Top-down Methods Research Articles

Digitalisation and Cybersecurity: Towards an Operational Framework

As businesses increasingly adopt digital processes and solutions to enhance efficiency and productivity, they face heightened cybersecurity threats. Through a systematic literature review and concept development, this article examines the intersection of digitalisation and cybersecurity. It identifies the methodologies and tools used for cybersecurity assessments, factors influencing the adoption of cybersecurity measures, and the critical success factors for implementing these measures. The article also puts forward the concept of cybersecurity governance process categories, which are used to classify the factors uncovered in the research. Findings suggest that current information security standards tend to be too broad and not adequately tailored to the specific needs of small and medium-sized enterprises (SMEs) when implementing emerging technologies, like Internet of Things (IoT), blockchain, and artificial intelligence (AI). Additionally, these standards often employ a top-down approach, which makes it challenging for SMEs to effectively implement them, as they require more scalable solutions tailored to their specific risks and limited resources. The study thus proposes a new framework based on the Plan-Do-Check model, built around the cybersecurity governance process categories and the three core pillars of governance, culture and standards. This is essentially a bottom-up approach that complements current top-down methods, and will be of value to both information technology (IT) professionals as an operational guide, and to researchers as a basis for future research in this field.

High-Yield Production of SiV-Doped Nanodiamonds for Spectroscopy and Sensing Applications.

Nanodiamonds (NDs) containing optically active centers have gained significant relevance as the material of choice for biological, optoelectronic, and quantum applications. However, current production methods lag behind their real needs. This study introduces two CVD-based approaches for fabricating NDs with optically active silicon-vacancy (SiV) color centers: bottom-up (BU) and top-down (TD) methods. The BU approach generates nanoporous diamond films with a core-shell structure, while the TD method employs molten-salt thermal etching to create uniform porous structures from nanocrystalline diamond films. Comprehensive characterization using advanced techniques revealed distinct morphologies and optical properties for each approach. The BU method yielded higher-quality diamond phases with top-surface incorporation of SiV centers, while the TD method demonstrated efficient nondiamond phase removal. Ultrasonic disintegration of both porous films produced NDs ranging from 40 to 500 nm, with unique morphologies characteristic of each approach. Photoluminescence measurements confirmed SiV centers (738 nm) in all NDs, exhibiting sensitivity to surface terminations, particularly in BU samples. Temperature-resolved spectroscopy shows the potential of the fabricated NDs for nano thermometry over a wide range of temperatures up to 100 °C. The zero-phonon line shows 0.022 ± 0.003 nm/K sensitivity, while the line width exhibits 0.068 ± 0.004 nm/K broadening. The presented BU and TD methods offer significant advantages over existing techniques, including streamlined production processes, high-yield ND synthesis with tailored properties, and the potential for scalable, cost-effective manufacturing.

A Review on Nanoparticles : The Building Blocks of Tomorrows Technology

Nanoparticles, defined as particles with dimensions in the nanometer range, exhibit unique properties that differ from their bulk counterparts, making them invaluable across various fields such as medicine, electronics, and environmental protection. Their small size and specific characteristics enable advanced applications, including targeted drug delivery, enhanced imaging, and improved sensors. Notable types of nanoparticles include silver, gold, magnetic, iron oxide, and platinum, each with distinct uses: silver for antimicrobial applications, gold for protein detection and drug delivery, magnetic for drug delivery and bio sensing, iron oxide for diagnostics and therapy, and platinum for catalysis. Nanoparticles are synthesized through top-down methods like milling and laser ablation, and bottom-up approaches such as sol-gel and hydrothermal processes. Their preparation involves techniques like emulsion-solvent evaporation and polymerization. Effective characterization, including analysis of size, shape, zeta potential, and drug entrapment efficiency, is essential for optimizing their performance in various applications. The review's current focus is on the synthesis, types, characterization, and most advanced applications of nanotechnology.

Rethinking Nanoparticle Synthesis: A Sustainable Approach vs. Traditional Methods.

