Various disciplines of engineering have contributed immensely in the progress of biology and medical science. The article examines how mechanical engineers who specialise in man-made machines can develop an understanding of the natural machines of life sciences and see that the domains of engineering, modern biology and medicine can potentially unlock the secrets of the natural world.
By the nature of the discipline, mechanical engineering plays a forefront role in the design and construction of inanimate machines using inanimate resources – man-made machines. On the other hand, biology and life sciences have contributed immensely to our understanding of the animate world – natural machines.
Technological advancements in different disciplines of engineering have greatly benefited the domain of biology and medical science. Engineers of all disciplines need to have basic understanding [1] of other domains of study and other disciplines in their domain of study, thus enabling them to work in teams, understand the language and communicate with other disciplines and domains.
This can be achieved if flexible academic curricula can be implemented at engineering and medical institutions, encouraging engineers to cross the disciplinary boundaries [2] and strengthen innovation though interdisciplinary and multidisciplinary research [3].
Mechanical engineers with specialisation in biology/life sciences might want to pursue research as a medical scientist instead of doing a formal undergraduate program in medicine and practicing as a physician. Medical scientists with a mechanical engineering major will do a great deal in unlocking the secrets of biology and life sciences.
The understanding of biology and life sciences can be enhanced by clearly conceptualising how nature functions through the mechanism of transport phenomena [4] at the level of species, momentum, energy and charge taking place at multi scales of temporal and spatial contexts [5] as shown in Table 1. Cells are the basic unit of all living organisms, which heavily rely on the molecular and quantum transport processes for their functioning.
Table 1: Phenomenological equations governing transport phenomena
| Flux Quantity |
Transport/ Force Field Variable |
Transport Coefficient |
Phenome-nological Law, Year |
Equation for Phenomeno-logical Law |
Macroscopic parameter from Microscopic interactions |
Resistance (R), Flow and Force Field analogy |
| Mass
(JD) |
Concentration (c) |
Diffusion Coefficient (D) |
Fick’s Law, 1855 |
JD=-Ddc/dx |
D = vλ/3 |
Δc/Rmass |
| Momentum,
(JV),
Darcy
(JD) |
Velocity (u)/ Pressure (p), Osmosis |
Coefficient of Viscosity (µ), Permeability ( ξ),
Porosity (φ) |
Newton’s Law,
Darcy’s Law, 1856 |
Jv=-µdu/dy
JD=-(ξ/µ)dp/dx
Jv=JD/φ |
µ=ρNvλ/3
ρN=Particle density
v=Particle velocity
λ=Mean free path |
Δp/Rhydraulic,
Δp/RDarcy |
| Energy
(JQ) |
Temperature (T) |
Thermal Conductivity (k) |
Fourier’s Law, 1822 |
JQ=-kdT/dx |
k=ρNcmvλ/3
cm=Particle specific heat |
ΔT/Rthermal |
| Charge
(JE) |
Potential (Φ) |
Electrical Conductivity (σ) |
Ohm’s Law, 1827 |
JE=-σdΦ/dx |
σ=ρcq2 λ/(mv)
m=Particle mass
q=Charge
ρc=Charge density |
ΔΦ/Relectrical |
Modern technological revolutions
Different domains of study such as biology, engineering, sciences and management/finance seek to contribute towards the four main modern technological revolutions, namely nanotechnology, biotechnology, energy technology and scientific computing. A common thread linking the above major scientific revolutions is thermodynamics, as shown in Table 2.
It is needless to elaborate the role thermodynamics has played in unraveling the secrets of nature and always been at the helm of every technological revolution witnessed by scientific community. The landscapes as pictured by Maxwell, Boltzmann, Gibbs, Planck, Einstein, Schrödinger, Dirac, Onsager, Fermi, Prigogine, von Neumann, Feynman, Bose, Saha, Lippmann, de Gennes, Bejan [6,7], becomes particularly essential while seeking the common thread for unified understanding of the natural world.
Language is learned from one's own mother. Mathematics is the language of science. Thermodynamics is the mother of all sciences.
Table 2:
Thermodynamic link with modern technological revolutions
| Modern Technological Revolution |
Thermodynamic Link |
| Nano Technology |
Micro-Nano scale and Quantum Transport |
| Bio Technology |
Gibbs Bio Energetics, Biofuels |
| Energy Technology |
Exergy in Energy and Environment, Fuel Cells |
| Scientific Computing |
Reversible quantum computing, Information, Communication |
Table 3 lists the types and levels of thermodynamic study undertaken by different domains and disciplines of engineering and science. The central theme that connects all the different types of thermodynamic studies is entropy. Table 4 gives the details of various formulations of entropy types and their proponents.
