Chapter 12: Developments in clothing protection technology – Functional Textiles for Improved Performance, Protection and Health


Developments in clothing protection technology

W. Zhong,     University of Manitoba, Canada

N. Pan,     University of California, Davis, USA


Clothing protective technology provides protection for millions of people from hazards at work or in emergency situations. Different types of protective clothing have been developed to protect us from various environmental hazards. The two major issues of protective clothing are its protective function and the comfort it provides as clothing. Crucial textile components for the design and development of protective clothing include fiber species, fabric structure and physical/chemical finish applied in the fabrication process. Since the design and/or functionalization of these components greatly influences the performance of protective clothing, much work has been concentrated on one or several of these components, and theories and simulation models have been developed to explain the mechanism of clothing protection. It is expected that nanotechnology and smart/intelligent textiles will be two heated topics in the future development of clothing protection.

Key words

clothing protection

clothing comfort


smart/intelligent textiles

12.1 Introduction

Through its protection of millions of people from hazards at work or in emergency situations, clothing protective technology may be the most important of the ‘personal protective technologies’ (PPT). It helps maintain the health and safety of people by reducing or eliminating hazardous exposures to heat, cold, dusts, toxins, radiations, impact and biohazards. Extensive efforts have been devoted to the research and development of new technology for clothing protection, in such fields as new materials, fabric structures and innovative treatments. This chapter will provide an overview of these development efforts and results, and of how they can enhance the function and/or comfort of protective clothing.

12.2 Key issues of protective clothing

Different types of protective clothing have been developed to protect us from various environmental hazards, such as extremely high/low temperatures, chemicals, micro-organisms, insects, UV radiation and so on. Despite its varied end uses, protective clothing has traditionally involved two major issues: its protective function and the comfort it provides as clothing.

When we speak of the protective function of clothing, we usually mean that what we wear will serve as an effective barrier against hazards. Depending on the nature of the hazards, the protective clothing may be designed to be waterproof, dust-impermeable, bulletproof, fireproof, etc. High performance fibers, special fabric structures or special finishes, etc. are generally regarded as able to render a clothing system protective, and are used for such a capacity. The design issues will be discussed in detail in the next chapter.

‘Comfort’, on the other hand, may mean more than is usually suggested by the word. Direct contact and interactions between textiles and the skin may cause reactions, or even damage and diseases [1], and may be responsible for skin irritation and intolerance caused by textiles, dermatitis caused by chemicals (i.e. dyes and finishes) and physical contact/friction, and so on. When we wear – or are advised to wear – a piece of clothing that is ‘protective’, we expect that it will be so ‘comfortable’ as never to cause us these problems. Now it is clear that such comfort can be derived from novel designs of the microclimate between clothing and the skin, which ensures thermal clothing comfort as well as comfort that necessarily goes with protective clothing.

12.2.1 Microclimate

Water escapes through the skin in two different ways: passive loss and sensible loss. From the deeper, highly hydrated layers of the epidermis and dermis, a passive flux of water takes place towards the more superficial stratum corneum (SC) layers, which have a relatively low water content. This is so-called transepidermal water loss (TEWL) [2]. Extensive research work has been published on the topic of TEWL [36]; however, knowledge about how textile materials influence TEWL is limited.

In 1987, Hatch et al. reported an in vivo study of water content in the surface layers of human SC and water evaporation from its surface due to the placement of fabrics on the skin for varying time periods [7]. A lightweight fabric placed on the skin produced no change in skin water content or evaporative water loss from the SC. Only for occluded treatments (e.g. fabric plus plastic film) did water content and evaporation increase as the covering fabrics remained for longer periods.

Water loss through the skin may also occur in the form of perspiration or sweat, secreted by the eccrine sweat glands deep in the dermis. Water evaporation via secretion absorbs heat, and thus helps regulate body temperature in response to environmental changes. For humans to feel comfortable, a fairly narrow range of surface temperature and humidity must be maintained in the air immediately surrounding the body. Clothing, therefore, plays an important role in regulating body temperature and controlling heat loss. The term microclimate, accordingly, has been used frequently to describe the environmental parameters that influence heat exchanges such as temperature, humidity and microspace air stream between the skin and clothing [8]. Microclimate is an important factor for wear comfort, and depends on properties such as moisture and heat transport through the clothing material, and on physiological and environmental conditions.