This review portrays a comparison between green protocols and conventional nanoparticle (NP) synthesis strategies, highlighting each method's advantages and limitations. Various top-down and bottom-up methods in NP synthesis are described in detail. The green chemistry principles are emphasized for designing safe processes for nanomaterial synthesis. Among the green biogenic sources plant extracts, vitamins, enzymes, polysaccharides, fungi (Molds and mushrooms), bacteria, yeast, algae, and lichens are discussed. Limitations in the reproducibility of green protocols in terms of availability of raw material, variation in synthetic protocol, and selection of material due to geographical differences are elaborated. Finally, a conclusion is drawn utilizing green chemical principles, & a circular economy strategy to minimize waste generation, offering a promising framework for the synthesis of NPs emphasizing sustainability.

Toolpath and Tool Design Innovations in Deformation Machining for Superior AA-7075 T6 Fins

Abstract A hybrid manufacturing process, deformation machining (DM) combines subtractive manufacturing with incremental forming. Monolithic components with complex profiles are created through the hybridization of manufacturing technologies, which also reduces the wastage of raw materials. The properties of geometry and surface quality of the fin made from the aluminum alloy Al-7075 T6 using the DM process’s bending mode was examined in this research, as were the effects of various approaches, toolpath methods, and tool design. To achieve the desired shape for the machined fin, various combinations of arcuate and slanting fin toolpath techniques were explored utilizing both top-down and bottom-up methods. The bottom-up method and the arcuate toolpath strategy were used to investigate various tool profiles. Using the best combination of toolpath strategy and tool profile, named as the T3 tool profile, which has a 0.6 mm nose radius and a circular sector, bottom-to-top (BTT)technique, and arcuate toolpath method, components with better geometrical features and surface roughness (SR) were produced. The analysis of the forming force in the bending approach of the DM progression was further carried out using this optimal combination.

Assessing methane emissions and multiple benefits of mitigation through coupled crop-livestock system

A potent greenhouse gas, methane, contributes to global warming, primarily from livestock activities such as fermentation and manure management. Recognized as a low-carbon agricultural approach, coupled crop–livestock systems are gaining increasing attention for mitigating methane emissions and environmental impacts. This study focused on Inner Mongolia to estimate its methane reduction potential. We calculated methane emissions using a combination of bottom-up and top-down methods, analyzed livestock distribution, estimated manure production, and assessed the potential of manure to replace chemical fertilizers based on crop nutrient demand. Livestock emissions totaled approximately 769.0 kt. Adopting crop–livestock coupling could reduce emissions by 30.1 kt. Returning manure as fertilizer can cover 57.7% of cropland, saving 57% nitrogen and 20% phosphorus fertilizers, thus reducing costs by $296.3 million. The study has provided a scientific reference for developing methane emission reduction strategies, which can shed light on tackling climate change in the context of agricultural systems.

Comparison of observation- and inventory-based methane emissions for eight large global emitters

Abstract. Monitoring the spatial distribution and trends in surface greenhouse gas (GHG) fluxes, as well as flux attribution to natural and anthropogenic processes, is essential to track progress under the Paris Agreement and to inform its global stocktake. This study updates earlier syntheses (Petrescu et al., 2020, 2021, 2023), provides a consolidated synthesis of CH4 emissions using bottom-up (BU) and top-down (TD) approaches for the European Union (EU), and is expanded to include seven additional countries with large anthropogenic and/or natural emissions (the USA, Brazil, China, India, Indonesia, Russia, and the Democratic Republic of the Congo (DR Congo)). Our aim is to demonstrate the use of different emission estimates to help improve national GHG emission inventories for a diverse geographical range of stakeholders. We use updated national GHG inventories (NGHGIs) reported by Annex I parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2023 and the latest available biennial update reports (BURs) reported by non-Annex I parties. Comparing NGHGIs with other approaches highlights that different system boundaries are a key source of divergence. A key system boundary difference is whether anthropogenic and natural fluxes are included and, if they are, how fluxes belonging to these two sources are partitioned. Over the studied period, the total CH4 emission estimates in the EU, the USA, and Russia show a steady decreasing trend since 1990, while for the non-Annex I emitters analyzed in this study, Brazil, China, India, Indonesia, and DR Congo, CH4 emissions have generally increased. Quantitatively, in the EU the mean of 2015–2020 anthropogenic UNFCCC NGHGIs (15±1.8 Tg CH4 yr−1) and the mean of the BU CH4 emissions (17.8 (16–19) Tg CH4 yr−1) generally agree on the magnitude, while inversions show higher emission estimates (medians of 21 (19–22) Tg CH4 yr−1 and 24 (22–25) Tg CH4 yr−1 for the three regional and six global inversions, respectively), as they include natural emissions, which for the EU were quantified at 6.6 Tg CH4 yr−1 (Petrescu et al., 2023). Similarly, for the other Annex I parties in this study (the USA and Russia), the gap between the BU anthropogenic and total TD emissions is partly explained by the natural emissions. For the non-Annex I parties, anthropogenic CH4 estimates from UNFCCC BURs show large differences compared to the other global-inventory-based estimates and even more compared to atmospheric ones. This poses an important potential challenge to monitoring the progress of the global CH4 pledge and the global stocktake. Our analysis provides a useful baseline to prepare for the influx of inventories from non-Annex I parties as regular reporting starts under the enhanced transparency framework of the Paris Agreement. By systematically comparing the BU and TD methods, this study provides recommendations for more robust comparisons of available data sources and hopes to steadily engage more parties in using observational methods to complement their UNFCCC inventories, as well as considering their natural emissions. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, future development needs to resolve knowledge gaps in the BU and TD approaches and to better quantify the remaining uncertainty. TD methods may emerge as a powerful tool to help improve NGHGIs of CH4 emissions, but further confidence is needed in the comparability and robustness of the estimates. The referenced datasets related to figures are available at https://doi.org/10.5281/zenodo.12818506 (Petrescu et al., 2024).

