",isbn:"978-1-83968-760-0",printIsbn:"978-1-83968-759-4",pdfIsbn:"978-1-83968-761-7",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"cc49d6034d85f8f2e2890c6acc3cc629",bookSignature:"Dr. Abhijit Biswas",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10285.jpg",keywords:"Mott Insulators, Semi Metals, Polycrystals, Single Crystals, Electronic Properties, Magnetic Properties, PLD, MBE, Topological Insulators, Topological Hall Effect, Devices Applications, Catalysis",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 9th 2020",dateEndSecondStepPublish:"October 7th 2020",dateEndThirdStepPublish:"December 6th 2020",dateEndFourthStepPublish:"February 24th 2021",dateEndFifthStepPublish:"April 25th 2021",remainingDaysToSecondStep:"5 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:"A pioneering researcher in the field of tailoring metal oxide crystal surfaces and growth as well as engineering of thin films for various emergent phenomena and energy applications. Dr. Biswas received his Ph.D. from POSTECH, South Korea.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"194151",title:"Dr.",name:"Abhijit",middleName:null,surname:"Biswas",slug:"abhijit-biswas",fullName:"Abhijit Biswas",profilePictureURL:"https://mts.intechopen.com/storage/users/194151/images/system/194151.png",biography:"Dr. Abhijit Biswas is a research associate at the Indian Institute of Science Education and Research (IISER) Pune, in India. His research goal is to design and synthesize highest quality epitaxial heterostructures and superlattices, to play with their internal degrees of freedom to exploit the structure–property relationships, in order to find the next-generation multi-functional materials, in view of applications and of fundamental interest. 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Currently, he is also serving as a reviewer of several reputed peer-review journals.\nDr. Biswas received his B.Sc. in Physics from Kalyani University, followed by M.Sc in Physics (specialization in experimental condensed matter physics) from Indian Institute of Technology (IIT), Bombay. His Ph.D., also in experimental condensed matter physics, was awarded by POSTECH, South Korea for his work on the transport phenomena in perovskite oxide thin films. Before moving back to India as a national post-doctoral fellow, he was a post-doc at POSTECH working in the field of growth and characterizations of strong spin-orbit coupled metal oxide thin films.",institutionString:"Indian Institute of Science Education and Research Pune",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Indian Institute of Science Education and Research Pune",institutionURL:null,country:{name:"India"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"20",title:"Physics",slug:"physics"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"205697",firstName:"Kristina",lastName:"Kardum Cvitan",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/205697/images/5186_n.jpg",email:"kristina.k@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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1. Introduction
The dimensions of integrated circuit devices decreased in each successive technology generation. The goal of this scaling is, on the one hand, to improve the performance of integrated circuits and, on the other hand, to integrate a greater number of devices per unit area. Static random access memories (SRAMs) are not an exception to this evolution, the dimensions of the transistors forming memory cells decreased roughly following Moore\'s Law. Consequently, the area occupied by each cell decreased from generation to generation [1]. Current technological processes used to manufacture complementary metal‐oxide‐semiconductor (CMOS) SRAM memories are in the nanometer region, since the nominal characteristic dimensions of the transistors forming each cell are of the order of tens of nanometers.
The supply voltage of SRAMs has also been reduced. However, this decrease did not follow the predictions of the International Technology Roadmap for Semiconductors (ITRS), in fact, it was more moderate. This is mainly due to the limitation imposed on the transistors threshold voltage scaling to avoid an excessive increase of leakage current [2]. To meet performance demands of current electronic systems, large capacity integrated SRAMs are usually needed, and in fact, FPGA‐SRAMs are not an exception. This requirement results in a large proportion of area dedicated to SRAM memory. Forecasts indicate that in the coming years this figure may reach 90% [3]. Of course, integrating large memories has an adverse impact on circuit area, which in turn results into higher costs. For this reason, designers try to integrate the largest possible number of SRAM cells per unit area. This leads to cells designs with small sizes to squeeze the full potential of technology. SRAMs are usually designed with transistors close to the minimum possible size, and arranged with the highest possible density. In addition, to reduce power consumption, voltages are kept as low as possible. Although, as mentioned before, the expected voltage reduction have not been fully implemented in real technology.
As a result of the decrease in device dimensions and of the reduction of supply voltage in successive technology generation, designing SRAM faces two major challenges: the first one is related to the stability of the cells and second one has to do with their susceptibility to radiation‐induced transient events. This chapter focuses on the second challenge, the CMOS SRAM radiation problem. However, SRAM stability issues are also discussed.
SRAMs are one of the most sensitive to radiation parts of a circuit. They are especially sensitive to those effects caused by a single energetic particle. These effects are the so‐called single event upsets (SEUs). They are considered soft errors (SE) because they trigger an error without permanently damaging the circuit. This chapter focuses on six‐transistor (6T) CMOS SRAM SEUs and on a technique to mitigate its effects, which is easily implementable in current FPGA design workflows. The architecture of 6T RAMS cell is described in Section 2.
Regarding the process that generate SEUs, the interaction of an energetic particle creates electron‐hole pairs, so that part of this deposited electric charge can be collected by a sensitive node affecting its voltage. If this node is the node of an SRAM and the perturbation is high enough, it can flip the cell state altering data stored in it, and thus generating an error. These errors are not necessarily destructive. In particular, in an SRAM, a particle is capable of modifying data stored in one or more memory cells without damaging them. This means that cells can be rewritten and operate normally. Nevertheless, cell data has been corrupted, and if the cell is read before a new write occurs, a read error will be produced.
The problem of radiation effects in integrated circuits is not new. It has been studied and taken into account for decades by designers in areas such as the aerospace industry and, since the mid‐1990s, also by the aeronautics manufacturers [4]. This is due to the high flow of energetic particles that devices operating in these high‐altitude environments are exposed to. The atmosphere shields part of the energetic particles that come from outside the Earth, so that, the higher the altitude, the higher the particle flux. To mitigate these effects, radiation shields, redundant components, techniques of error detection and correction and radiation tolerant elements are used. The implementation of these measures ranges from technological aspects of architecture to system level. Many of these measures increase costs and negatively impact circuit performance. There exist many well‐known techniques to mitigate SEU effects, such as triple modular redundancy (TMR), which can be suitable for certain applications. However, most of them involve high penalties in terms of cost, power, or performance, which can be affordable for the space industry but could be non‐acceptable for other FPGA fields of application.
In addition, due to technology scaling, SEUs are becoming a major reliability concern for electronic devices in general and SRAMs in particular, not only in harsh radiation environments but also at ground level, where radiation fluxes are low. In the case of SRAMs, this is due to the fact that the number of errors per time unit in SRAM memories due to radiation‐induced transient events has increased with technology scaling [3, 5]. This fact has two main causes. The first cause has to do with both reducing the dimensions of the transistors forming the cells and with decreasing the supply voltage. Both factors contribute to reduce the amount of electrical charge used by a cell to store one bit of information. Thus, it is easier that the charge induced by the interaction of a particle upsets the cell content. The second cause includes three related factors: the increase in the number of cells integrating SRAMs, the higher density of cells, and the amount of chip area occupied by SRAM cells. All of them contribute to increase the probability that an energetic particle interacts with a sensitive area of a memory causing a transient event that leads to cell data corruption. In a FPGA, this can be a serious problem, since SRAM‐based FPGAs rely on SRAMs to store configuration bits. An SEU affecting one of those bits can produce an unpredictable behavior or even a complete system failure.
To conclude, SEU effects are not a new problem and the space industry has developed specialized techniques to deal with them for decades. However, FPGAs are used in a broad range of applications, and in many of them circuits are not subject to high radiation fluxes. Nevertheless, due to technology scaling, they are becoming sensitive to radiation either from the environment or from the circuit materials. For this reason, it is necessary to implement some radiation hardening techniques, especially if the circuit is operated in critical systems. Traditional aerospace techniques are not suitable for most SRAM‐based FPGA applications, since they involve high costs or significant performance degradation, which cannot be assumed. One of the most paradigmatic examples is commercial electronics or any other FPGA application field where FPGAs are attractive due to its fast time to market, flexibility, and reprogrammability, which reduce costs while keeping good performance. Thus, the aim of this chapter is to present a technique that fills this gap and can be used as a suitable technique to improve radiation reliability in a broad range of FPGA‐SRAMs applications. More specifically, the technique works at the cell design level, and its goal is to enable the design of intrinsically more robust cells. In addition, the technique is also attractive because it is compatible with current memory compilers, since it does not change SRAMs cell architecture.
