Archive | October 2016

Biological Spintronic Semiconductors: Frontiers

Spintronics

Spintronics is an emerging field of basic and applied research in physics and engineering.  Spintronics, meaning “spin transport electronics”, exploits the intrinsic spin of electrons, in addition to their electronic charge, in solid-state devices like sensors.

Spintronic devices make use of spin properties instead of, or in addition to electron charge to carry information, thereby offering opportunities for novel micro‐ and nano‐electronic devices. These devices are expected to become the ideal memory media for computing and main operating media for future quantum computing..  In spintronics the spin of an electron is controlled by an external magnetic field and polarize the electrons. These polarized electrons are used to control the electric current. The goal of spintronics is to develop a semiconductor that can manipulate the magnetism of an electron…  External magnetic fields can be applied so that the spins are aligned (all up or all down), allowing a new way to store binary data in the form of one’s (all spins up) and zeroes (all spins down).

Biological materials are being investigated in spintronics as in the face of continued miniaturization of components and circuitry in microelectronics, conventional semiconductor microelectronics is rapidly approaching its useful miniaturization limits… For an alternative approach…. biological molecules are known to self‐assemble with nanometer scale resolution and possess some unique qualities that might be crucial for nanoscale fabrication.  A Fakhar 2008.

Biological Semiconductors

The concept of biological semiconductors has been around for some years (e.g A V Vannikov 1970. Bioelectrical signals play critical roles in many biological processes such as energy harvesting, rapid communications and inter/intra cellular synchronisation.  Specific examples include photosynthesis, vision, carbohydrate metabolism, neurophysiology, wound healing, tissue regeneration and embryonic development.

Biological semiconductors already identified include melanin and peptides. Charge transport has also been found in a variety of naturally-derived small molecule, semiconducting biological compounds including carotenoids (produced by plants and bacteria), which offer protection against oxidative species, pigmentation, and light harvesting for photosynthesis. M Mukovich 2012.  

The Giese Group, examined electron transfer along a series of polypeptides and demonstrated that the existence of central aromatic acids can serve as stepping stones to support the electron hopping mechanism. W Sun 2016.  It has been noted that ‘assuming an electron or hole in a polypeptide is located on any peptide group, then if the life of this state is comparable with the period of interpeptide vibrations, the distances between all the bonds in the peptide group are changed and stabilised in this state.  Furthermore, in the neighbourhood of this peptide group, the distances between neighbouring peptitdes also becomes different, which changes the probability of transfer from group to group.  It is observed that the proposed mechanism for this is extremely similar to the mechanism of the motion of a polaron in an oxide semiconductor’. L I. Boguslavskii – 2013.

Spintronics, Spin Chemistry and Quantum Biology 

Spin chemistry is an older field of science than spintronics.  It has been drawn upon by those attempting to explain room temperature quantum mechanical effects in photosynthesis and (possibly) magnetoreception (N Lambert 2013).

Very recently it has been recognised that the fields of spin chemistry and spintronics  are working on very similar areas of science and there is a strong argument for drawing the two fields together.

 J Matysik (2017)  has provided an initial ontology that describes the similarities and differences  between the findings of each field.  It might also be useful to turn this into a semantic web ontology to assist in research, and also connect in other fields including quantum biology, and broader biology.  It is important that there is more communication between chemistry, physics and biology around spin in biological materials.

There are various theories relating to quantum biology, but it is hoped that with the drawing together of scientific disciplines, the exact mechanisms will become clearer.

Quantum Biology as Biological Spintronic Semiconductors.

There are several evidenced examples in biology of processes which involve ultra-fast electron transfer, singlet and triplet spin mechanisms and quantum coherence (taking place at room temperature).

  1. Evidence of the solid state photo-CIDNP effect, singlet and triplet states, ultra-fast electron transfer, and quantum coherence in photosynthesis.
  2. Evidence of the solid state photo-CIDNP effect, singlet and triplet states and ultra-fast electron transfer in some flavoproteins.  In addition there are widely explored scientific theories of cryptochrome (a flavoprotein) and/or magnetite triggering a quantum mechanical effect during ‘magnetoreception’.

Manifestations of quantum coherence in different solid state systems include semiconductor confined systems, magnetic systems, crystals and superconductors. Ultrafast electron transfer and charge separation is possible in semiconductors A Ayzner 2015, S Gélinas 2014.

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Good Timing: The Synchronisation of Neural Networks in Computing and Implications for Neurology

A symbiotic relationship now exists between the study of neural networking in computing, and neurology.  Artificial neural networks were originally inspired by neuroscience, although major developments have been guided by insights into the mathematics of efficient optimization, rather than neuroscientific findings.  A H Marblestone 2016.  Now neurology is looking towards the development of neural networks to increase our understanding of how the brain works.  There is the possibility that  the two fields will increasingly merge – with particular recognition of the importance of bio-physics in the study of intelligence.

For a long time, the accepted model of memory formation was linear. Short term memories were thought to directly transform into long term memory in a classical, mechanistic fashion. But this model has been challenged.

The new model emerging is complex and non-linear.  The brain is starting to be seen as ‘more than the sum of its parts’ – analogous to a parallel computer (with many interconnected networks), artificial neural networks/deep learning, or a ‘network of networks (such as the Internet), with all the problems (cascading failures) and solutions (built in redundancy) that are associated with such a model.

Modern neuroscience is going through a renaissance of its own – moving away from mechanistic views of the brain, to focus on connectivity.  It recognises some networks may be particularly important for such connectivity e.g the default mode network – which is effected in various neurological conditions such as Alzheimer’s, as well as altered states of consciousness such as meditation and psychedelic drug use.
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Circadian Rhythms and Ageing

Intraterrestrial life extends down at least 5 km and animals are found even in the deepest oceans. The biosphere is, therefore, dominated by dark, largely “arrhythmic” habitats, and in terms of biomass, most of life on earth resides in places isolated from the direct effects of the sun…studies of species that live away from the sun […]

Is the Coupling of Circadian Rhythms and Metabolism/Redox Regulating Morphogenesis

Self Organisation Far from Equilibrium

New states can arise from far from equilibrium, possessing an extraordinary degree of order, whereby trillions of molecules coordinate their actions in space and time. Under certain circumstances, entropy producing processes are able to organise themselves in the presence of noise, in a way that so called dissipative structures are formed (Prigogine and Lefever 1975, and Nicolis and Prigogine 1977).  Also see J England 2015 on ‘dissipative adaptation in driven self-assembly’.

Dissipative processes are present in biology.  It is asked whether these could be contributing to morphogenesis.

Stochastic reaction-diffusion simulations have been successfully used in a number of biological applications. Formation of skin patterns and the biochemical processes in living cells (like gene regulatory networks), the cell cycle, circadian rhythms, signal transduction in E Coli chemotaxis, MAPK pathway, oscillations of Min proteins in cell division, and intracellular calcium dynamics are examples of processes mathematically modelled by reaction and reaction-diffusion systems. T Vejchodsky 2013, J Eliaš – ‎2014A Zakharov 2014T Hinze 2011. Read More…