Alexander Lukin’s research while affiliated with Hydrometeorological Research Centre of Russian Federation and other places

The swift progress in low-dimensional nanocarbons, specifically in the realm of the authentic one-dimensional carbon chain featuring sp1 hybridization, has unveiled exciting prospects for integrating them into cutting-edge technologies across diverse industries. To fully harness their potential, precise control over the growth process is necessary to obtain desired nanostructure and functionality. However, optimizing properties through traditional approaches has been challenging due to complex interactions. To address this, we implement a focused data-driven strategy for nanocarbon inverse design by leveraging a state-of-the-art data-driven nanocarbon genome approach (NCGA). By uncovering relationships between growth parameters and resultant traits, this serves as an expedient catalyst in engineering nanostructures with tailored attributes. We introduce an extensive array of technological approaches aimed at precisely controlling the growth process. These methods encompass stimulating and precisely adjusting synergistic effects, coordinating atomic vibrations at a collective level through the implementation of multilayer nano-interfaces, harnessing the potential of active screen plasma surface engineering, utilizing nano-patterning and allotropic phase transformations, incorporating heteroatom doping, and effectively directing self-assembly. These aim to unlock nanomaterials' latent potential and reveal novel neural pathways within the data-driven NCGA, enhancing its predictive capabilities. Specifically, triggering self-organization during growth can potentially unlock previously unexplored neural pathways. The data-driven NCGA offers a paradigm shift, accelerating discovery and design of nanocarbons with optimized, application-specific properties.

This paper introduces an innovative nanotechnology-based approach that provides a pathway to enhance the energy release efficiency of nanoenergetic materials (nEMs) by harnessing self-synchronized collective atomic vibrations and phonon wave resonance within the transition domains between nanocomponents, without altering the material composition. The key innovation involves incorporating finely-tuned 2D-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into the transition domains using advanced multistage processing and assembly techniques. These programmable nanodevices enable precise control over self-synchronized collective atomic vibrations and phonon wave propagation, leading to synergistic effects. To activate and optimize these effects, a combination of various methods is employed, including energy-driven initiation of allotropic phase transformations, surface acoustic wave-assisted micro/nano-manipulation, heteroatom doping, directed self-assembly using high-frequency electromagnetic fields, and data-driven inverse design approaches. By leveraging a data-driven inverse design strategy and uncovering hidden structure-property relationships, we maximize energy release efficiency using the carbon nano-materials genome approach derived from multifactorial neural network-based predictive models. This approach not only unlocks new functionalities in nEMs but also improves environmental performance and safety levels. By pioneering transformative pathways for nEMs through harnessing phonon wave resonance in low-dimensional nanocarbon transition interfaces, this research brings significant advancements in the field.

This paper introduces a new nanotechnology-driven approach that provides a transformative pathway to substantially enhance the energy release efficiency of nanoenergetic materials (nEMs) without altering their chemical composition. The groundbreaking concept involves strategically harnessing, self-synchronized collective atomic vibrations and phonon wave resonance phenomena within the transition domain's interconnecting nanocomponents. A key novelty is the incorporation of meticulously engineered two-dimensional-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into these transition domains, facilitated by advanced multistage processing and assembly techniques. These programmable nanodevices enable unprecedented control over the initiation, propagation, and coupling of self-synchronized collective atomic vibrations and phonon waves, unleashing powerful synergistic effects. Central to this approach is the bidirectional, self-reinforcing interaction between precisely tailored nano-architectures and phonon dynamics within the multilayer nano-enhanced interfaces. This synergistic coupling facilitates the rational programming of energy transfer pathways, granting access to previously inaccessible energy reserves inherently locked within the nEM systems. To optimally activate and harness these synergistic mechanisms, a strategic combination of cutting-edge methods is judiciously employed. These include energy-driven stimulation of allotropic phase transformations, surface acoustic wave-assisted manipulation at micro-/nanoscales, heteroatom doping, directed self-assembly driven by high-frequency electromagnetic fields, and a data-driven inverse design framework. Notably, by leveraging a data-driven inverse design strategy rooted in multifactorial neural network predictive models, we uncover previously hidden structure-property relationships governing the nano-enhanced interfaces. This novel data-driven "nanocarbon genome" approach enables rational maximization of energy release efficiency in nEM systems. Overall, this transformative nanoscale concept not only unlocks unprecedented high-energy functionalities but also ushers in significant improvements in environmental sustainability and operational safety for nEMs.