2. Radiation impact on SRAMs
The analysis of radiation impact on integrated circuits is difficult and is typically performed by experimental tests or using device‐level simulations. However, the critical charge (Qcrit) is a parameter usually used as a standardized methodology to analyze the circuit‐level impact of radiation on SRAMs [6, 7]. One of the main advantages of this parameter is that it can be obtained by electrical simulations, which are cheaper than experimentation and less time consuming than device‐level simulations. In addition, it helps to understand how SEUs are produced.
When an energetic particle impacts a CMOS circuit substrate, it induces a charge track due to electron‐hole pair generation. This deposited charge can be collected by a sensitive node—typically the drain of an off transistor—which is near to the ionization track [4]. This results in a transient current pulse at the node. A sufficiently strong current pulse will modify data stored in the cell (cell flip). If this occurs, an SEU is produced. The word “Single” means that the cell upset is caused by a single energetic particle. The parameter used to quantify the minimum amount of charge collected by a memory element node that changes its state is the critical charge. Typically, Qcrit is determined by electrical simulation analyzing how a given memory cell flips under current pulses having different shapes and intensities. It has been reported that energetic particle strikes lead to current transients with varying pulse durations (pulse width), and that the Qcrit value of a node is a function of the waveform shape [8, 9]. For this reason, a proper choice of current waveforms to estimate the critical charge is important. In this chapter, we will use the well‐known double‐exponential current source model given by
i(t)=i0(e−t−t0τ1−e−t−t0τ2)E1
where i(t) is the current intensity at time t, i0 is a parameter that scales the current intensity, τ1 determines the current fall‐time, τ2 its rise time, and t0 is the time at which the current peak is initiated. The total charge injected in the node is the area under the i(t) curve. The shape of one of these curves is represented in Figure 1.
Figure 1.
Example of a double exponential current pulse.
Figure 2 depicts a 6‐transistor SRAM (6T‐SRAM) cell configuration. It has two cross‐coupled inverters which form the two internal cell nodes (LN and RN). In addition, it has two access transistors, which are used to reach the internal nodes from outside the cell in the read and write operations.
Figure 2.
6T‐SRAM cell schematic.
Figure 3 shows the current sources scheme used to simulate SEUs. In particular, it is necessary to investigate two types of SEUs: a 0‐to‐1 SEU, where the impacted node is at 0 level, and a 1‐to‐0 SEU, where the impacted node is at 1 level. Due to cell symmetry, only two configurations cover all possibilities of memory cell perturbation. Figure 3 also shows that a charge injection on a node which is at 0 requires the nMOS transistor to drain the collected charge due to the particle hit. Conversely, when a particle hits a node which is at 1, the pMOS transistor maintains the stored value by providing the current needed to hold the node electrical value.
Figure 3.
6T‐SRAM cell schematics for simulating a 1 to 0 SEU (left) and a 0 to 1 SEU (right).
This chapter deals only with 6T SRAM cells, although there are other SRAM which are specially designed to deal with radiation issues. In general, they are hardened SRAM cells that maintain their stored data even if the electrical state of some of their nodes is flipped by a particle strike, some of them are described in [10, 11]. The main drawbacks of them are the increase in cell transistor count with the consequent area increase. In addition, in these cells, it is difficult to implement regular cell layouts, which, as it will be described in Section 3, is a useful method for parameter variation minimization. Furthermore, nonstandard cells complicate the possibility to include them in current SRAM and FPGA design flows. Conversely, the technique that will be described in Section 3 is fully compatible with SRAM memory compilers and easily adaptable to current FPGA designs. Other mitigation techniques, such as supply voltage increase [9], are not suitable to be implemented in many applications due to their impact on power consumption and long‐term reliability.
Memories are usually structures in which the maximum density of integration is requested. Therefore, the transistors forming memory cells are usually close to the minimum dimensions enabled by technology. Nevertheless, this section describes how it is possible to achieve more robust SRAM cells by varying the channel width of some of the cell transistors. This technique has a clear impact on the area occupied by each cell and, therefore, in the total memory area. For this reason, we will study how to use the area increase in the most efficient way, that is, how to get some gain in critical charge with minimum additional area. Moreover, the impact of this technique in terms of power consumption, stability, and access time is characterized in Section. 4.4.
Designing SRAMs is a challenge as technology scales down mainly due to parameter variations. There are two main causes of mismatch between the cell cross‐coupled inverters: polysilicon and diffusion critical dimensions, as well as implant variations [12]. The use of subwavelength lithography and reactive ion etching are two of the main causes that converts the drawn polygon corners on the layout mask into rounded shapes on the manufactured circuits. Although proper optical proximity corrections can minimize those distortions, these techniques alone cannot compensate all the distortions, especially as the lithography gap is increasing with each successive technology node [12]. As a result, traditional cell designs are very sensitive to misalignment because they include transistor diffusion width changes. These changes in width produce bends and steps in the diffusion regions, which in turn, cause small variations of the poly placement that lead to significant poly‐diffusion overlay misalignment. This variability impacts directly on transistor matching, which can compromise cell stability and functionality.
The so‐called regular cell layouts (Figure 4) have shown to be more tolerant to parameter variations due to several factors: all poly lines are drawn in the same direction, poly lines are aligned facilitating better polysilicon critical dimension control, and helping phase shift masking techniques [13]. In addition, when a cell is inside the SRAM array, all transistors see the same polysilicon patterns, thus minimizing poly proximity issues [12]. Finally, regular cells have straight diffusions and, therefore, are much less sensitive to misalignments [14, 15].
Figure 4.
6‐T SRAM regular layout.
Parameter variation has become a key factor in SRAM memory design. For this reason, the regular layout is the one that is considered in this chapter. Using regular layouts imposes geometrical restrictions, for example, as previously mentioned, it is necessary to orientate all polysilicon lines in the same direction and keep them aligned. However, the determining factor that mainly affects the transistor channel width modulation technique is the impossibility to introduce steps and bends in the diffusion areas. This means that the designer will be unable to freely change SRAM transistors channel widths.
The formation of bends in the diffusion regions of a cell, like the one considered in Figure 4, can be avoided if all nMOS transistors channel width (Wn) is the same, as well as all pMOS transistors channel width (Wp) is also the same. In Figure 4, it can be seen that this way the diffusion areas (colored in green) remain straight. If we consider as a reference a cell where channel width of all transistors is the minimum (Wmin), the restriction is expressed as
Wn=rn·WminWp=rp·WminE2
With these two restrictions, the nMOS channel width can vary independently from the pMOS channel width. This implies that the designer has two degrees of freedom.
3.1. Critical charge results
As it was mentioned before, the behavior of the cell undergoing a current injection due to an energetic particle impact depends on the duration of the pulse (pulse width); for this reason, it is interesting to use it as a parameter to explore.
Pulse widths of current transients are highly variable and depend on multiple parameters, but several studies show that they are between a few picoseconds and hundreds of picoseconds [6]. 3D simulations also show that short pulses correspond to ionization events whose track crosses the drain of a cut‐off transistor, while long ones are the result of events whose track does not pass through the drain [9]. It is necessary to consider both cases, since the location of the trace ionization with respect to drain is a random parameter. For this reason, to characterize the behavior of the cell, simulations with pulse widths ranging between 20 and 200 ps have been performed.
In addition, there are two different critical charges depending on which node (the one at 0 or the one at 1) receives the collected charge modeled by the current injection. The collection of electrons by the drain junction of an nMOS in OFF state results in a current pulse that upsets the affected node from 1 to 0, so this critical charge is named Qcrit,e. Similarly, the collection of holes by a pMOS drain junction upsets the affected node from 0 to 1, so this critical charge is called Qcrit,h. If both critical charges are represented as a function of pulse width, Figure 5 is obtained.