Clothing comfort has been extensively studied; however, not much has been done towards clarifying how the skin responds to the clothing fabric in various conditions. Hatch et al. published works revealing in vivo cutaneous and perceived comfort response to fabric [914]. Their work began with experiments in a simulated skin/fabric/microclimate system composed of a modified Kawabata Thermolabo apparatus housed in a controlled environmental chamber [11]. The three experimental fabrics (one cotton and two polyester fabrics with different fiber deniers) showed small differences in water vapor and air permeability as well as energy dissipation rates. The results suggested that these thermophysiological comfort parameters were related more to fabric structures than to fiber contents. Also, these researchers added, different mechanical and surface properties of fibers were found to contribute to variation in sensorial comfort of the experimental fabrics [9]. They then went on to document water content and blood flow in human skin under garments worn by exercising subjects in a hot and humid environment [10]; no significant differences were observed between the three experimental fabrics in terms of alteration in capillary blood flow, SC water content, skin evaporative water loss or skin temperature [12]. These researchers made further investigations, placing fabric patches directly on the volar forearm skin of the subjects instead of having them loosely worn by the subjects [13, 14]. The experiments revealed that, for normal skin, SC hydration generally increase as fabric moisture content increased.

Kwon et al. compared the physiological effects of the hydrophilic and hydrophobic properties of the fabrics worn by exercising and resting subjects with and without wind [15]. Three types of materials with different moisture regains (wool/cotton blend with high moisture regain, 100% cotton with intermediate regain, 100% polyester with low regain) combined to form a clothing ensemble for the test. The results indicated that hydrophilic properties of the fabrics were physiologically significant for reducing heat strain (including skin temperature, clothing microclimate temperature and humidity) and pulse rate for both the exercising and resting subjects, especially when influenced by the wind.

Generally, the experiments and analysis on skin response to textile and clothing system have not yet led to commercial interventions. One reason is the difference from one subject to the other in terms of physical status and sensitivity. When it comes to the in vitro experiments, the difficulties lie in how to realistically represent the whole skin/fabric/microclimate system.

12.2.2 Skin reactions and irritations caused by textiles

Irritation of the skin as a result of its reaction to textiles, all too often due to chemicals or dyes, will be discussed in Chapter 21.

Skin irritation may also be caused by physical contact and friction between clothing and the skin. The frictional properties of the skin are of interest in the area of cosmetic products and clinical dermatology dealing with acute and chronic friction trauma such as blisters and calluses [16].

A study on skin friction properties involved human subjects of different gender and age [17]. Measurements were obtained from 11 anatomical regions, namely, the forehead, upper arm, volar and dorsal forearm, postauricular, palm, abdomen, upper and lower back, thigh and ankle. The dynamic friction coefficient did not vary significantly between age and sex groups but varied considerably from region to region. It was suggested that frictional properties of the skin are dependent more on water content or non-apparent sweating, and may be related to sebum secretion. A subsequent study showed that surface lipid content (SSL) is also related to these properties [18].

Other studies on the influence of skin friction on the perception of fabric texture and pleasantness under a series of environmental conditions from neutral to hot-dry and hot-humid also revealed that moisture on the skin surface increased skin friction [19] and that fiber type and moisture influenced fabric-to-skin friction measurements [20]. According to these reports, moisture on the skin is more important than the fiber type or fabric construction parameters in determining the nature and intensity of fabric-to-skin friction, and glabrous skin friction changes less with wetting than with hairy skin.

Recent studies have further clarified how moisture, sebum and emollient products are related to skin friction properties [21]. Elkhyat et al. recorded the influence of hydrophilic/hydrophobic balance (Hi/Ho) of the skin surface on the friction coefficient, using both in vitro and in vivo experiments [22]. They showed that the higher hydrophobia tendency of the surfaces, the lower the friction coefficient. The friction coefficient, therefore, may quantify the influence of lubrificant/emolients/moisturizers applied to the skin. And the relationship between the friction coefficient and the hydrophilic/hydrophobic balance can be reversed in the presence of water and sebum on the forehead.