Recent advances in nanomaterials have been heavily influenced by low-dimensional nanocarbon allotropes. In particular, carbyne has attracted attention for its potential as a true one-dimensional carbon chain with sp1 hybridization. To maximize the capabilities of this material, we employ a focused data-driven inverse design approach based on the carbon nanomaterials genome concept. This involves using deep learning neural network models to identify key descriptors tied to desired properties, enabling property prediction and reverse engineering of nanocarbons. Our iterative approach entails: (i) gathering growth/property data on nanostructures; (ii) identifying informative numerical/categorical predictors; (iii) developing deep learning models mapping descriptors to properties; (iv) refining models with new insights; (v) determining required descriptors/conditions for target properties via inverse mapping; (vi) validating models by synthesizing predicted nanostructures; and (vii) enhancing models with validation data. This allows uncovering hidden growth-property connections, precisely tuning nanocarbons for desired attributes. We introduce new methodologies including exciting synergistic effects, synchronizing atomic vibrations, active screen plasma, energy-driven transformations, surface acoustic micro/nano-manipulation, doping and directed self-assembly to expose relationships and integrate insights into the inverse design flow. This research promises to accelerate discovery of next-generation low-dimensional nanocarbons with exceptional properties and applications.

This paper introduces an innovative nanotechnology-based approach that provides a pathway to enhance the energy release efficiency of nanoenergetic materials (nEMs) by harnessing self-synchronized collective atomic vibrations and phonon wave resonance within the transition domains between nanocomponents, without altering the material composition. The key innovation involves incorporating finely-tuned 2D-ordered linear-chain carbon-based multilayer nano-enhanced interfaces as programmable nanodevices into the transition domains using advanced multistage processing and assembly techniques. These programmable nanodevices enable precise control over self-synchronized collective atomic vibrations and phonon wave propagation, leading to synergistic effects. To activate and optimize these effects, a combination of various methods is employed, including energy-driven initiation of allotropic phase transformations, surface acoustic wave-assisted micro/nano-manipulation, heteroatom doping, directed self-assembly using high-frequency electromagnetic fields, and data-driven inverse design approaches. By leveraging a data-driven inverse design strategy and uncovering hidden structure-property relationships, we maximize energy release efficiency using the carbon nanomaterials genome approach derived from multifactorial neural network-based predictive models. This approach not only unlocks new functionalities in nEMs but also improves environmental performance and safety levels. By pioneering transformative pathways for nEMs through harnessing phonon wave resonance in low-dimensional nanocarbon transition interfaces, this research brings significant advancements in the field.

We propose to uncover new opportunities for predictive nano-sized energetic materials performance enhancement through manipulating by vibrational interactions, energy exchange as well as heat transfer enhancement within the reaction zones at nanoscale. The combination of multiple carbon nanostructured materials with various hybridizations within a single substance can uncover new unique properties. Due to a recent fundamental discovery the collective atomic vibrations, called phonon waves, manifested in transition domains of multilayer nanostructures, incorporation of self-organized arrays of metastable nanostructures are capable controlling vibrational interactions and energy exchange within the reaction zones at nanoscale. For using this phenomenon, we propose predictive incorporation into the nano-sized energetic material composition of various carbon-based allotropes, used as catalytic nano-additives, combined with assembling them by the self-organized arrays of differently hybridized low-dimensional nanocarbon promoters. For predictive combining of multiple differently hybridized nanocarbons within a single substance we propose to use the energy-driven initiation of the allotropic phase transformations in nanocarbon promoters by concurrent electron and ion irradiation. For fine tuning the collective atomic vibrations, nanoarchitecture and functionality of the mentioned arrays of differently hybridized nanocarbon promoters we propose using combination of a set of techniques: concurrent electron and ion irradiation, using the surface acoustic waves combined with heteroatom doping along with application external electromagnetic fields and using the data-driven nanoscale manufacturing approach.