Figure 5.
Critical charge for electrons and holes of a minimum‐sized 6T‐SRAM (rn = rp = 1) as a function of pulse width.
It can be observed that Qcrit,e is lower than Qcrit,h. Therefore, it is normally considered that the cell‐flip process is dominated by Qcrit,e, and sometimes Qcrit,h is neglected. However, accurate models need to include both critical charges, as it will be shown in Section 4.4.
In addition, critical charges for a 6T cell for various combinations of Wp, Wn were calculated. Figure 6 shows the results in a graph where the independent variables are rp, rn. Results are shown for two different pulse widths and only for Qcrit,e, since Qcrit,h show similar results.
Figure 6.
Critical charge (Qcrit,e) as a function of rn and rp and for two different pulse widths.
Figure 6 shows how the cell is more robust as the transistors channel width is increased. However, increasing the channel width of transistors produces a clear and undesired impact on the area of each cell and, therefore, on the total memory area. For this reason, it is necessary to establish a trade‐off between the increased radiation robustness and the additional area used. Moreover, it is convenient to use the additional area in the most efficient possible way. This is discussed in the following subsection.
It has also been studied how the supply voltage affects cell robustness. Figure 7 shows the results of critical charge for a typical alpha‐particle pulse width of 30 ps [6] as a function of rp, rn for two different supply voltages.
Figure 7.
Critical charge (Qcrit,e) as a function of rn and rp and for two different supply voltages and for a 30 ps pulse width.
As it can be observed, a decrease in the supply voltage causes a reduction in the critical charge for all combinations of transistors channel widths. This result is in line with the previously mentioned fact that a cell with reduced voltage supply uses less charge to store data and, therefore, it is easier to change its stored value.
3.2. Additional area optimization to harden the SRAM cell
Due to the almost linear behavior of the graph in Figure 6, the following coefficients can be defined and are virtually independent of Wp and Wn:
χp=∂Qcrit∂Wpχn=∂Qcrit∂WnE3
These two coefficients represent the efficiency, in terms of critical charge, of a certain increase in the transistors channel width (pMOS in the case of χp, and nMOS in the case of χn).Geometrically, these coefficients represent the slopes in the two horizontal directions of the planes of Figure 6. These slopes vary as a function of the different pulse widths; therefore, coefficients are a function of the considered pulse width. If this dependence is plotted, Figure 8 is obtained.
Figure 8.
Dependence of χp,e and χn,e with pulse width for nominal supply voltage (1.2 V).
Figure 8 shows that, in general, χp is larger than χn, only for very short pulses χn tends to equal or even exceed the value of χp. This means that for pulses longer than about 10 ps, increasing only pMOS transistors width (Wp) is more efficient than increasing nMOS transistors (Wn). As it has been mentioned before, the widths of the current pulses generated by SEU vary. However, for alpha particles, a typical pulse width is about 30 ps [6]. For this typical pulse width, increasing Wp is more efficient than increasing Wn.
Same simulations were repeated for 0.8 V supply voltage, the results are shown in Figure 9.
Figure 9.
Dependence of χp,e and χn,e with pulse width for 0.8 V supply voltage.
The results obtained are analogous to those of Figure 8. However, the values of χp and χn at 0.8 V are lower than at 1.2 V (note that the graphs in Figures 8 and 9 are represented at the same scale). This means that reducing the supply voltage not only reduces the critical charge but also reduces the efficiency in terms of critical charge to make wider pMOS transistors.
Finally, Figure 10 plots χp as a function of the pulse width and supply voltage in a surface plot and as a family of curves generated by the supply voltage parameter.
Figure 10.
Dependence of χp,e with pulse width and supply voltage.
The graph in Figure 10 shows that reducing both the supply voltage and the pulse width decreases the efficiency, in terms of critical charge, of modulating the pMOS transistors channel width.
From all the results presented in this section, it can be deduced that if the SEU robustness of an SRAM cell is to be increased in a certain percentage, increasing the widths of only the pMOS and leaving the nMOS unmodified is more efficient than any other combination of transistor width modulation. Or, for a given percentage area budget, increasing only pMOS widths maximizes critical charge.
Table 1 shows the critical charges for a pulse of 30 ps for three values rp (and rn = 1) at nominal voltage. In addition, it shows the increased area with respect to the minimum sized cell (rp = 1, rn = 1). Areas are obtained by designing cells with the regular layout features and restrictions described earlier.
rp
Wp (µm)
Qcrit,e (fC)
Qcrit,e increment with respect to minimum cell (%)
Area increment with respect to minimum cell (%)
1.0
0.15
1.72
0
0
1.5
0.23
2.14
24
9
2.0
0.30
2.51
46
17
Table 1.
Critical charge and cell area increment for three different values of rp, and rn = 1 (Wmin = 0.15 μm). The supply voltage is nominal.
Table 1 shows that, for example, for an area increase of 17%, an increment 46% in critical charge is achieved.
To sum up, the transistors channel width modulation technique has shown by simulation to be effective in terms of improving critical charge. For this reason, it was decided to implement and test this technique in a real memory prototype (test chip) described in Section 4.1.
4. Experimental results of the modulation technique
4.1. Test chip description
The transistor width modulation technique was implemented in a custom fabricated SRAM test chip in a 65‐nm CMOS commercial technology. Memory cells are six‐transistor (6T) cells and were implemented following regular layout design specifications to minimize parameter variations. The regular layout characteristics were described in Section 3, and include the use of straight diffusion regions and regular alignment of word line polysilicon lines.
From all the previously simulated cells, five of them were implemented in the test chip (five different combinations of transistors channel widths). All these combinations satisfy the restrictions imposed for a regular layout. The selected combinations (cell types) of rn and rp are schematized in Figure 11 and detailed in Table 2. For each one of the five cell types, a total of 4096 cells were implemented. Finally, the test chip was irradiated following the procedure detailed in Section 4.2 to experimentally test the modulation technique.
Figure 11.
Schematic representation of the five cell types implemented in the test chip.
Cell type
pMOS width, Wp (µm)
nMOS width, Wn (µm)
Cell height (µm)
Cell width (µm)
Cell area (µm2)
Cell area increment with respect to A (%)
A
0.15
0.15
0.58
1.75
1.01
0
B
0.23
0.15
0.58
1.91
1.10
9
C
0.30
0.15
0.58
2.05
1.18
17
D
0.23
0.23
0.58
2.07
1.19
18
E
0.15
0.30
0.58
2.05
1.18
17
Table 2.
Main geometric features of the five cell types implemented in the test chip.
4.2. Experimental irradiation procedure
The objective of the experiment is to obtain the soft error rate (SER) of each one of the five cell types, that is, the number of soft errors (SEUs) for time unit.
The 65‐nm CMOS test chip was mounted on a specifically designed PCB and controlled by an FPGA to drive and capture data.
As a radiation source, it was used an Am‐241 alpha source with a 5 kBq activity providing alpha particles of 5.5 MeV. The source active area was 7 mm in diameter and was placed atop the unencapsulated chip, and all five cell types were irradiated at the same time. The control FPGA was not irradiated because the objective of the experiment was only to study the behavior of the test chip SRAM cells under radiation conditions.
The test procedure was performed following the subsequent steps:
Write all memory cells to a known value.
Read all memory cells, and compare to the written values.
Initiate the memory radiation.
Wait for a sampling time Ts.
Read the whole memory and determine the number of cells whose state changed. Go to Step 4.
Steps 4–5 were cycled until the experiment was finished. The overall number of SEUs, NTOT, is given by the addition of the number of SEUs recorded at each sampling period (Ni), i.e.
NTOT=∑i=1nNiE4
with n being the number of times that the memory is read. The overall time experiment (texp) is given by texp=nTs. The SER at each sampling time period (SERi) is given by SERi=Ni/Ts, while the mean SER of the overall experiment is given by
SER=∑i=1nSERin=∑i=1nNin·Ts=NTOTtexpE5
The determination of the sampling period Ts is important, since it must guarantee that the probability of a given cell to experience two or more flips within the same sampling period is negligible, while keeping the overall read time small with respect to the overall hold time (we are interested in computing the memory SER when the memory is not being accessed) [16]. We ran an initial experiment using a small one‐minute Ts value and determined an SER order of magnitude of 1 SEU/minute. Based on this, we set a Ts value of 30 min to not increase the memory read rate. The mean estimated SEU error using this Ts value is 1‰.