Table 3: Types of thermodynamic study
| Type of Study |
Characteristic feature |
| Equilibrium/Classical Thermodynamics |
Macroscopic, continuum, process between equilibrium states |
| Statistical Thermodynamics |
Microscopic, particulate |
| Non-Equilibrium/Irreversible Thermodynamics |
Dissipative systems, near equilibrium, far from equilibrium, linear, non-linear |
| Biological Thermodynamics |
Context of living organisms, biochemisry, bioengineering, biophysics |
| Nano Thermodynamics |
Small systems, nanosize |
| Quantum Thermodynamics [8] |
Irreversible quantum mechanics and thermodynamics [9] |
Table 4:
Types of entropy [10]
| Entropy Type |
Entropy Formulated by, Year |
Entropy Expression, S |
| Equilibrium |
Clausius, 1850 |
∫δQ/T
Q=Heat transferred,
T= Temperature |
| Configurational |
Boltzmann, 1872 |
kBlnW
kB=Boltzmann’s constant
W=Thermodynamic probability |
| Statistical |
Gibbs, 1878 |
-kB∑pilnpi
pi=Probability of microstate |
| Quantum |
von Neumann, 1927 |
-kBTr(∑ρlnρ)
Tr=Trace
ρ=Density matrix of quantum mechanical system |
| Information |
Shanon, 1948 |
∑pilog(1/pi)
pi=Probability of event |
| Nonadditive |
Tsallis, 1988 |
kB/(q-1)(1-∑piq)
pi=Probability
q=Entropic index |
The research in the area of quantum thermodynamics [11] in the future also intends to unlock the secret of cell and molecular biology. Identifying the origins, modes and pathways of different transport careers are the necessary ingredients for witnessing the complete picture of the processes taking place at the cellular level of a biological species.
Synergy of mechanical engineering with biology/medicine
Mechanical engineering study relates to many of the modern biology and medicine fields as given in Table 5.
Table 5:
Relation of mechanical engineering with modern biology and medicine
| Modern Biology and Medicine |
Mechanical Engineering |
Synergised Courses |
| BioFluid Flow |
Modern/Advanced Fluid Mechanics |
1) Biological Thermodynamics, 2) Quantum Thermodynamics,
3) Mechanics and Thermodynamics of Biological Systems,
4) Advanced Applied Computational Fluid Mechanics/Dynamics
5) Python Programming Language Interface to Equilibrium, Non-Equilibrium, Statistical, Nano, Biological and Quantum Thermodynamic Simulation
|
| BioEnergetics, Molecular Machines |
Non-Equilibrium & Quantum Thermodynamics [5], Modern/Advanced Engineering Thermodynamics |
| Bio Mechanics |
Modern Mechanics |
| Bio NanoTechnology and Biological Transport |
MEMS & Micro-Nano Fluidics [5] |
| Modeling and Simulation of Biological Systems |
Computational Fluid Dynamics [5] |
Today, simulation drives medical diagnostic and treatment and has become an integral part of biology and medical science [12] with availability of heterogeneous computing hardware. Medical scientists need to develop an understanding of the underlying physics of cause to cure of human health-related problems through their research. To minimise the difference between the actual performance v/s predicted performance, it is important to know all the mechanisms of transport involved and their phenomena as already shown in Table 1.
Academic teaching/learning pedagogy with the synergised courses, as shown in Table 5, can enhance the understanding of mechanical engineering graduates inclined to pursue careers as medical scientists or those seeking alternative career opportunities.
Conclusions
A cross-disciplinary understanding of the natural machines can equally benefit the domains of engineering, modern biology and medicine, potentially leading to unlocking the secrets behind the workings of the natural world.
Author:
Auro Ashish Saha
Professor of Mechanical Engineering,
Department of Mechanical Engineering
Pondicherry Engineering College
Pondicherry - 605 014
India
Email: asaha@pec.edu
References
1. Waite, G.N. and Waite, L., 2007. Applied Molecular and Cell Biology for Engineers, McGraw-Hill, New York.
2. Gautam Biswas, et al. 2010. Profile of Engineering Education in India: Status, Concerns and Recommendations, Narosa Publishing House Pvt. Ltd., New Delhi.
3. Ekwkwe, N. and Islam, N., 2012. Disruptive Technologies, Innovation and Global Redesign: Emerging Implications, Information Science Reference, Hershey.
4. Rodrigo Soto, 2015. Kinetic Theory and Transport Phenomena, Oxford University Press, New York.
5. Auro Ashish Saha, 2017, Mechanical engineering must futureproof to maximize tomorrow’s technology,
http://www.engineersjournal.ie/2017/06/06/mechanical-engineering-futureproof-tomorrows-technology/
6. Adrian Bejan, 2016. The Physics of Life, St. Martin’s Press, New York.
7. Adrian Bejan, 2017, Evolution in thermodynamics, Applied Physics Reviews, 4, 011305.
8. W. Muschik, 2007. Why so many “schools” of thermodynamics? Forschung im Ingenieurwesen, 71, pp. 149-161.
9. Davide Castelvecchi, 2017. Battle between quantum and thermodynamic laws heats up, Nature, 543, 597-598.
10. Auro Ashish Saha, 2017, Non-equilibrium and quantum thermodynamic simulation, MEE-86. M.Tech. (ET) – II Semester, Lecture Notes, Pondicherry Engineering College, Pondicherry
11. Auro Ashish Saha, Modern Era of Quantum Thermodynamics – From Insights to Innovation and Discoveries, manuscript under preparation.
12. Saha, A. A., et al. 2013. Advanced CFD Modeling using GeForce GPUs, International Journal of Mechanical Engineering & Computer Applications, 1, pp. 61-69.