conditions with TEPA loading at 15.06%, a high gravity factor of 2.67, and a gas flow rate of 30 L/min, TEPA-Al2O3 achieves a CO2 adsorption capacity of 48.5 mg/g in RAB, which is an improvement of 15.56 mg/g compared to traditional fixed-bed technology. Moreover, it reaches adsorption saturation faster under high gravity conditions, exhibiting a significantly higher adsorption rate compared to traditional fixed-bed systems. Furthermore, the adsorption process better conforms to the Avrami model. Steam stripping regeneration is utilized to regenerate the adsorbent, demonstrating excellent regeneration performance and stable adsorption capacity, thereby proving its feasibility and economic benefits as a DAC technology.

Background: Tumor necrosis factor (TNF) receptor-associated factor 2 (TRAF2) is an oncogenic regulator of Wnt/β-catenin signaling in colon cancer. Previously we have reported a pentacyclic triterpenoid compound liquidambaric acid (LDA) inhibiting Wnt/β-catenin signaling via targeting TRAF2, however, LDA inhibition of cancer cells was observed only at high doses. It is important to identify small molecules targeting TRAF2 in colon cancer with higher potency . Methods: Microscale thermophoresis (MST) assay was used to screen a panel of pentacyclic triterpenoids. Cellular thermal shift assay (CETSA) was used to confirm target engagment in living cells. Drug affinity responsive target stability (DARTS) coupled with mass spectrometry (MS) was used to identify the potential targets of candidate TRAF2 binder. Wnt signaling inhibition was evaluated by 7TGC reporter assay, TOPFlash assay, reverse transcription and real-time quantitative PCR, as well as zebrafish eyeless assay. Cancer inhibition was assessed by cell viability assay, colony formation assay and xenograft studies. CRISPR/Cas9 knockout HCT116 cells was used to assess the requirement of TRAF2 for liquidambaric lactone (LDL) inhibition of cancer. Results: A LDA analogue LDL selectively targeted TRAF2 with higher binding affinity. Both LDL and LDA targeted the TRAF-C domain of TRAF2 with slightly different binding sites. Of note, LDL showed much stronger inhibition of colon cancer cells than LDA in colony formation assay. LDL inhibition of cancer was also comfirmed in xenograft mice. Depletion of TRAF2 totally blocked LDL inhibition of Wnt signaling, TNF signaling and growth of cancer cells. Conclusions: A natural product LDL is a potent inhibitor of TRAF2 for cancer therapy, and TRAF2 is required for LDL inhibition of cancer.

Tactile sensory organs for three-dimensional (3D) force perception are essential for most living organisms and enable them to perform complex and sophisticated tasks to survive and evolve. Magnetic-based tactile sensors have been developed rapidly in recent years due to the exploitability of 3D force decoupling. Here, a method of magnet splicing is introduced, which can be applied to a magnetic tactile sensor to realize 3D self-decoupling of magnets’ displacements. This method enables the magnets to produce a completely consistent magnetic field distribution as the ideal magnetization model within a certain working range, eliminating the compensation and correction of the 3D magnetic flux density signal. This method carves out a new way for the practical application of 3D decoupling theory, showcasing the great potential in the fields of magnetic sensors and magnetic actuators.

High-gravity wet dust removal technology has attracted much attention because of its potential to cut liquid into smaller liquid droplets and lower energy consumption. However, the complex structure and the high-speed rotation of the rotating packed bed do not allow us to analyze the flow field using conventional methods, and thus the capture mechanism of fine particles in a high-gravity environment is poorly understood. In this study, a two-dimensional computational fluid dynamics model was established to investigate the distribution of the gas–liquid two-phase flow field inside of a rotating packed bed. The characteristics of the flow field, such as the liquid form, gas–liquid contact time, and gas flow path, were investigated, and the droplet size distribution and gas–liquid slip velocity were quantitatively analyzed. The inertial capture efficiency was calculated using the Stokes number, and the dust removal efficiency distribution in the rotating packed bed was compared. The reason for the high collection efficiency of fine particles by the high-gravity wet dust removal technology was explained by numerical simulations. Two new structures were designed to improve the total dust removal efficiency.