4.3. Experimental results
The experiment was conducted under the conditions and procedure described in Section 4.2 for a total time of 72 h to accumulate enough SEUs as to obtain a reliable SER result.
The SEU count evolution is shown in Figure 12. As expected, results show that the accumulated SEU count with time is linear. An alternative way to calculate SER is by obtaining the slope of the plot of accumulated number of SEU as a function of time.
Figure 12.
Accumulated SEUs in a 72 h period irradiation for the five cell types.
The first important result from Figure 12 is that different memory cell types have different SER values (i.e., different slopes). If each SER is computed and represented in a bar plot, Figure 13 is obtained.
Figure 13.
SER of 4096 cells for each one of the five cell types.
In addition, SER values are tabulated in Table 3 along with critical charge results. Keep in mind that a more robust cell means more critical charge but less SER.
Cell type
SER (s−1 × 10−3)
Qcrit,e (fC)
C
3.87
2.51
B
4.60
2.14
D
5.24
2.44
A
5.68
1.72
E
8.30
2.26
Table 3.
SER and critical charge values for the five different cell types (sorted by SER value).
From Figure 13 and Table 3, it is observed that the stronger cell—from a SER point of view—is the C, followed by B, and that the less robust is E. In addition, if critical charge is also taken into account, the following can be observed:
The best cell is C; note that this occurs from both critical charge and SER points of view.
Increasing the pMOS transistors channel widths (cells A, B, and C) causes an increase in critical charge, which directly results into a decrease in SER. That is, cell C is more robust than B, and B more robust than A, from both from critical charge and SER point of view.
There is no the same direct correlation when cells in which nMOS transistors have been modified are involved. Cells D and E are among the most robust ones in terms of critical charge, and yet are among the ones that show worst SER.
In Section 3.2, it was justified that increasing pMOS transistor widths was, from a critical charge point of view, the most efficient way to use the additional area. Cells B and C are the ones in which only pMOS transistor width is increased. From these results, it can be concluded that, in terms of SER, increasing only the pMOS transistors width is also the best way to improve SRAM cells robustness.
In short, increasing the pMOS transistors channel width improves critical charge and SER. However, increasing the nMOS transistors channel width improves critical charge, but worsens SER. The reason for this nonsymmetrical behavior must be sought in the fact that increasing critical charge by widening the channel of the transistors has a dual effect on SER:
It increments cell robustness, because more charge is needed to flip the cell (higher critical charge).
It lowers cell robustness because a wider transistors channel involves a sensitive area increase, which may also involve an increase in the ability of the cell nodes to collect the charge that has been deposited by an impacting energetic particle.
The key point is that the relative contribution of these two factors (critical charge and area increase) is not the same in the case of widening nMOS and pMOS transistors. Increasing the channel size of pMOS implies an area increase inside the well, while increasing the channel size of nMOS increases the area directly on the substrate. The different ability to collect charge of pMOS (in the well) or nMOS (on the substrate) is the qualitative explanation of the observed relation between SER and critical charge for nMOS and pMOS width modulation. This behavior is quantitatively explained in the following section.
4.4. Analysis of the results
Experimental data show that maintaining minimum nMOS transistors width (rn = 1) while increasing pMOS transistor channel widths improves both critical charge and SER for a 6T memory cell. However, increasing nMOS transistor channel width improves memory cell critical charge, but worsens SER. As it has been mentioned before, this can be qualitatively explained as follows: Increasing transistor width has two competing effects on SER. On the one hand, SEUs are more difficult to occur, because Qcrit is raised due to the increase of both the drain capacity and the transistor width, which enhances transistor strength. On the other hand, widening a transistor increases its sensitive area, raising the probability of the cell to collect charge and thus be flipped by the effect of an energetic particle. The relative contribution of these two opposite effects on SER depends on the transistor type (nMOS or pMOS), especially for CMOS bulk technologies with well areas for pMOS transistors [17].
To model these two effects, it is necessary to use an expression that relates SER and critical charge. The following expression [18] will be used:
SER=κ(Adiff,n·e−Qcrit,eηe+Adiff,p·e−Qcrit,hηh)E6
where Adiff,n and Adiff,p are the nMOS and pMOS sensitive drain area. Qcrit,e and Qcrit,h are respectively the critical charges due to the collection of electrons and holes, and κ is a parameter that depends on the radiation flux. Parameters ηe and ηh represent electron and hole charge collection efficiency. To compute SER, parameters κ, ηe, and ηh need to be experimentally obtained, as they depend on the environment and on the device precise characteristics. Note that the model includes both critical charges (Qcrit,e and Qcrit,h) introduced in Section 3.1.
In our case, since we obtained SER and critical charge for different cell types, we can fit SER experimental data to the calculated critical charge values and obtain the unknown parameters κ, ηe, and ηh. Diffusion areas can be expressed as Adiff,n=Wn·Hn, and Adiff,p=Wp·Hp, being Hn and Hp the diffusion lengths of the drains of the nMOS and pMOS transistors. The design rules restrictions for symmetrical and regular cell layout impose Hn to be slightly longer than Hp (in fact we used the minimum possible diffusion length in the pMOS transistor, Hp=Hmin, while Hn=Kdiff·Hmin with Kdiff = 1.1 for the five different cells). Introducing again rn and rp coefficients defined in Eq. (2) we obtain:
The values of SER, Qcrit,e, Qcrit,h, rn, rp, and Kdiff in Eq. (8) are known and, therefore, KA, ηe and ηh remain as fitting parameters, being KA the product of κ and Amin, diff. The obtained values after the fitting for these parameters are: KA = 3.13 × 10−6 s−1, ηe = 2.02 fC, and ηh = 0.79 fC.
Figure 14 compares the experimental and fitted SER. As it can be seen, Eq. (8) accurately describes the experimental SER as a function of critical charge and geometrical parameters. In addition, the model properly describes quantitatively the asymmetrical influence of nMOS and pMOS transistor width in terms of SER, which was previously interpreted qualitatively.
Figure 14.
SER (experimental and modeled) of 4096 cells for each one of the five cell types.
The experimentally fitted parameters and the resulting critical charge values from Eq. (8) allow to plot SER as a function of rn and rp. The resulting surface is shown in Figure 15.
Figure 15.
SER as a function of rn and rp.
Results of Figure 15 confirm that increasing rp leads to a SER reduction, whereas increasing rn produces an undesired SER increment. This SER surface can be compared to the critical charge surface of Figure 6, where critical charge was improved as both rn and rp were increased.
If the charge collection efficiency values obtained as fitting parameters are analyzed, it is confirmed that charge collection efficiency for electrons (ηe) is higher than for holes (ηh) [19]. In addition, critical charge for electrons (Qcrit,e) is smaller than for holes (Qcrit,h). This electron and hole asymmetry in terms of charge collection efficiency and in terms of critical charge is the root cause of the observed differences of SER dependency with rn and rp.
Usual 6T‐cells are designed with minimum sized access transistors (Wacc=Wmin), minimum sized pMOS (Wp=Wmin), and non‐minimum‐sized nMOS (Wn=CR·Wmin). The CR parameter is called cell ratio and is usually greater than 1, being the most frequent values between 1.5 and 2.5 as a trade‐off to assure cell stability during write and read operations [3]. Note that this cell with this transistor dimensions does not have straight diffusions. In addition, also note that this cell has the internal latch (cross coupled inverters) equal to the ones in E cell.
From the irradiation experiments, it has been obtained that the C cell shows an SER that is a 46% of the E cell SER, that is, C cell receives less than half the number of SEUs per time unit than E cell. Note that this improvement is achieved only by adequate transistor sizing, because both cells (C and E) have the same area. If instead of considering this two cells, we compare the C cell with respect to a usual cell with CR = 2, then the SER of the C cell is a 57% the SER of the CR = 2 cell.
