180 research outputs found
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
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