**Sensors and Biodetection**

[12] Holi JL, Hwang JN. Finite precision error analysis of neural network hardware imple-

[13] Draghici S. On the capabilities of neural networks using limited precision weights.

[14] Chen T, Du Z, Sun N, Wang J, Wu C, Chen Y, et al. DianNao: A small-footprint highthroughput accelerator for ubiquitous machine-learning. Acm Sigplan Notices. 2014;

[15] Luo T, Luo T, Liu S, He L, He L, Wang J, et al., editors. DaDianNao: A machine-learning supercomputer. In: Ieee/Acm International Symposium on Microarchitecture. 2014 [16] Suda N, Chandra V, Dasika G, Mohanty A, Ma Y, Vrudhula S, et al. Throughput-Optimized OpenCL-based FPGA Accelerator for Large-Scale Convolutional Neural Networks. In: Proceedings of the 2016 ACM/SIGDA International Symposium on Field-Programmable

[17] Hu J, Shen L, Sun G. Squeeze-and-excitation networks. Computer Science. 2017;arXiv:

[18] Desoli G, Chawla N, Boesch T, Singh SP, Guidetti E, Ambroggi FD, et al., editors. 14.1 A 2.9TOPS/W deep convolutional neural network SoC in FD-SOI 28nm for intelligent

[19] Nair V, Hinton GE, editors. Rectified linear units improve restricted boltzmann machines. In: International Conference on International Conference on Machine Learning; 2010 [20] Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image rec-

[21] Deep CNN and Weak Supervision Learning for Visual Recognition [Internet]. 2016. Available from: https://blog.heuritech.com/2016/02/29/a-brief-report-of-the-heuritech-

[22] Chen YH, Emer J, Sze V. Using dataflow to optimize energy efficiency of deep neural

[23] Alwani M, Chen H, Ferdman M, Milder P, editors. Fused-layer CNN accelerators. In: Ieee/

[24] Sze V, Chen YH, Yang TJ, Emer JS. Efficient processing of deep neural networks: A tutorial

[25] Gupta S, Agrawal A, Gopalakrishnan K, Narayanan P. Deep learning with limited numer-

[26] Qiu J, Wang J, Yao S, Guo K, Li B, Zhou E, et al., editors. Going deeper with embedded FPGA platform for convolutional neural network. In: Acm/Sigda International

[27] Li H, Fan X, Jiao L, Cao W, Zhou X, Wang L, editors. A high performance FPGA-based accelerator for large-scale convolutional neural networks. In: International Conference

Gate Arrays. Monterey, California, USA. 21 – 23 February, 2016. pp. 16-25

embedded systems. In: Solid-State Circuits Conference; 2017

ognition. Computer Science. 2014;arXiv:1409.1556

network accelerators. IEEE Micro. 2017;**37**(3):12-21

acm International Symposium on Microarchitecture; 2016

and survey. Proceedings of the IEEE. 2017;**105**(12):2295-2329

ical precision. Computer Science. 2015;arXiv:1502.02551

Symposium on Field-Programmable Gate Arrays; 2016

on Field Programmable Logic and Applications; 2016

mentations. Computers IEEE Transactions on. 1993;**42**(3):281-290

Neural Networks. 2002;**15**(3):395

**49**(4):269-284

166 Green Electronics

1709.01507

deep-learning-meetup-5/

**Chapter 9**

**Provisional chapter**

**Biomolecules and Pure Carbon Aggregates: An**

**Biomolecules and Pure Carbon Aggregates: An** 

DOI: 10.5772/intechopen.73177

"Green electronics" is a novel scientific term which aims to identify the compounds of natural origin (economically safe and biodegradable) and establish economically efficient route for production of synthetic materials. The purpose of green electronics is to create path for the production of human and environmental friendly electronics and the integration of electronics with living tissue in particular. These researches may help to fulfill not only the organic electronics to deliver low cost energy efficient materials and devices, but also achieve unimaginable functionalities for electronics. In this chapter we have considered the molecular electronic devices biomolecules: deoxyribonucleic acid (DNA) and pure carbon aggregates: (carbon nanotubes (CNTs)/graphene), their proper-

**Keywords:** biosensing, carbon nanotubes (CNTs), graphene, nucleobases, sensors

Nanobiotechnology is gaining tremendous impetus in this era due to its ability to modulate metals into their nanosize and further interaction to the biological complexes, which efficiently changes their physicochemical and optical properties. Accordingly, considerable attention is being given to the development of novel strategies for the different nanoparticles of specific composition and size using biological sources. As the currently available techniques are expensive, environmentally harmful, and inefficient with respect to materials and energy use, so the emphasis is given to design the user friendly, non-toxic complexes, which can be used in biomedical and environmental applications. The major key prerequisite for achieving sustainability in the electronics industry is the usage of materials and technologies that have

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

**Application Towards "Green Electronics"**

**Application Towards "Green Electronics"**

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.73177

Ruby Srivastava

Ruby Srivastava

**Abstract**

ties and applications.

**1. Introduction**

#### **Chapter 9 Provisional chapter**

#### **Biomolecules and Pure Carbon Aggregates: An Application Towards "Green Electronics" Biomolecules and Pure Carbon Aggregates: An Application Towards "Green Electronics"**

DOI: 10.5772/intechopen.73177

#### Ruby Srivastava Ruby Srivastava

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.73177

#### **Abstract**

"Green electronics" is a novel scientific term which aims to identify the compounds of natural origin (economically safe and biodegradable) and establish economically efficient route for production of synthetic materials. The purpose of green electronics is to create path for the production of human and environmental friendly electronics and the integration of electronics with living tissue in particular. These researches may help to fulfill not only the organic electronics to deliver low cost energy efficient materials and devices, but also achieve unimaginable functionalities for electronics. In this chapter we have considered the molecular electronic devices biomolecules: deoxyribonucleic acid (DNA) and pure carbon aggregates: (carbon nanotubes (CNTs)/graphene), their properties and applications.

**Keywords:** biosensing, carbon nanotubes (CNTs), graphene, nucleobases, sensors