Carbon metabolism modelling and regulation in Beijing

Land use and cover change leads to significant increases in urban carbon emissions. Considering the insufficiency of spatially fine-grained management in previous carbon emission studies, this study integrated top-down and bottom-up methods to simulate urban carbon metabolism. Metabolic actors were allocated to grids based on land use and POI data and then attributed to districts. Results indicated that from 2000 to 2018, Beijing's Carbon Imbalance Index increased by 55.81% in 2010 and declined by 12.46%. Carbon emission dominated the changes in the Carbon Imbalance Index, with the Production and Supply of Electric Power actors consistently accounting for over 25.96%, while the contribution of Urban and Transportation actors reached 20.11% and 27.74% in 2018, respectively. The metabolic actors exhibited a gradient distribution pattern from southeast to northwest. Artificial actors' carbon emissions decreased from the center to the periphery and spread along the road network, with the High-High cluster in the southeast mainly contributed by Manufacturing (22.33%) and the Production and Supply of Electric Power (20.16%) actors. Spatial distribution changes of Natural actors mainly occurred in Daxing and Chaoyang districts, whose absorption area extended by 45% and 37.26%, respectively, contributing to an increase in carbon absorption by 2.47 and 0.15 times. The Semi-natural actor exhibited net carbon emissions, with the High-High cluster in the southeast zone contributing 60.96% of emissions in 2000. We also categorized Beijing into four Areas based on the relationship between carbon emission and absorption. Targeted policy recommendations were formulated for different districts and metabolic actors.

IMAGE CAPTION GENERATOR USING CNN AND LSTM

Machine learning is now all the rage in the AI world. We have recently used AI to construct very clever devices with exceptional performance. Deep learning is a subset of machine learning that produces very accurate findings, which in turn indicates very good performance. Apps for picture description make use of deep learning in our study. Providing a description of a picture's content is what image description is all about. Object and action detection in the input picture is the foundation of the notion. When describing images, there are primarily two methods: bottom-up and top-down. Bottom-up methods create captions by combining the information of an input picture. Using different architectures, such as recurrent neural networks, top-down methods provide a semantic representation of an input picture, which is then translated into a caption. One potential advantage of picture description is that it might aid those with visual impairments in comprehending what is shown in online images. What follows is an explanation of the specifics. Looking at the image below, what can you make out?

POLO: Pose estimation with one-stage location-sensitive coding

The precise monitoring of fish keypoints and behavioral patterns is crucial in fish farming, influencing decisions on feeding schedules and assessing fish health. Traditional approaches to multi-object pose estimation often lean towards either Bottom-up or Top-down methods. Our innovative solution introduces a streamlined single-stage multi-object pose estimation framework, utilizing a unique approach to instance assignment based on location. By incorporating position encoding as an index for candidate pose heatmap groups, we achieve end-to-end multi-object pose estimation with reduced redundancy through non-maximum suppression. Our framework, named POLO, has been validated on a meticulously annotated fish keypoint dataset, demonstrating outstanding performance with a remarkable 65.34% OKS AP at 71.4 FPS on Tesla v100. With its real-time capabilities, POLO is highly adaptable, making it suitable for deployment on various edge computing devices and addressing real-world challenges effectively. We believe our framework can serve as a solid baseline for diverse pose estimation tasks across different domains.