To measure the frictional coefficient of the skin, use is now made of such commercial instruments as the UMT series Micro-Tribometer [23, 24] and the KES-SE Frictional Analyzer [25, 26]. However, measurements thus obtained may lack comparability, due to disagreement on which scientific law governs the relationship between physical pressure and skin friction. The classic Amonton’s law [27], which stipulates that the friction coefficient remains unchanged under varying normal loads and speeds of the probe (i.e. the opposing material used to measure skin friction), has long been challenged by numerous researches including some recent ones [23, 26], in which the friction coefficient was found to be inversely proportional to load [28].

Compared to what has been achieved in the study of the frictional coefficient of the skin surface, far less work has been performed on the assessment of frictional force between the skin and fabric. Such assessment usually involves slowly pulling fabric samples across the surface of the skin (i.e. forearm) so as to record with a force transducer the frictional force required to pull each fabric across the skin. The pressure between the fabric and skin is often applied by suspending a weight to the free end of the fabric. The resulting irritation effects caused by friction can then be documented [19, 20]. Other methods for measuring skin/fabric frictions were achieved using a strain gauge [29], or strained gauged flexure couples arranged in such a way as to try to detect both the normal and frictional force [30]. Measurements can be made by giving the applied material a wipe with the right index finger.

Hatch summarized work performed to understand skin irritation caused by contact and/or friction of clothing or other textile materials [31]. It is reported that dermatological problems are linked to six fibers: (a) nylon, for contact dermatitis and contact urticaria, (b) wool, for acute and cumulative irritant dermatitis, aggravate atopic dermatitis, allergic contact dermatitis, and immulogic contact urticaria, (c) silk, for atopic dermatitis and contact urticaria, (d) glass fiber, for mechanical irritation, (e) spandex fiber and (f) rubber fiber. Some forms of dermatitis, as in the cases of nylon, spandex and rubber fibers, were often caused by dye, finish or fiber additive instead of fiber material itself.

A study on the effects of wearing diapers on the skin showed that skin wetness was proportional to diaper wetness, and, with increased skin wetness, coefficients of friction and abrasion damage would increase [32]. According to a study of the electrostatic potentials generated on the surface of the scrotal area, the accumulated electrostatic charges on the pants were due to the friction of the pants with the skin when different types of textile fabric were worn [33]. Polyester pants showed the highest potential while polycotton pants produced less than half that level. The daytime readings were higher than those in the night, probably mainly due to the higher temperature and activities during the day. A related study even suggested that this electrostatic potential may be responsible for inhibited hair growth [34].

12.3 Developments in clothing protection

Crucial textile components for the design and development of protective clothing include fiber species, fabric structure and physical/chemical finish applied in the fabrication process. Since the design and/or functionalization of these components tremendously influence the performance of protective clothing, much work has been concentrated on one or several of these components. Theories and simulation models have been developed to explain the mechanism of clothing protection.

12.3.1 Textile components in the development of protective clothing

Textile fiber is the basic unit of textiles. In the last few decades, a wide variety of advanced fibers were developed for protective clothing. For example, fibers with high heat resistance were made for thermal protective clothing. Aramid fibers were manufactured from the long-chain synthetic polyamide in which at least 85% of the amide linkages are attached directly to two aromatic rings [35], namely the aromatic groups are linked into the backbone chain through either the 1, 3 positions (meta-aramid) or the 1, 4 positions (para-aramid). Nomex and Kevlar from Dupont are widely used meta- and para-aramid fibers, respectively. Meta-aramid fibers are known for their good thermal stability and long-time stability at high temperatures, which justify their extensive use in thermal protective clothing. Valued for their high tenacity and high modulus, Kevlar fibers, on the other hand, are frequently used in ballistic fabrics. Other high performance fibers for protective clothing include both organic fibers (polybenzimidazole fibers, high molecular weight polyethylene, etc.) and inorganic fibers (glass fibers, carbon fibers, etc.).

Alongside the development of new fiber species is the development of new fiber formats. The high surface area to volume ratio of nanofibers explains why they can be an ideal material for protective clothing against biochemicals and air contaminants. The woven, non-woven or knitted fabrics, when coated with nanofibrous membranes, can be made into protective clothing or masks that will present minimal impedance to moisture vapor diffusion required for evaporative cooling. The water vapor transmission test results showed that electrospun polyurethane webs were able to significantly improve the performance of protective clothing as a barrier to liquids, and that air permeability would decrease with increasing electrospun web area density [36]. It was also demonstrated that a layered fabric system (electrospun polyurethane fiber web layered on spunbonded non-woven) with a web area density of 1.0 and 2.0 g/m2 exhibited higher air permeability than most PPE (personal protective equipment) materials currently in use [37]. Zinc titanate nanofibers were also tested and found able to improve detoxification properties of protective clothing [38].