The effects of the transistor width modulation technique on power consumption and access time are summarized in Table 4. For example, it can be observed that C and E cells show similar access times and power consumption levels (although there is an increase of the energy needed to change the logic state of the C cell, it presents lower leakage current than the E cell).
Cell type
Leakage (pW/cell)
Write energy (fJ/cell)
Write time (ns)
Read time (ns)
RSNM (mV)
WSNM (mV)
A
125.5
4.65
0.32
0.28
168
468
B
134.2
5.93
0.33
0.28
178
429
C
144.1
7.10
0.35
0.28
184
346
D
163.8
6.45
0.36
0.27
165
468
E
180.6
5.59
0.36
0.26
149
517
Table 4.
Summary of different power, speed and stability figures of the fife different cell types.
Finally, it was also analyzed how the modulation technique affects read and write stability, by computing two well‐known parameters: read static noise margin (RSNM) and write static noise margin (WSNM). As it can be seen in Table 4, RSNM is not very affected. Despite that, in [20], a technique to recover the RSNM of a 6T cell is analyzed. In addition, WSNM is degraded in some cell types (the ones in which pMOS transistors are increased in size). To overcome that, if needed, there are write assist techniques that could be suitable to improve WSNM [21, 22]. However, all tested cells types are experimentally writable with no write assist technique applied.
5. Conclusions
Due to technology scaling, radiation effects have become a major concern for modern integrated circuits even at ground level. FPGA SRAMS are not an exception, and radiation effects are even maximized, because these circuits are usually designed with transistors sizes close to the minimum allowed by technology. The so‐called SEUs are the main radiation issue for SRAMs. SEUs are capable of altering the memory content of SRAM cells without permanently damaging the circuit.
A technique based on transistor width modulation was developed and tested. The technique consists in modifying the cell transistors channel width in a way that is compatible with the so‐called regular layouts (i.e. avoiding the formation of bends in the diffusion regions). The main advantage of this layout scheme is that it reduces parameter variation. Nevertheless, it imposes some geometrical restrictions over transistor sizes, so that the modulation technique has to be designed to meet those constraints.
The technique was implemented and tested using two approaches: critical charge and experimental SER. Critical charge is a parameter cheap and easy to obtain, because it can be calculated using electrical simulations. However, as it was shown, it does not give a directly accurate measurement of the robustness of an SRAM cell if transistor areas are modified. Conversely, SER is a better parameter to assess cell robustness. The main drawback of SER is that it can only be directly obtained with experimental measurements, which are expensive and time consuming. After a preliminary analysis, the most interesting transistor size combinations where selected and implemented in a custom‐fabricated test chip. The test chip has 4096 cells of each one of the five selected cells types, and all of them where irradiated with alpha particles to experimentally obtain SER.
Results show that some of the cell types are much more robust to radiation than others. In addition, results also reveal that, while a larger critical charge can lead to a better SER, some memory cells with higher critical charge also exhibit worst SER. This behavior was found when increasing nMOS channel widths. This suggests that special care must be taken when comparing SRAM cells with different transistor areas using critical charge as a figure of merit. Despite that, results indicate that SER can be estimated from critical charge with a model if some cell intrinsic cell parameters are known.
Results also show that SER is improved by increasing the pMOS transistors channel width (Wp), and worsened when the nMOS transistors channel width is increased (Wn). For this reason, the best way to design a hardened 6T SRAM cell is by minimizing the nMOS transistors channel width and dedicating all additional area to increase pMOS transistor channel width. In addition, for a 65‐nm CMOS commercial technology, SER was reduced to a 57% of the value that conventional nonstructured layout cells exhibit. Due to careful transistor sizing, this radiation robustness improvement was achieved with minor area penalty. However, this hardened cells with wider pMOS transistors, also show a reduction in cell writability. To overcome this issue, write assist techniques can be implemented. Nevertheless, if a trade‐off between writability, area, and radiation robustness is achieved by proper transistor sizing, hardened cells remain writable without any further action. Finally, with the modulation technique presented in this chapter, the achieved cell radiation robustness gain is fundamentally an area trade‐off, provided that the cell remains writable. For this reason, at design level, radiation robustness can be set as an adjustable parameter in memory compilers.
Acknowledgments
This work has been supported by the European FEDER fund and the Spanish Ministry of Science and Innovation under Grant no. AP2006‐03170 and TEC2008‐04501 and TEC2011‐25017 projects. It has also received funding to support competitive research groups from the Balearic Government (2011–2013), financed jointly by FEDER fund.
In addition, I want to sincerely thank all the members of the Electronics Systems Group (GSE‐UIB) of the University of the Balearic Islands who have contributed to this research.
\n',keywords:"SRAM, FPGA, Radiation, single event upset, hardening",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/53004.pdf",chapterXML:"https://mts.intechopen.com/source/xml/53004.xml",downloadPdfUrl:"/chapter/pdf-download/53004",previewPdfUrl:"/chapter/pdf-preview/53004",totalDownloads:3099,totalViews:289,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,dateSubmitted:"June 9th 2016",dateReviewed:"October 6th 2016",datePrePublished:null,datePublished:"May 31st 2017",dateFinished:null,readingETA:"0",abstract:"Due to integrated circuit technology scaling, a type of radiation effects called single event upsets (SEUs) has become a major concern for static random access memories (SRAMs) and thus for SRAM‐based field programmable gate arrays (FPGAs). These radiation effects are characterized by altering data stored in SRAM cells without permanently damaging them. However, SEUs can lead to unpredictable behavior in SRAM‐based FPGAs. A new hardening technique compatible with the current FPGA design workflows is presented. The technique works at the cell design level, and it is based on the modulation of cell transistor channel width. Experimental results show that to properly harden an SRAM cell, only some transistors have to be increased in size, while others need to be minimum sized. So, with this technique, area can be used in the most efficient way to harden SRAMs against radiation. Experimental results on a 65‐nm complementary metal‐oxide‐semiconductor (CMOS) SRAM demonstrate that the number of SEU events can be roughly reduced to 50% with adequate transitory sizing, while area is kept constant or slightly increased.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/53004",risUrl:"/chapter/ris/53004",book:{slug:"field-programmable-gate-array"},signatures:"Gabriel Torrens",authors:[{id:"193438",title:"Dr.",name:"Gabriel",middleName:null,surname:"Torrens",fullName:"Gabriel Torrens",slug:"gabriel-torrens",email:"gabriel.torrens@uib.es",position:null,institution:{name:"University of the Balearic Islands",institutionURL:null,country:{name:"Spain"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Radiation impact on SRAMs",level:"1"},{id:"sec_3",title:"3. SRAM cell transistors channel width modulation technique",level:"1"},{id:"sec_3_2",title:"3.1. Critical charge results",level:"2"},{id:"sec_4_2",title:"3.2. Additional area optimization to harden the SRAM cell",level:"2"},{id:"sec_6",title:"4. Experimental results of the modulation technique",level:"1"},{id:"sec_6_2",title:"4.1. Test chip description",level:"2"},{id:"sec_7_2",title:"4.2. Experimental irradiation procedure",level:"2"},{id:"sec_8_2",title:"4.3. Experimental results",level:"2"},{id:"sec_9_2",title:"4.4. Analysis of the results",level:"2"},{id:"sec_11",title:"5. Conclusions",level:"1"},{id:"sec_12",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Yamauchi, H. Embedded Memories for Nano-Scale VLSIs. Aurburn: Springer Publishing Company; 2009.'},{id:"B2",body:'Yamauchi, H. Embedded SRAM circuit design technologies for a 45nm and beyond. In: 7th International Conference on ASIC; Guilin. IEEE Press; 2007. p. 1028–1033.'},{id:"B3",body:'Pavlov, A.; Sachdev, M. CMOS SRAM Circuit Design and Parametric Test in Nano-Scaled Technologies: Process-Aware SRAM Design and Test. Auburn: Springer Publishing Company; 2008.'