One-pot radiolytically synthesized reduced graphene oxide-gold nanoparticles composites and exploration in energy storage

Graphene and its composites are of primary importance, particularly in the field of energy storage. Numerous bottom-up and top-down methods have been proposed in the literature to produce these materials with enhanced physicochemical properties. Recently, an innovative and green methodology was developed based on ionizing radiation, allowing the quantitative synthesis of graphene oxide-based materials. With the aim to extend this strategy for the preparation of hybrid nanomaterials, the objective of this work was the one-pot synthesis of nanocomposites composed of reduced graphene oxide – gold nanoparticles (rGO-AuNPs) via gamma ray-induced radiolytic reduction. UV–Vis Absorption Spectroscopy, Fourier Transform Infrared Spectroscopy, Raman Spectroscopy and X-ray Photoemission Spectroscopy were utilized to comprehensively evaluate the reduction degree of graphene oxide and the formation of gold nanoparticles. Atomic Force Microscopy and Scanning Electron Microscopy were employed to obtain the morphological and topographical information on synthesized nanocomposites. Thermal properties were investigated by Thermogravimetric Analysis and electrical properties were investigated using Cyclic Voltammetry and Potentiostatic Charge and Discharge method. The results demonstrated the successful reduction of graphene oxide and gold ions through the drastic transformation of oxygen-containing functional groups and the formation of gold nanoparticles. Electrical characterization results highlighted the excellent electrical properties of radiosynthesized rGO-AuNPs composites and their great potential for supercapacitance application.

Template Selection Strategy for Synthesis of One-Dimensional CrSbSe3 Ferromagnetic Semiconductor Nanoribbons.

CrSbSe3─the only experimentally validated one-dimensional (1D) ferromagnetic semiconductor─has recently attracted significant attention. However, all reported synthesis methods for CrSbSe3 nanocrystals are based on top-down methods. Here we report a template selection strategy for the bottom-up synthesis of CrSbSe3 nanoribbons. This strategy relies on comparing the formation energies of potential binary templates to the ternary target product. It enables us to select Sb2Se3 with the highest formation energy, along with its 1D crystal structure, as the template instead of Cr2Se3 with the lowest formation energy, thereby facilitating the transformation from Sb2Se3 to CrSbSe3 by replacing half of the Sb atoms in Sb2Se3 with Cr atoms. The as-prepared CrSbSe3 nanoribbons exhibit a length of approximately 5 μm, a width ranging from 80 to 120 nm, and a thickness of about 5 nm. The single CrSbSe3 nanoribbon presents typical semiconductor behavior and ferromagnetism, confirming the intrinsic ferromagnetism in the 1D CrSbSe3 semiconductor.

A deep top-down framework towards generalisable multi-view pedestrian detection

Multiple cameras have been frequently used to detect heavily occluded pedestrians. The state-of-the-art methods, for deep multi-view pedestrian detection, usually project the feature maps, extracted from multiple views, to the ground plane through homographies for information fusion. However, this bottom-up approach can easily overfit the camera locations and orientations in a training dataset, which leads to a weak generalisation performance and compromises its real-world applications. To address this problem, a deep top-down framework TMVD is proposed, in which the feature maps within the rectangular boxes, sitting at each cell of the discretized ground plane and of the average pedestrians’ size, in the multiple views are weighted and embedded in a top view. They are used to infer the locations of pedestrians by using a convolutional neural network. The proposed method significantly improves the generalisation performance when compared with the benchmark methods for deep multi-view pedestrian detection. Meanwhile, it also significantly outperforms the other top-down methods.

How Effective is the 360-degree Feedback Appraisal Method for Evaluating Employee Performance?

360-degree feedback, also known as multisource feedback, multi-rater feedback, or the 360-degree review system, is a comprehensive employee evaluation method designed to promote the all-around development of employees. Unlike traditional top-down appraisal methods, this system gathers input from various sources to create a holistic view of performance and areas for improvement. The 360-degree feedback process is designed to be continuous, supporting ongoing development throughout the year, rather than relying solely on periodic evaluations. This approach helps to address performance issues and foster growth on a regular basis, promoting a culture of continuous improvement.