Fabric structure is another important textile component. One of the most frequently used fabric structures is the multilayered, so termed because such a structure is composed of a number of layers and able to provide multi-protection to the wearer. Multilayered fibers have been extensively used in thermal protective clothing as static air trapped between the layers provides excellent insulation. Recently, much research work has been performed to gain a better understanding of the heat and moisture transfer through the multilayered fabrics so as to ascertain a fabric structure that will contribute the highest level of safety and the largest degree of comfort [3941]. Polytetrafluoroethylene (PTFE)/fabric laminates, for instance, have been used in waterproof, chemical/biological protective clothing, which is both protective and breathable [42, 43]. Composite fabric/system has been drawing increasingly eager attention from protective clothing researchers, and a variety of materials have been used for such composite fabric systems to bring in a synergy for the purpose of protection and/or comfort [4446].

Various treatments and finishes have also been introduced to enhance the protection of clothing. Many flame retardants, including those based on phosphorus, have been used in treating cellulose fibers, which will be blended into inherent flame-resistant fibers to achieve both thermal protection and comfort [4750]. Treatments that will help render the protective clothing antibacterial [5153] and anti-insect [5458] have been extensively studied. Nanotechnology [52, 53] and smart/intelligent materials [5962] have found their applications in the treatment of fibers or fabrics, also for the purpose of enhanced protection.

12.3.2 Modeling and simulation for clothing protection

Simulation models have been developed to aid related efforts, often by precisely and vividly representing the transport process of hazardous particles penetrating the fabric structure [63]. These researches are important because they generate further knowledge on which to base further research, and are themselves cost-effective than the normal experimental tests.

The ability of a fibrous filter to collect aerosol particles is usually expressed in terms of its filtration efficiency, and the fraction of entering particles it retained. This efficiency is often derived from the aerosol filtration efficiency of a single filter element (η), whose size and shape are chosen to best represent the microstructure and porosity of a given filtering material [64, 65]. The single fiber efficiency is the combined effects of the various mechanisms of capture, including direct interception, inertial impaction, diffusion deposition, gravitational settling, etc. [64, 65]. These mechanisms are not necessarily independent. Adhesive forces involved in the filtration process are also studied. They include Van der Waals forces [65, 66] and electrostatic forces [67, 68] between the particle and a fibrous filter.

The arrangement formats of fibers in a filter, however, always have great impact on the aerosol filtration since the fibers interact with each other and with the particles during the filtration process. The most difficult job in the study of aerosol filtration processes is the description of the heterogeneous fibrous structures. To account for the effect of fiber arrangement, two multifiber models were used to investigate the interception efficiency of fibrous filters composed of symmetrical arrays of fibers, including the parallel and staggered arrays [69, 70], thus enabling the filtration process to be simplified as a two-dimensional periodic flow. Shapiro [71] introduced an inclusion model, where the filter material was regarded as a uniform matrix containing a certain volumetric fraction of inclusion of a certain size. Both inside and outside the inclusion, the filter structure is assumed to be homogeneous, albeit with different porosities. Alternative approaches [72] involved a model where the filter media was represented by a two-dimensional distribution [73] of cells of varying packing density.

When the filter structure is defined, the flow field in the course of filtration can be characterized by such constitutive equations as the continuity equation and Darcy’s law. The constitutive equations and the corresponding boundary conditions can be solved analytically or numerically to give the pressure field and velocity field. These relations, combined with expressions for the single fiber efficiency, allow calculation of the efficiency of each element of the filter (local efficiency), as well as their combination or averaging into the overall efficiency of filter materials [72, 74].

However, none of these models suffices to precisely describe the heterogeneous structure of a fibrous filter and the stochastic nature of aerosol behavior. Other discrete approaches have therefore been attempted to deal with problems involved in the description of heterogeneous structures. These approaches include the lattice Boltzmann (LB) model [75] and the cellular automata (CA) probabilistic model [76]. The CA models keep track of the many-body correlations and provide a description of the fluctuations, while the LB models are believed to be numerically more efficient and exhibit more flexibility to adjust the fluid parameters [76].

