Interlayer Registry Determines the Sliding Potential of Layered Metal Dichalcogenides: The case of 2H-MoS2

We provide a simple and intuitive explanation for the interlayer sliding energy landscape of metal dichalcogenides. Based on the recently introduced registry index (RI) concept, we define a purely geometrical parameter which quantifies the degree of interlayer commensurability in the layered phase of molybdenum disulphide (2HMoS2). A direct relation between the sliding energy landscape and the corresponding interlayer registry surface of 2H-MoS2 is discovered thus marking the registry index as a computationally efficient means for studying the tribology of complex nanoscale material interfaces in the wearless friction regime.Comment: 13 pages, 7 figure

Graphene transistors are insensitive to pH changes in solution

We observe very small gate-voltage shifts in the transfer characteristic of as-prepared graphene field-effect transistors (GFETs) when the pH of the buffer is changed. This observation is in strong contrast to Si-based ion-sensitive FETs. The low gate-shift of a GFET can be further reduced if the graphene surface is covered with a hydrophobic fluorobenzene layer. If a thin Al-oxide layer is applied instead, the opposite happens. This suggests that clean graphene does not sense the chemical potential of protons. A GFET can therefore be used as a reference electrode in an aqueous electrolyte. Our finding sheds light on the large variety of pH-induced gate shifts that have been published for GFETs in the recent literature

Electromechanical properties of suspended Graphene Nanoribbons

Graphene nanoribbons present diverse electronic properties ranging from semiconducting to half-metallic, depending on their geometry, dimensions and chemical composition. Here we present a route to control these properties via externally applied mechanical deformations. Using state-of-the-art density functional theory calculations combined with classical elasticity theory considerations, we find a remarkable Young's modulus value of ~7 TPa for ultra-narrow graphene strips and a pronounced electromechanical response towards bending and torsional deformations. Given the current advances in the synthesis of nanoscale graphene derivatives, our predictions can be experimentally verified opening the way to the design and fabrication of miniature electromechanical sensors and devices based on ultra-narrow graphene nanoribbons.Comment: 12 pages, 6 figure

Graphene Transistor as a Probe for Streaming Potential

We explore the dependence of electrical transport in a graphene field effect transistor (GraFET) on the flow of the liquid within the immediate vicinity of that transistor. We find large and reproducible shifts in the charge neutrality point of GraFETs that are dependent on the fluid velocity and the ionic concentration. We show that these shifts are consistent with the variation of the local electrochemical potential of the liquid next to graphene that are caused by the fluid flow (streaming potential). Furthermore, we utilize the sensitivity of electrical transport in GraFETs to the parameters of the fluid flow to demonstrate graphene-based mass flow and ionic concentration sensing. We successfully detect a flow as small as~70nL/min, and detect a change in the ionic concentration as small as ~40nM.Comment: 6 pages, 4 figure

From 2D to 3D: novel nanostructured scaffolds to investigate signalling in reconstructed neuronal networks

To recreate in vitro 3D neuronal circuits will ultimately increase the relevance of results from cultured to whole-brain networks and will promote enabling technologies for neuro-engineering applications. Here we fabricate novel elastomeric scaffolds able to instruct 3D growth of living primary neurons. Such systems allow investigating the emerging activity, in terms of calcium signals, of small clusters of neurons as a function of the interplay between the 2D or 3D architectures and network dynamics. We report the ability of 3D geometry to improve functional organization and synchronization in small neuronal assemblies. We propose a mathematical modelling of network dynamics that supports such a result. Entrapping carbon nanotubes in the scaffolds remarkably boosted synaptic activity, thus allowing for the first time to exploit nanomaterial/cell interfacing in 3D growth support. Our 3D system represents a simple and reliable construct, able to improve the complexity of current tissue culture models

Effects of IKAP/hELP1 Deficiency on Gene Expression in Differentiating Neuroblastoma Cells: Implications for Familial Dysautonomia

Familial dysautonomia (FD) is a developmental neuropathy of the sensory and autonomous nervous systems. The IKBKAP gene, encoding the IKAP/hELP1 subunit of the RNA polymerase II Elongator complex is mutated in FD patients, leading to a tissue-specific mis-splicing of the gene and to the absence of the protein in neuronal tissues. To elucidate the function of IKAP/hELP1 in the development of neuronal cells, we have downregulated IKBKAP expression in SHSY5Y cells, a neuroblastoma cell line of a neural crest origin. We have previously shown that these cells exhibit abnormal cell adhesion when allowed to differentiate under defined culture conditions on laminin substratum. Here, we report results of a microarray expression analysis of IKAP/hELP1 downregulated cells that were grown on laminin under differentiation or non-differentiation growth conditions. It is shown that under non-differentiation growth conditions, IKAP/hELP1 downregulation affects genes important for early developmental stages of the nervous system, including cell signaling, cell adhesion and neural crest migration. IKAP/hELP1 downregulation during differentiation affects the expression of genes that play a role in late neuronal development, in axonal projection and synapse formation and function. We also show that IKAP/hELP1 deficiency affects the expression of genes involved in calcium metabolism before and after differentiation of the neuroblastoma cells. Hence, our data support IKAP/hELP1 importance in the development and function of neuronal cells and contribute to the understanding of the FD phenotype

The Baltimore declaration toward the exploration of organoid intelligence

We, the participants of the First Organoid Intelligence Workshop - "Forming an OI Community" (22-24 February 2022), call on the international scientific community to explore the potential of human brain-based organoid cell cultures to advance our understanding of the brain and unleash new forms of biocomputing while recognizing and addressing the associated ethical implications. The term "organoid intelligence" (OI) has been coined to describe this research and development approach (1) in a manner consistent with the term "artificial intelligence" (AI) - used to describe the enablement of computers to perform tasks normally requiring human intelligence. OI has the potential for diverse and far-reaching applications that could benefit humankind and our planet, and which urge the strategic development of OI as a collaborative scientific discipline. OI holds promise to elucidate the physiology of human cognitive functions such as memory and learning. It presents game-changing opportunities in biological and hybrid computing that could overcome significant limitations in silicon-based computing. It offers the prospect of unparalleled advances in interfaces between brains and machines. Finally, OI could allow breakthroughs in modeling and treating dementias and other neurogenerative disorders that cause an immense and growing disease burden globally. Realizing the world-changing potential of OI will require scientific breakthroughs. We need advances in human stem cell technology and bioengineering to recreate brain architectures and to model their potential for pseudo-cognitive capabilities. We need interface breakthroughs to allow us to deliver input signals to organoids, measure output signals, and employ feedback mechanisms to model learning processes. We also need novel machine learning, big data, and AI technologies to allow us to understand brain organoids