Bilayer-favored intercalation induced low-voltage electrochemical production of nano-graphene oxide in neutral phosphate

Graphene oxide (GO) exhibits great potential in various fields such as catalysis, wastewater treatment, and energy storage. However, traditional top-down GO preparation methods based on graphite exfoliation often suffer from high energy consumption and inevitably environmental pollution. In this work, an environmentally benign and low-voltage electrochemical exfoliation approach to fabricate nanoscale GO employing carbon fiber-based materials as the precursor using phosphate was proposed. Under neutral phosphate electrolyte, bilayer graphene oxide with a lateral size of ∼500 nm, thickness of ∼1.5 nm, and C/O ratio of 2.96 could be obtained via a constant potential process. By adjusting the pH to 12 to intensify the exfoliation reaction, the lateral size of the graphene oxide was controllable, decreasing to ∼50 nm, while the C/O ratio decreased to 0.9. Due to the further decrease in C/O ratio, the thickness increased slightly to 2–3 nm. The exfoliation potential (1.6–2.5 V vs. Ag/AgCl) and electrolyte concentration (50–500 mM) had an obvious impact on the yield of graphene oxide. Through electrochemical analysis such as linear sweep voltammetry, as well as density functional theory calculations, the exfoliation mechanism of phosphate is elucidated in detail, demonstrating that the stepwise ionized phosphate anions possess more robust intercalation capability than sulfate, thus enabling efficient exfoliation to the intertwined nanocrystalline graphite structure of carbon fibers. The DFT results revealed the bilayer-favored intercalation of phosphate, which accords well with experiments. This work provides a new controllable and green approach for GO synthesis, demonstrated by life cycle assessment. It could assist subsequent studies exploring the size effects of GO and its applications in environmental remediation and energy storage.

Collaborative optimization of multi-energy multi-microgrid system: A hierarchical trust-region multi-agent reinforcement learning approach

In the context of the expanding diversity of energy demands, an increasing number of heterogeneous Multi-energy Microgrids (MEMGs) are engaging in the collaborative framework of the Multi-energy Multi-microgrid System (MEMMG). However, following this trend, the existing centralized Integrated Energy Management System (IEMS) control strategy is unreliable for future energy systems, characterized by more complex optimization control and a flexible system structure. This paper introduces a hierarchical Multi-agent Deep Reinforcement Learning (HMADRL) approach for distributed IEMS in MEMMG. Firstly, by employing a hierarchical approach, this method simplifies control complexity by segmenting the overarching control challenge into tasks of collaborative planning and action control, which are distributed across varied multi-agent scenes. Considering both macro and microeconomic factors, alongside carbon emissions, the optimal operation of MEMMG is realized through a bottom-up edge multi-agent control approach, in contrast to traditional top-down centralized methods. Secondly, in the phase of the inter-MEMG collaborative strategy, the Centralized Training Decentralized Execution (CTDE) framework is adopted to overcome the problems of unstable training environments and large-scale agent training, and each heterogeneous microgrid can develop local strategies independently with the assurance that their internal data will not be overly exposed. Thirdly, within each MEMG, the Trust-Region (TR) model is introduced for multi-agent action control, adeptly addressing the effects of mutual exclusion in decision-making time series. Simultaneously, an initialized Hot Experience Pool (HEP) is implemented, efficiently reducing exploration in complex, high-dimensional spaces. Finally, the off-time agent model is integrated into the HMADRL environment and undergoes secondary training based on real interactions, thereby deriving the optimal energy management policy. The proposed method markedly reduces reliance on exact physical modeling systems. Comparative simulations validate the proposed control scheme’s efficacy.

The Impact of the NeuroAffective Relational Model (NARM) on Client Agency

ABSTRACT The NeuroAffective Relational Model (NARM) is a therapeutic model designed to treat Complex Post-Traumatic Stress Disorder (C-PTSD) integrating top-down (cognitive) and bottom-up (somatic) methods. Reinforcing client agency is one of the four pillars of the NARM model. This Interpretative Phenomenological Analysis investigated how NARM impacts client agency from the perspective of NARM Therapists. Fourteen NARM Therapists participated in a focus group to describe their work as a NARM trained trauma therapist treating clients who have experienced C-PTSD. The study revealed four themes that represent the phenomenon of client agency supported by the NARM model from the perspective of NARM Therapists. The emergent themes that support client agency include Connecting to Present Moment Awareness, Reflecting and Reinforcing Client Choices, Acknowledging Client Insight, and Contracting with the Client. Social workers can support clients experiencing C-PTSD by reinforcing client agency and utilizing trauma-informed approaches such as NARM to advance NASW standards for clinical social work practice standards one, two, and eleven (i.e. values and ethics, specialized practice skills, and interventions and professional development).