Soft robot incarnates its unique advantages in deep-sea exploration, but grapples with high hydrostatic pressure’s unpredictable impact on its mechanical performances. In our previous work, a self-powered soft robot showed excellent work performance in the Mariana Trench at a depth of 11 000 m, yet experienced notable degradation in deforming capability. Here, we propose a magnetic loading method for characterizing elastomer’s mechanical properties under extremely high hydrostatic pressure of up to 120 MPa. This method facilitates remote loading and enables in-situ observation, so that the dimensions and deformation at high hydrostatic pressure are obtained and used for calculations. The results reveal that the Young’s modulus of Polydimethylsiloxane (PDMS) monotonously increases with pressure. It is found that the relative increase in Young’s modulus is determined by its initial value, which is 8% for an initial Young’s modulus of 2200 kPa and 38% for 660 kPa. The relation between initial Young’s modulus and relevant increase can be fitted by an exponential function. The bulk modulus of PDMS is about 1.4 GPa at 20 °C and is barely affected by hydrostatic pressure. The method can quantify alterations in the mechanical properties of elastomers induced by hydrostatic pressure, and provide guidance for the design of soft robots which serve in extreme pressure environment.

BackgroundMost mobile cessation studies have found that such interventions have a higher quitting rate than interventions providing minimal smoking cessation support. However, why such interventions are effective has been almost unstudied by researchers. ObjectiveThis paper describes the principles of the personalized mobile cessation intervention-based WeChat app and used generalized estimated equations to assess why a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage than a nonpersonalized intervention. MethodsThis is a 2-arm, double-blind, randomized controlled trial in five cities in China. The intervention group received a personalized mobile cessation intervention. The control group received a nonpersonalized SMS text message smoking cessation intervention. All information was sent by the WeChat app. The outcomes were the change in protection motivation theory construct scores and the change in transtheoretical model stages. ResultsA total of 722 participants were randomly assigned to the intervention or control group. Compared with those who received the nonpersonalized SMS text message intervention, smokers who received the personalized intervention presented lower intrinsic rewards, extrinsic rewards, and response costs. Intrinsic rewards were determinants of stage change, thus explaining why the intervention group was more likely to promote smokers from the preparation stage to the action stage (odds ratio 2.65, 95% CI 1.41-4.98). ConclusionsThis study identified the psychological determinants at different stages to facilitate smokers moving forward to the next stage of quitting behavior and provides a framework to explore why a smoking cessation intervention is effective. Trial RegistrationChinese Clinical Trial Registry ChiCTR2100041942; https://tinyurl.com/2hhx4m7f

Extracellular vesicle-mediated transfer of microRNAs is a novel mode of cell-to-cell genetic transmission. Extracellular vesicles produced by microbes have been shown to contain significant quantities of physiologically active molecules such as proteins, lipids, and RNA, which could be transported to host cells and play a key role in both inter-kingdom signaling and physiological responses. In this study, we identified sRNAs by sequencing small RNAs (sRNAs) from Lactobacillus plantarum-derived extracellular vesicles (LDEVs) and detected the expression levels of vesicular sRNAs using quantitative reverse transcription-polymerase chain reaction (RT-PCR), which demonstrated the presence of microRNA-sized RNAs (msRNAs) within these vesicles. We chose sRNA71, a highly expressed msRNA, for further investigation, predicted its potential target genes for the human genome, and indicated that it could be translocated into mammalian cells. The biological functions of this sRNA71 were subsequently explored through cellular proteomics, western blot, and luciferase reporter assay. According to the findings, transfection with synthetic sRNA71 mimics substantially reduced Tp53 expression in HEK293T cells and suppressed the gene expression through binding to the 3′ UTR of Tp53 mRNA. In conclusion, it is hypothesized that microbial-derived extracellular vesicles serve as carriers of functional molecules such as sRNAs, which play an essential role in regulating microbial-host communication.

An accurate algorithm for sea ice segmentation is critical for monitoring sea ice parameters of ship navigation in ice-covered seas, as it can automatically extract ice objects and corresponding information to compute essential parameters such as surface ice concentration and ice floe size. In this paper, based on digital images captured by onboard cameras, a novel network called Ice-Deeplab for pixel-wise ice image segmentation is proposed. The Ice-Deeplab network is constructed using the deep convolutional neural network Deeplab and is modified with an attention module and an improved decoding structure. To investigate its reliability, the Ice-Deeplab network is applied to a 320-image dataset, with 80% for training and 20% for validation. The experiments demonstrated that the proposed Ice-Deeplab yields better segmentation results than the original Deeplab model under different validation scenarios, achieving an overall accuracy of 90.5% among the classes sea-ice, ocean, and sky. Moreover, the proposed model was applied to un-labelled test data to demonstrate its generalisation ability for real-time ice segmentation.