},{id:"B4",body:'Normand, E. Single Event Effects in Avionics and on the Ground. International Journal of High Speed Electronics and Systems. 2004;14(2): 285–298.'},{id:"B5",body:'Baumann, R. C. Soft errors in advanced semiconductor devices-part I: the three radiation sources. IEEE Transactions on Device and Materials Reliability. 2001;1(1):17–22.'},{id:"B6",body:'S. V. Walstra, C. Dai. Circuit-Level Modeling of Soft Errors in Integrated Circuits. IEEE Transactions on Device and Materials Reliability. 2005;5(3):358–364.'},{id:"B7",body:'N. Seifert, P. Slankart, M. Kirsh, B. Narasinham, V. Zia, C. Brookseron, A. Vo, S. Mitra, B. Gill, J. Maiz. Radiation-Induced Soft Error Rates of Advanced CMOS Bulk Devices. In: IEEE Int. Reliability physics symposium; 2006. p. 217–224.'},{id:"B8",body:'P. Jain, V. Zhu.. Judicious Choice of Waveform Parameters and Accurate Estimation of Critical Charge for Logic SER. In: International. Conference on Dependable Systems and Networks.; Edinburgh, UK. IEEE/IFIP; 2007.'},{id:"B9",body:'T. Heijmen.. Factors that Impact the Critical Charge of Memory Elements. In: IOLTS 2006 Proceedings; Como, Italy. IEEE Computer Society; 2006. p. 6.'},{id:"B10",body:'M. Nicolaidis. Design for soft error mitigation. IEEE Trans. on Device and Materials Reliability. 2005;5(3):405–418.'},{id:"B11",body:'Z. Liu, V. Kursun. Characterization of a Novel Nine-Transistor SRAM Cell. IEEE Trans. On VLSI systems. 2008;16(40):488–492.'},{id:"B12",body:'Ban P. Wong, Anurag Mittal, Yu Cao, and Greg Starr. Nano-CMOS Circuit and Physical Design. Hoboken, New Jersey: John Wiley … Sons; 2005.'},{id:"B13",body:'K. Osada. Universal-Vdd 0.65-2.0 V 32 kB cache using voltage-adapted timing-generation scheme and a lithographical-symmetric cell. In: IEEE International Solid-State Circuits Conference; 2001. p. 168–169.'},{id:"B14",body:'F. Hamzaoglu, K. Zhang, Y. Wang, H.J. Ahn, U. Bhattacharya, Z. Chen, Y.-G. Ng, A. Pavlov, K. Smits, M. Bohr. A 3.8 GHz 153 Mb SRAM Design With Dynamic Stability Enhancement and Leakage Reduction in 45 nm High-k Metal Gate CMOS Technology. IEEE Journal of Solid-State Circuits. 2009;44(1):148 - 154.'},{id:"B15",body:'M. Yamaoka, K. Osada, K. Ishibashi. 0.4-V Logic Library Friendly SRAM Array Using Rectangular Diffusion Cell and Delta-Boosted-Array-Voltage Scheme. IEEE Journal of Solid-State Circuits. 2004;39(6):934–940.'},{id:"B16",body:'N. Seifert ; P. Slankard ; M. Kirsch ; A. Vo ; S. Mitra ; B. Gill ; J. Maiz. Radiation-Induced Soft Error Rates of Advanced CMOS Bulk Devices. In: IEEE International Reliability Physics Symposium Proceedings; San Jose, CA. IEEE Electron Device Society; 2006. p. 217–225.'},{id:"B17",body:'D. E. Fulkerson. An Engineering Model for Single-Event Effects and Soft Error Rates in Bulk CMOS. IEEE Transactions on Nuclear Science. 2011;58(2):506–515.'},{id:"B18",body:'T. Heijmen, P. Roche, G. Gasiot, K.R. Forbes, and D. Giot. A comprehensive study on the soft-error rate of flip-flops from 90-nm production libraries. IEEE Transactions on Device and Materials Reliability. 2007;7(1):84–96.'},{id:"B19",body:'P. Hazucha, and C. Svensson. Impact of CMOS technology scaling on the atmospheric neutron soft error rate. IEEE Transaction on Nuclear Science. 2000;47(6):2586–2594.'},{id:"B20",body:'S. Keshavarapu, S. Jain and M. Pattanaik. A New Assist Technique to Enhance the Read and Write Margins of Low Voltage SRAM Cell. In: International Symposium on Electronic System Design (ISED); Kolkata. IEEE Computer Society Conference Publishing Services (CPS); 2012. p. 97–101.'},{id:"B21",body:'R. Gupta, V. Gadi, H. A. Upendar. Write Assist Scheme to Enhance SRAM Cell Reliability Using Voltage Sensing Technique. In: International Conference on Embedded Systems; 2016. p. 318–322.'},{id:"B22",body:'S. Keshavarapu, S. Jain and M. Pattanaik. A New Assist Technique to Enhance the Read and Write Margins of Low Voltage SRAM Cell. In: International Symposium on Electronic System Design; 2012. p. 97–101.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Gabriel Torrens",address:"gabriel.torrens@uib.edu",affiliation:'
University of the Balearic Islands, Palma de Mallorca, Spain
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1. Introduction
“Leadership is not only about individuals, but also about teams” [1].
Nowadays, leadership in health services is an important issue that aims to protect and improve human health. Rapid changes and developments in the health sector increase the importance of developing managership and leadership skills for health managers [2]. Regional and national health systems tend to redesign their functions and priorities by making structural changes in social and economic terms to cope with the increasing health problems [3]. The inclusion of complex technology and intense human relations in hospital services, which constitute a significant part of health care services, leads to the emergence of important managerial problems [4]. The existence of effective, creative, visionary, motivated, knowledgeable, principled leaders for the development of the institution is important to eliminate various problems in health services. To be able to do this, it is necessary to determine the qualifications that can contribute to the effective leadership of corporate managers [2, 5].
Leadership in health services is of great importance in terms of following innovations and adapting to existing situations [6]. Leadership can be defined as a multidimensional process, which means that a person motivates others to direct their activities and develop their skills under certain circumstances [3, 7]. The leader is the person who sets the goals of his group and who influences and directs the members of the group in line with these goals [8]. In addition, a good leader must be dynamic, passionate, have a motivational effect on other people, be solution oriented, and try to inspire others. Nurses, who work together with other health personnel in hospitals, constitute an important group in leadership. Nursing, which is a key force for patient safety and safe care, is a human-centered profession, and therefore leadership is a key skill for nurses at all levels. The leadership styles of nurse managers are believed to be an important determinant of job satisfaction and job commitment of nurses. Nurses who are mobilized and empowered to perform specific personal or group goals by a good leader nurse are willing to implement evidence-based practices and are highly motivated, well informed, and committed to organizational goals. Therefore, they perform patient care in a more effective and planned process. It has become imperative to examine the role of leadership styles of nurse managers on staff outcomes after miscarriage of health workforce, which is a global nursing problem, increasing health care costs and workload [9, 10].
There is a limited number of articles in the literature about the leadership styles of nurses. In these studies, the importance of leadership styles and practices on patient outcomes and patient safety, health service power and corporate culture were determined [3]. However, Cummings [10] stated that most styles can be grouped under relational leadership or task-focused leadership. Relational leadership styles focus on people and relationships. It includes transformational, emotional intelligence, resonance, and participatory leadership. These styles are positively associated with staff satisfaction, organizational commitment, improved staff health welfare, stress reduction, job satisfaction, productivity increase, effective study, and positive patient outcomes. However, task-focused leadership is focused on completion of works, deadlines, and directives. Task-focused leadership styles include operational, autocratic, and laissez-faire leadership [10].
2. Leadership styles in nursing
2.1 Relational leadership
Relational leadership styles focus on people and relationships and include transformational, emotional intelligence, resonance, and participatory leadership [11]. These leadership styles are associated with increased employee satisfaction, organizational commitment, improved staff health and well-being, stress reduction, job satisfaction, increased productivity, effective work, and positive patient outcomes [10].
2.1.1 Transformational leadership
Transformational leadership is considered the gold standard of leadership [11]. Transformational leadership is at the center of nursing because it has an impact on patient outcomes, employee satisfaction, and safety culture. Transformational nurse leaders first perform nursing, communicate effectively with their audiences, and become effective role models [12]. Such leaders are motivated and empowering, encouraging and following their audience for organizational goals and individual goals [13, 20]. In addition, it is explained how the transformational leaders have four characteristics that affect their audience. These characteristics are charisma, inspirational, intellectual thinking, and individual attention [42].