Lithography-Free Metaplasmonic Sensors Developed by TWD/GLAD Technique

Nowadays, plasmonic sensors are the most widely used and commercialized label-free optical biosensors and have become a widespread tool for studying chemical/biochemical interactions. Label-free, real-time, and direct measurements are the major benefits of the plasmonic sensors, including high-throughput surface bio-functionalization strategies without amplification or pretreatment of the sample [1]. The working principle of plasmonic sensing has been extensively described and reviewed over the decades [2], however, the possibility to develop cheap, effective, and clinically-accepted biosensors has recently become available due to the development of nanotechnology. Briefly, these nanostructures can be localized or can be arranged on 2D arrays of plasmonic metasurfaces, and can be fabricated by single-layer metallic films and a combination of metallic and dielectric films. The most popular plasmonic metals are gold and silver due to their high conductivity and low dielectric losses. Generally, top-down nanofabrication methods based on laser/e-beam lithography have been used, including nanostencil lithography based on shadow-masked nano-pattering and nanoimprint lithography [3]. Although such technologies have a high potential to achieve scalable and cost-effective nanofabrication at the wafer scale, these processes maintain the following main challenge: a master nano-mold/pattern is required to transfer metasurfaces with an associated high cost. Therefore, other technologies are the subject of research that overcomes this limitation and still offer an outstanding quality of metallic films, such as TDW (thermal dewetting) and GLAD (glancing angle deposition) (Fig.1). These techniques do not require master nano-mold/patterns; consequently, they can achieve lithography-free large-scale plasmonic metasurfaces [4]. TDW and GLAD usually generate quasi-ordered plasmonic metasurfaces compared to conventional lithographic methods.In this paper, the experimental results of the optical sensing properties of the sensors developed by the utilization of the combination of these two technologies in a single system are presented. The TWD/GLAD magnetron sputtering system has been designed and manufactured based on the Kurt J. Lesker MAG-Torus magnetrons, supplied with DC/RF power sources and an ECR manipulator that enables deposition at various angles with maximal 20 rpm rotation speed and heating option up to 850oC. The system is controlled by the software that enables deposition of the samples with the same parameters which pave the way for fabrication of the sensors on the industrial scale. The optical-sensing system was built based on an ST-VIS-50 spectrometer (Ocean Optics) and Tungsten Halogen Source (360-2000 nm, 2800 K, Ocean Optics) and optical table from Thorlabs. The obtained reflectance measurement has shown that the utilization of the GLAD technique decreases the reflectance peak in comparison with samples deposited without GLAD (flat samples). At the same time, angles in the range of 82-86oC seem to be preferable for nanostructure fabrication.Additionally, the utilization of the TWD technique, i.e. deposition at lower temperatures in the range of 60-100oC (depending on the substrate) and then annealed at higher temperatures such as 250oC and 300oC in a vacuum and under argon flow in the deposition chamber led to increased normalized response. However, the experiments have shown that the optimal annealing time is between 30-45 min depending on the SPR multi-structure, for example for Ag (6nm), Ti (2nm), and Au (2nm) the 30min at 250oC seems to be the best set. For such compositions, the surface sensitivity (nm/nm) and bulk sensitivity (nm/RIU) are more or less the same - 0.9 and 300, respectively. The obtained results are very promising for developing cheap, rapid, and very effective biosensors for various applications. Therefore, the obtained results seem to be very interesting for the ECS conference audience, for example, the developed Ag/Ti/Au multi-structures can be applied in novel organ-on-a-chip platforms for LADMET (liberations, absorption, distribution, metabolism, excretion, and toxicology) analysis [5].Fig. 1. Schematic diagram representation of lithography free methods for developing quasi-ordered metamaterials from left to right: Thermal dewetting and glancing angle deposition. The insert shows the chiral plasmonic nanospirals fabrication by glanced angle deposition [4].