Fixing carbon dioxide as a polymer material is an effective and environmentally beneficial approach for reducing the harm of CO2 greenhouse gas. In this paper, carbon dioxide and cyclohexene oxide were used as co-monomers, and a chiral binuclear cobalt complex with a biphenyl linker was employed as the catalyst to successfully prepare a poly(cyclohexenylene carbonate) with high stereoregularity. The influence of catalyst structure, CO2 pressure, and operating temperature on the copolymerization rate and polymer structure were systematically investigated. Optimal catalyst structure and operating conditions were determined, resulting in an excellent poly(cyclohexenylene carbonate) with a stereoregularity as high as 93.5%. Performance testing revealed that the polyester had a molecular weight of approximately 20 kg/mol, a glass transition temperature of 129.7 °C, an onset decomposition temperature of 290 °C, and a tensile strength of 42.8 MPa. These results demonstrate high thermal stability and mechanical strength, indicating the potential for expanding the applications of aliphatic polycarbonate materials.

Summary: β-Catenin is a central component in the Wnt signaling pathway; its degradation has been tightly connected to ubiquitylation, but it is rarely examined by loss-of-function assays. Here we observe that endogenous β-catenin is not stabilized upon ubiquitylation depletion by a ubiquitylation inhibitor, TAK-243. We demonstrate that N-terminal phosphorylated β-catenin is quickly and strongly stabilized by a specific neddylation inhibitor, MLN4924, in all examined cell types, and that β-catenin and TCF4 interaction is strongly enhanced by inhibition of neddylation but not ubiquitylation. We also confirm that the E3 ligase β-TrCP2, but not β-TrCP1, is associated with neddylation and destruction of β-catenin. GSK3β and adenomatous polyposis coli (APC) are not required for β-catenin neddylation but essential for its subsequent degradation. Our findings not only clarify the process of β-catenin modification and degradation in the Wnt signaling pathway but also highlight the importance of reassessing previously identified ubiquitylation substrates.

Surface plasmon microscopy (SPM) provides the capability of measuring surface properties of subnanometer layers within the diffraction limited order. In a typical SPM, small changes correspond to surface plasmons (SPs) absorption profile variations on a reflecting back focal plane (BFP), which can be monitored in real-time. However, the lack of fast and high-accurate identification method on SPs profiles has posed significant challenges on objective-coupled SPM instruments, and also limited their practical applications in fast phenomenon sensing and image batch processing. Here we propose a morphological method to identify the SPs absorption profiles. It can extract the SPs profile information from experimentally recorded BFP images with low quality properly and automatically. Experimental verification and further discussions are included.

A novel pellet 3D printer was first developed, and its structure was constructed out of three main parts. The material used in this device was polycaprolactone (PCL), which was praised for its good characteristics in the biomanufacturing and chemical industries. Three essential parameters that had important effects on the diameter of the printed fibers were systematically studied using a L9(34) orthogonal design table. Using the fused deposition modelling (FDM) method, some products were printed with this machine. Results showed that the stepper motor’s speed had the most significant effect on the diameter of the printed fibers. The optimal parameters were, a stepper motor speed of 1.256 mm3 s−1, a nozzle moving speed of 9.6 mm s−1, and 1.1 mm of height between the nozzle and the platform. Defects like gaps, warping, and poor surface quality were found to be related to different combinations of process parameters. By using the developed pellet 3D printer, the pre-step of making filaments can be avoided, which will bring convenience to FDM 3D printing.

Multiple-phenyl phosphorous compounds are a group of chemical materials that have been used as reactants, pharmaceutical intermediates, extractants, and catalysts in organic synthetic reactions. However, the crystal growth of bulk crystals of multiple-phenyl phosphorous compounds, which may expand their applications in photonics technology, have been largely overlooked. In this article, the crystal growth of tetraphenylphosphonium bromide (TPPB) has been studied in organic solvents and water. The crystal structures and crystallization features are analyzed by X-ray diffraction data. By a slow temperature-lowering method, a single-crystal of TPPB (2H2O) with the size of 27 × 20 × 20 mm3 has been obtained in water. The basic thermal and optical properties were characterized. We find that the TPPB (2H2O) crystal shows excellent transparent property in the near-IR region. Large Raman shifts and strong Raman scattering intensity indicate that TPPB is a potential candidate in Raman-scattering-based nonlinearity applications.