It is thought that the transformational leaders fascinate their audience with the charisma feature. This fascination is sometimes associated with the physical characteristics of the leader as well as communication skills and vision. The inspiring character of transformational leaders supports and motivates their followers with encouraging speeches in case of hard work and crises [14].
Transformational leaders, with their intellectual characteristics, encourage their followers to think innovatively and to think about how we can do it better. At the same time, these leaders do not prefer their followers to accept their thoughts as they are [14]. Finally, the transformational leaders, who are interested in their followers individually, advise them in line with their individual needs. In addition, leaders appreciate their followers within the team.
When considered with a general assessment, transformational leaders think that their followers should be evaluated individually and the needs and characteristics of the followers may change with the influence of the leader. Therefore, with the mentoring of the leader, the development of the followers increases at the same rate.
2.1.2 Resonance leadership
Resonance leadership is based on emotional intelligence and awareness, including being open and sensitive to judgment [15]. Resonance leaders have emotional intelligence features. These are self-awareness, self-management, social awareness, and relationship management [16]. According to these characteristics, resonance leaders are effective in managing and solving conflict, democratic, collaborative, and can find solutions to problems.
2.1.3 Emotional intelligence
Emotional intelligence was first described as a feature of transformational and resonant leadership in the 1980s. Leaders with emotional intelligence have four important structures: self-awareness, self-management, social awareness, and social skills. Emotionally intelligent leaders are sensitive to the well-being, emotions, and emotional health of themselves and their followers, and develop effective personal relationships while directing followers to common business goals. Emotionally intelligent leaders manage and reflect their emotions, making rational decisions to ensure teamwork and collaboration. Emotionally intelligent leaders are also effective in conflict resolution because they have the ability to see the situation from others’ perspective and manage work stress [11].
2.1.4 Participatory leadership
In participatory leadership, the views of individuals and groups are taken into consideration. Knowledge, experience, skills, and innovation are of great importance in the decision-making process, with a wide range of expertise and participation in engagement. In 2016, WHO called for participatory leadership to replace hierarchical leadership models of health leadership, suggesting that inclusiveness and the involvement of various stakeholders would strengthen health services [17].
2.2 Task-focused leadership
The task-focused leadership style involves planning business activities, clarifying roles within a team or a group of people, as well as a set of objectives, and continuous monitoring of processes and performance. Task-focused leaders focus on completion of jobs, deadlines, and directives [10]. Task-focused leadership is significantly associated with high-level patient satisfaction [18].
2.2.1 Transactional and autocratic leadership
“Do it now!”
This concept, which is referred to as “transactional leadership” in English literature, is used as “interactionist,” “operational,” or “transactional” leadership in different sources. Transactional leadership is a leadership style that provides short-term goals and motivates viewers through the fulfillment of individual needs in exchange for high performance toward organizational goals [19]. Leaders in transactional leadership act as exchanges managers by exchanging followers who lead to improvement in production, and are interested in processes rather than shared values with forward-thinking ideas [18, 20].
Transactional leadership style emerges in two basic forms as “management with exceptions” and “conditional rewarding” [21, 22]. The form management with exceptions is divided into two as active and passive. The active leader monitors the performance of the team followers and intervenes to correct these errors when he/she detects errors. The passive leader expects the followers’ mistakes to draw their attention before giving negative feedback or any warning [23]. In conditional rewarding, transactional leaders clearly explain to their followers what their duties are, how they will be made, and how they will be rewarded if the desired tasks are fulfilled satisfactorily [21, 24].
Transactional leaders are cultural carriers who maintain the existing order and act in line with traditions and past [25]. In crises where an explicit orientation is required, the transactional leadership approach is an effective style. Transactional leadership can be the best leadership style for the direction of critical events [18, 26]. This leadership style can be effective in emergency situations such as cardiac arrest, by enabling nurses to focus on the task as a whole on the patient [27].
In the literature, transactional leadership and transformational leadership are explained together and comparisons are made. Besides, unlike the transformational leadership, leaders who adopt an interactive approach want to maintain the same things instead of changing the future, and they are less concerned with the creative and innovative aspects and focus on concepts such as efficiency and quality [28]. Bass emphasizes the use of interactive leadership as a conditionally rewarding performance, especially among followers and leaders [29]. While transformational leadership results in a performance beyond expected, interactive leadership focuses on the expected results [30]. According to the transactional leadership, leadership is seen as a simple mutual exchange between leaders and followers based on economic or political reasons, while transformational leadership states that leaders and followers influence each other in order to achieve higher levels of motivation and morale [31].
Another type of transactional leadership is autocratic leadership. Autocratic leaders are defined as directives, controlling, power-oriented, and closed-minded. The leader describes the “what, when, why, and how” of the task. He/she emphasizes obedience, loyalty, and strict adherence to the rules. Followers do what the autocratic leader says [32]. The autocratic leadership style can be considered ideal in emergencies because he or she takes all decisions himself/herself, regardless of the views of the leading staff [3]. Because information is seen as power, critical information can be hidden from the team. Mistakes are not tolerated and individuals are accused rather than erroneous operations. Rewards are given for compliance, but disobedience is punished [18, 32]. In addition, autocratic leaders can create fear among staff and often make decisions without consulting the team [32]. These leaders motivate their subordinates by using their “legal powers,” “rewarding powers,” and “coercive forces.” Autocratic leaders may not be welcome by their team, but this can be transformed into appreciation and devotion when the positive results of their leadership emerge. Although staff do not like autocratic leaders, they often work well on their orders [18, 32]. This leadership approach can be useful at the moment when it is necessary to make quick decisions or to mobilize uneducated and less-motivated followers in the short term by pressure and fear [6, 33, 34]. The positive aspect of this style is that it works perfectly in emergencies or chaotic situations with little time for discussion.
Schoel et al. found that very popular leaders were perceived as ineffective, while unpopular leaders could be perceived as effective [35]. According to the results of Uysal et al., the perception of the behavior of hospital managers as autocratic by followers decreases the productivity of the work [6], because autocratic leadership is perceived negatively by the followers; the reason is that the authoritarian attitude does not give the employee the right to speak, and that the awards and punishments are precise and clear.
2.2.2 Laissez-faire leadership
The style of leadership recognizing full freedom is also referred to as “laissez-faire” in the literature and is expressed as “let them do it.” This kind of a leader advises the process by not participating in the process, encourages followers to generate ideas, offers suggestions when asked by followers, and declares opinions. [31]. Leadership that recognizes full freedom is a style in which the leader provides little or no orientation or control, and prefers a practical approach. Fully free leadership style includes a leader who does not decide, and acts without staffing or supervision [3]. The main task of the leader is to provide resources. Such leaders dissipate responsibilities and retreat and refrain from taking decisions [31]. The leader only gives his/her opinion when asked about his/her opinion on any subject, but this view is not binding on his/her followers [36].
Leadership that recognizes full freedom is an authoritative, task-focused leadership style, because it involves the regulation of tasks in times of crisis, so it shows reactive leadership. This style of leadership is often used by inexperienced leaders or those who are about to vacate their leadership positions, who prefer to give up their followers or others to change their positions, such as those who would like to give up their job [18]. The leader leaves the followers on their own. Followers do what they think is the best. Followers are trained to find the best solution to their problems. Whenever he/she sees it necessary, a person can form a group with whom he/she wants to solve problems, try new ideas, and make the decisions that he/she thinks are most appropriate for him/her [37, 38].
There are positive and negative aspects of the leadership style that gives full freedom. The first positive aspect of this leadership style is the determination and implementation of the goals, plans, and policies of employees or members of the organization, and it mobilizes the creativity of each member or employee [39]. The second positive aspect is that employees are motivated to train themselves and find the most appropriate solution to the problems. When the individual deems it necessary, he/she creates a group with the people he/she wants, solves the problems, tries new ideas, and reaches the most appropriate decisions [40]. The negative aspects of leadership, which gives full freedom, are the emergence of turmoil within the organization and the fact that everyone leads to the targets he/she wants and even toward opposing targets. Another disadvantage is the significant decrease in organizational success, independent of personal achievements.