Then a statistical mechanics model, i.e. the Ising model combined with Monte Carlo (MC) simulation, was introduced as a new approach to the study of aerosol filtration by fibrous filters. The Ising model had earlier been presented for the study of ferromagnetic phase transition [77]. Since then it has been frequently used to study a system consisting of interactive subsystems, each of which bears two interchangeable states [7881]. In the Ising model, a real system is divided by a grid into a discrete system composed of a number of lattice cells. The filtration system is thus treated as a system made from such subsystems as fiber cells and aero particle cells that interact with each other through adhesion. The transport and deposition process of the particles in the fibrous substrate is due to interactions as well as the effect of moving air stream, resulting in each particle moving from one cell to the other. In general, such a change in the system’s configuration is driven by the energy difference after and before the change, subject to the random fluctuations represented by the MC simulation. Allowing use of a simpler binary algorithm, the Ising model makes for greater simulation accuracy and efficiency.

Model description

To describe the filtration process through a fibrous filter, a discrete 3-D Ising model is proposed. The system is divided into a lattice of a number of cubic cells. The length of a single cubic cell can be chosen arbitrarily and, for the sake of convenience, is made to be equal to the diameter of a fiber.

To represent the possible states of each cell, two variables are introduced:

1. si, indicating whether a cell (i) is occupied by a particle (si = 1) or not (si = 0);

2. Fi showing whether a cell (i) is filled with fibrous substrate (Fi = 1) or not (Fi = 0).

Energy of the system (the Hamiltonian) should be the summation of the energies of each single cell Hi, which in turn is the summation of the interactions between the cell i and its 26 nearest neighboring cubic cells (see Fig. 12.1 ), as

12.1 A cell i in a 3-D Ising model with its neighbors.


This equation takes into account all three types of interactions:

1. Cohesive interaction between neighboring particle cells, as shown in the first term on the right hand side of the equation, where A represents the cohesion energy between particles, and the summation of s values is over all nearest neighboring cells of cell i.

2. Adhesive interaction between particle and fiber substrate, shown as the terms in the bracket, where B and C correspond to the adhesion energies between a particle and a fiber substrate in the same cell, and that in the nearest neighboring cells, respectively.

3. Gravitational effect of particles as shown in the last term, where G is the intensity of the gravity field and yi the y-coordinate of cell i in the lattice.

The coefficients in equation [12.1] are determined in a manner described as follows:

It is assumed that the Van der Waals forces dominate the interactions between the fiber and the particles. According to the Lifshitz theory [82], the interaction energy between a particle (sphere) of diameter dp and a surface, and that between two particles (spheres) with diameters dp1 and dp2, can be expressed as equations [12.2] and [12.3], respectively:



where h1,2 is the Hamaker constant, and D the distance between the particle(s) and the surface. An approximate expression for the Hamaker constant of two bodies (1 and 2) interacting across a medium 3, none of them being a conductor, is


where h is the Planck’s constant, ve is the main electronic adsorption frequency in the UV (assumed to be the same for the three bodies, and typically around 3 × 1015 s− 1), ni the refractive index of phase i, εi the static dielectric constant of phase i, kB the Boltzmann constant, and T the absolute temperature.

Two constants, k1 and k2, are used to represent the ratios of A/C and B/C, respectively.


The ratio A/C is equal to the ratio of the cohesive energy between two particles to adhesive energy between a particle and fiber in neighboring cells. As the interaction distances in two cases are the same, the ratio is also equal to the ratio of the Hamaker constants in the two cases. B/C is the ratio of particle/fiber adhesive energy in the same cell to that in the neighboring cells, and therefore equals the ratio of the interaction distances. For interactions between a pair of neighboring particle and fiber cells, the distance, D1, is assumed to be one half of the cell length, while for interactions of particle/fiber within a cell, the distance, D2, depends on the scale of the surface roughness. In the present work, the value of C is determined by simulation to accommodate the experimental data. And the values of A and B are determined by equation [12.5].