Due to the unique combination of physicochemical and structural properties of carbyne-enriched nanocoatings, they can be used for the development of high-end electronic devices. We propose using it for the development of sensor platforms based on silicon bulk micromachined membranes that serve as a part of microcapacitors with flexible electrodes, with various sizes and topologies. The carbyne-enriched nanocoating was grown using the ion-assisted pulse-plasma deposition method in the form of 2D-ordered linear-chain carbon with interchain spacing in the range of approximately 4.8–5.03 Å. The main characteristics of the fabricated sensors, such as dynamic range, sensitivity, linearity, response, and recovery times, were measured as a function of the ethanol concentration and compared for the different sizes of the micromembranes and for the different surface states, such as patterned and non-patterned. The obtained results are the first step in the further optimization of these sensor platforms to reach more precise detection of volatile organic compounds for the needs of the healthcare, air monitoring, and other relevant fields of human health.

The application of carbyne-enriched nanomaterials opens unique possibilities for enhancing the functional properties of several nanomaterials and unlocking their full potential for practical applications in high-end devices. We studied the ethanol-vapor-sensing performance of a carbyne-enriched nanocoating deposited onto surface acoustic wave (SAW) composite substrates with various electrode topologies. The carbyne-enriched nanocoating was grown using the ion-assisted pulse-plasma deposition technique. Such carbon nanostructured metamaterials were named 2D-ordered linear-chain carbon, where they represented a two-dimensionally packed hexagonal array of carbon chains held by the van der Waals forces, with the interchain spacing approximately being between 4.8 and 5.03 Å. The main characteristics of the sensing device, such as dynamic range, linearity, sensitivity, and response and recovery times, were measured as a function of the ethanol concentration. To the authors’ knowledge, this was the first time demonstration of the detection ability of carbyne-enriched material to ethanol vapors. The results may pave the path for optimization of these sensor architectures for the precise detection of volatile organic compounds, with applications in the fields of medicine, healthcare, and air composition monitoring.

A recently proposed, game-changing transformative energetics concept based on predictive synthesis and preprocessing at the nanoscale is considered as a pathway towards the development of the next generation of high-end nanoenergetic materials for future multimode solid propulsion systems and deep-space-capable small satellites. As a new door for the further performance enhancement of transformative energetic materials, we propose the predictive ion-assisted pulse-plasma-driven assembling of the various carbon-based allotropes, used as catalytic nanoadditives, by the 2D-ordered linear-chained carbon-based multicavity nanomatrices serving as functionalizing nanocarriers of multiple heteroatom clusters. The vacant functional nanocavities of the nanomatrices available for heteroatom doping, including various catalytic nanoagents, promote heat transfer enhancement within the reaction zones. We propose the innovative concept of fine-tuning the vibrational signatures, functionalities and nanoarchitectures of the mentioned nanocarriers by using the surface acoustic waves-assisted micro/nanomanipulation by the pulse-plasma growth zone combined with the data-driven carbon nanomaterials genome approach, which is a deep materials informatics-based toolkit belonging to the fourth scientific paradigm. For the predictive manipulation by the micro- and mesoscale, and the spatial distribution of the induction and energy release domains in the reaction zones, we propose the activation of the functionalizing nanocarriers, assembled by the heteroatom clusters, through the earlier proposed plasma-acoustic coupling-based technique, as well as by the Teslaphoresis force field, thus inducing the directed self-assembly of the mentioned nanocarbon-based additives and nanocarriers.