Skogstad et al. state that the type of leadership recognizing full liberty reinforces the role conflict and role ambiguity experienced by the individual, and increases the conflicts with colleagues [40]. Hinkin et al. also state that leadership behaviors that recognize full liberty harm the punitive and rewarding roles of the leader and decrease leaders’ effectiveness [41]. Chaudhry and Javed state that fully free leadership has no effect on the motivation of the followers compared to other types of leadership [42]. Şentürk et al. reveals that fully free leadership does not have a reinforcing effect on innovative behaviors but rather reduces it [31]. According to the results of Uysal et al., the perception of the behavior of hospital managers as autocratic by followers decreases the productivity of the work [6]. Because autocratic leadership is perceived negatively by the followers. The reason is that the authoritarian attitude does not give the employee the right to speak, and that the awards and punishments are precise and clear.
2.2.3 Instrumental leadership
Instrumental leadership focuses on choosing an appropriate strategy along with appropriate resources to achieve business goals, and it is vital for sustainable corporate performance [43, 44]. This leadership style is part of the spectrum of transformational and interactive leadership styles. Instrumental leaders can be effective managers because they ensure efficiency protection. Thus, jobs are completed in line with the resources, strategic vision, and time constraints of the health facility [45]. In current leadership approaches, the strategy and task-focused developmental functions of the leaders are not taken into account; however, strategy and task-focused functions, which are instrumental forms of leadership, are essential for organizations and followers to ensure sustainable performance. Instrumental leadership is based on neither ideals nor swap relationships. Instrumental leadership includes ensuring harmony between the organization and the environment, developing strategies, preparing task and strategy tables, using resources effectively, and providing performance feedback [44]. The most prominent feature of the instrumental leadership type is the determination of the subordinates’ path by the leader [34]. The instrumental leader is mainly concerned with the timely completion of the work related to the desired goal; it focuses on functions such as setting goals, organizing group members, setting up the communication system, and determining work-related times [46]. Akyurt et al. found that instrumental and interactive leadership have a statistically significant and positive effect on job satisfaction and organizational commitment [21]. Tengilimoglu and Yigit, in their study on 355 state hospital workers in order to determine the effect of leadership behavior in hospitals on job satisfaction of the employees, found that the leadership style with the highest job satisfaction were participatory, instrumental, success-oriented, and supporting leadership, respectively [34].
3. Effective leadership
As the health sector is in a process of change, new leadership approaches need to be implemented to effectively manage this new structure [46]. Developments in the field of management-organization and organizational behavior and new concepts have also led to the emergence of new leadership styles in leadership [4]. Leadership is important for every organization as well as for health organizations, because the success of an organization is a good leader [47]. For effective leadership, it is important to focus on the dynamic relationships between guidance, leadership values, culture, talent, and organizational context [48]. Effective leaders in health care services consider safe, qualified, and friendly care as the top priority. Effective leadership is critical to facilitate quality care, patient safety, and positive staff development. Leaders make the voice of patients continuous; they continuously monitor their patient experiences, concerns, needs, and feedback [49]. Nurses, the largest workforce in a health institution and a dynamic profession, play an important role in health leadership and policy-making, while maintaining their traditional care skills [50]. The leadership style of executive nurses plays an important role in the provision of job satisfaction and motivation of nurses, development of institutional commitment, and effective management of conflicts [51, 52, 53]. In addition, effective leadership styles can increase the quality of health care outcomes. In addition, leadership in health facilities is considered as an important factor in ensuring quality health services, patient satisfaction, and financial performance.
4. Conclusion
Nurses are responsible for guiding the community because of their responsibilities in health care. Patient care and education, effective communication, and clinical management are the most important tasks. These tasks are closely related to leadership behavior. Nurses who exhibit leadership behavior will be pioneers in bringing the profession to a professional level. The goal of future health care institutions should be to influence the quality of patient care through a good nursing leadership. Future research should focus on the development, applicability, and implementation of robust leadership style models in different health environments. These studies should include multidisciplinary professional teams; strengthen the role of nurses and other health professionals; and address organizational parameters and individual wishes, preferences, and expectations for quality of life and health care.
Acknowledgments
We thank everyone who provided scientific guidance.
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"nursing, leadership, leadership styles, patient safety, quality of care",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/69876.pdf",chapterXML:"https://mts.intechopen.com/source/xml/69876.xml",downloadPdfUrl:"/chapter/pdf-download/69876",previewPdfUrl:"/chapter/pdf-preview/69876",totalDownloads:572,totalViews:0,totalCrossrefCites:0,dateSubmitted:"April 11th 2019",dateReviewed:"September 11th 2019",datePrePublished:"November 4th 2019",datePublished:null,dateFinished:"November 4th 2019",readingETA:"0",abstract:"Recent developments in the field of management-organization and organizational behavior and new concepts have also led to the emergence of new leadership styles in leadership. Leadership in health services is important for following innovations and adapting to current situations. Nurses working together with other health personnel in hospitals providing health services constitute an important group in leadership. Nursing, which is a key force for patient safety and safe care, is a human-centered profession, and therefore leadership is a key skill for nurses at all levels. The leadership styles of nurse managers are believed to be an important determinant of job satisfaction and persistence of nurses. The need for nurses with leadership skills and the need for nurses to develop their leadership skills are increasing day by day. There are several leadership styles defined in nursing literature. These leadership styles are examined under the titles of relational leadership style, transformational leadership, resonant leadership, emotional intelligence leadership, and participatory leadership. The task-focused leadership style is explored under the headings of transactional and autocratic leadership, laissez-faire leadership, and instrumental leadership.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/69876",risUrl:"/chapter/ris/69876",signatures:"Serpil Çelik Durmuş and Kamile Kırca",book:{id:"9047",title:"Nursing",subtitle:"New Perspectives",fullTitle:"Nursing - New Perspectives",slug:"nursing-new-perspectives",publishedDate:"December 16th 2020",bookSignature:"Serpil Çelik Durmuş",coverURL:"https://cdn.intechopen.com/books/images_new/9047.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"189558",title:"Ph.D.",name:"Serpil",middleName:null,surname:"Çelik Durmuş",slug:"serpil-celik-durmus",fullName:"Serpil Çelik Durmuş"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. 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The Effect of Leadership Behaviors of Clinical Responsible Nurses on Nurses’ Job Satisfaction. (Thesis). Halic University, Institute of Health Sciences. İstanbul. 2009'},{id:"B52",body:'Bucak B. The Perceptions of Leadership Approaches and Conflict Management Strategies of Nurses Who Work in Two Different Hospitals in Ankara. (Thesis). Gazi University Institute of Health Sciences. Ankara. 2010'},{id:"B53",body:'Gülkaya G. Transformative Leadership Behaviors of Nurses in Service and Motivation Status of Nurses Working Together. (Thesis). Hacettepe University, Institute of Health Sciences. Ankara. 2012'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Serpil Çelik Durmuş",address:"serpilcelik2010@gmail.com",affiliation:'
Nursing Management Department, Faculty of Health Sciences, Kırıkkale University, Turkey
Nursing Department, Faculty of Health Sciences, Kırıkkale University, Turkey
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We are currently in the process of collecting sponsorship. If you have any ideas or would like to help sponsor this ambitious program, we’d love to hear from you. Contact us at info@intechopen.com.
\n\n
All of our IntechOpen sponsors are in good company! The research in past IntechOpen books and chapters have been funded by:
\n\n
\n\t
European Commission
\n\t
Bill and Melinda Gates Foundation
\n\t
Wellcome Trust
\n\t
National Institute of Health (NIH)
\n\t
National Science Foundation (NSF)
\n\t
National Institute of Standards and Technology (NIST)
\n\t
Research Councils United Kingdom (RCUK)
\n\t
Foundation for Science and Technology (FCT)
\n\t
Chinese Academy of Sciences
\n\t
Natural Science Foundation of China (NSFC)
\n\t
German Research Foundation (DFG)
\n\t
Max Planck Institute
\n\t
Austrian Science Fund (FWF)
\n\t
Australian Research Council (ARC)
\n
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