On-Surface Synthesis of Open-Shell Nanographenes through the π-Extension of Dibenzo[Hi,St]Ovalene

Graphene nanostructures are attracting attentions for their intriguing optical, electronic, and magnetic properties that are critically dependent on their chemical structures. Whereas it is challenging to obtain atomically precise structures by typical top-down fabrication methods, such as lithographic patterning of graphene and unzipping of carbon nanotubes, bottom-up synthesis enables the preparation of molecular nanographenes and graphene nanoribbons (GNRs) with pre-designed structures. In addition to the solution synthesis based on the methods of synthetic organic chemistry, such graphene nanostructures can also be synthesized on metal surfaces under ultrahigh vacuum conditions and directly visualized by atomic resolution scanning probe microscopy (SPM) [1]. Using carefully designed and solution-synthesized molecular precursors, this on-surface synthesis method can provide various nanographenes, including the structures that are highly unstable under ambient conditions. We have previously developed the solution synthesis of dibenzo[hi,st]ovalene (DBOV) with strong red fluorescence [2], and achieved its π-extension to circumpyrene [3]. Following the successful synthesis of rhombus-shaped nanographenes with four zigzag edges, showing a closed-shell or an open-shell depending on the size [4], we functionalized DBOV and circumpyrene with two 2,6-dimethylphenyl groups for their on-surface π-extension to unprecedented zigzag-edged nanographenes. The resulting structures were clearly visualized by scanning tunneling microcopy and their open-shell characters were indicated by theoretical and experimental investigations, revealing large magnetic exchange couplings of up to 190 meV [5]. We have more recently also achieved further π-extension of these open-shell nanographenes on surface and obtained initial results for their polymerization.[1] Chen, Z.; Narita, A.; Müllen, K.; Adv. Mater. 2020, 32, 2001893.[2] Paternò, G. M.; Chen, Q.; Wang, X.-Y.; Liu, J.; Motti, S. G.; Petrozza, A.; Feng, X.; Lanzani, G.; Müllen, K.; Narita, A.; Scotognella, F., Angew. Chem. Int. Ed. 2017, 56, 6753–6757.[3] Chen, Q.; Schollmeyer, D.; Müllen, K.; Narita, A., J. Am. Chem. Soc. 2019, 141, 19994–19999.[4] Mishra, S.; Yao, X.; Chen, Q.; Eimre, K.; Gröning, O.; Ortiz, R.; Di Giovannantonio, M.; Sancho-García, J. C.; Fernández-Rossier, J.; Pignedoli, C. A.; Müllen, K.; Ruffieux, P.; Narita, A.; Fasel, R.; Nat. Chem. 2021, 13, 581.[5] Biswas, K.; Soler, D.; Mishra, S.; Chen, Q.; Yao, X.; Sánchez-Grande, A.; Eimre, K.; Mutombo, P.; Martín-Fuentes, C.; Lauwaet, K.; Gallego, J. M.; Ruffieux, P.; Pignedoli, C. A.; Müllen, K.; Miranda, R.; Urgel, J. I.; Narita, A.; Fasel, R.; Jelínek, P.; Écija, D. J. Am. Chem. Soc. 2023, 145, 2968–2974.

Toward Practical Applications of Engineered Living Materials with Advanced Fabrication Techniques.

Engineered Living Materials (ELMs) are materials composed of or incorporating living cells as essential functional units. These materials can be created using bottom-up approaches, where engineered cells spontaneously form well-defined aggregates. Alternatively, top-down methods employ advanced materials science techniques to integrate cells with various kinds of materials, creating hybrids where cells and materials are intricately combined. ELMs blend synthetic biology with materials science, allowing for dynamic responses to environmental stimuli such as stress, pH, humidity, temperature, and light. These materials exhibit unique "living" properties, including self-healing, self-replication, and environmental adaptability, making them highly suitable for a wide range of applications in medicine, environmental conservation, and manufacturing. Their inherent biocompatibility and ability to undergo genetic modifications allow for customized functionalities and prolonged sustainability. This review highlights the transformative impact of ELMs over recent decades, particularly in healthcare and environmental protection. We discuss current preparation methods, including the use of endogenous and exogenous scaffolds, living assembly, 3D bioprinting, and electrospinning. Emphasis is placed on ongoing research and technological advancements necessary to enhance the safety, functionality, and practical applicability of ELMs in real-world contexts.