The transportation process of aerosol particles through the fibrous substrate is usually accomplished by airflow in a certain velocity. The usual thermodynamic theories specify the considered bodies/systems in a state of absolute equilibrium, whereas aerosol particles transport through fibrous structures in airflow is conventionally categorized in aerodynamics, and it comes with substantial friction loss of transport characteristic of irreversibility. Therefore, dealing with such a problem we have, on the one hand, to make statistical calculations and, on the other, we are compelled to use mechanical energy terms like work of drag force. Assuming a quasi-equilibrium process this way, it is possible to extend MC simulation [79] to the case of aerosol particles transport through fibrous filters in an airflow:

When a particle is suspended in airflow of velocity V, through one time step in which air moves from its original cell to a neighboring cell, the particle can move in four different ways (Fig. 12.2), subject to different probabilities:

12.2 Energy difference due to airflow.

1. In the first case, the particle moves with the air stream to the neighboring cell. Accordingly, there is no relative velocity between particle and air stream during this time step, and the work done to the particle by airflow can be regarded as zero.

2. In the second case, the particle moves to a cell ahead of that of the air, with a velocity V relative to the air. The system energy change (dE) in this time step includes both the change in Hamiltonian, dH, and the work done to the particle by airflow, WA, as:


where l is the size of a cell, FD is the drag force act on the particle with diameter d by the air stream and can be calculated according to the Stokes’ law as


where η is the viscosity of air which, at standard pressure and room temperature, is 1.81 × 10− 5 Pa · s.

3. In case 3, the particle remains in the original cell despite the moving of air, the relative velocity of the particle to the air is − V. Therefore, the system energy change should be


4. In case 4, the particle may deviate from the air stream and move to other neighboring cells, as is the result of the combination of either the above three mechanisms or the diffusion. The influence of diffusion can be represented by the random effect of the MC simulation described in the next section.

The energy difference in each case is then used in the MC simulation to provide the probability for a cell changing its state at each time step.

In all the simulations (MC simulations) in the present study, for the sake of simplicity, movement of fibers is neglected. That is, the filtration process is assumed not to alter the internal structure of the fibrous filter, so that values of F for all the cells are kept constant in a simulation. Therefore, the process of aerosol filtration is the result of each particle moving from one cell to the other and/or depositing on the fiber substrate in a fiber cell. Procedures of the simulation are as follows:

1. Initial configuration is created by developing the lattice, within which the fibrous media are laid. The initial values of both F (1 or 0) and s (1 or 0) for each cell are also determined. A cell i is considered to be covered with fiber (F = 1) if the distance between the cell center and the fiber axis is smaller than the fiber radius.

2. All the particles in the space are scanned. For example, a particle cell i in the lattice is randomly selected. It can move in four different ways as described in the last section (also in Fig. 12.2). For each case, dE (energy difference between the configurations before and after the change) is calculated. Then the case with the lowest value of dE is selected as the most probable change. If a random number uniformly distributed between 0 and 1 is chosen and is smaller than the spin-flip probability, p = exp(− βΔET), the change of configuration takes place. Here, β is a constant inversely proportional to the absolute temperature.

3. An MC step ends when all the particles in the current state have been scanned. Then step 2 is repeated to start a new MC step until the whole simulation is terminated.

In the present study, an MC step is defined as the time in which air moves from one cell to a neighboring one with size l. Therefore, if the velocity of air is V, the relationship between an MC step and real time is


Results and discussion

Based on the above description, a computational simulation algorithm is developed for the process of aerosol particles of different sizes filtering through isotropic fibrous filters with different fiber volume fractions.

Experimental data are adopted from the literature [83]; the filter used for testing is made from a polyester fiber, Dacron, of 12.9 μm in diameter. The filter fiber volume fraction is 27.1%. The particles are mono-disperse aerosols generated from DOP (dioctyle phthalate) solutions of different concentration to give different aerosol particle sizes.

To start the simulation, the length of a cubic cell is made to be equal to the fiber diameter, 12.9 μm. The fiber mat is constructed by generating a certain number of fibers whose center points and orientations are randomly determined. Next, the fiber volume fraction is represented by the ratio of the number of cells that are occupied by fibers to the total number of cells. The simulated system comprises a lattice of 228 × 100 × 50, as shown in Fig. 12.3. The boundaries are periodical. In the space to the left of the fibrous filter, where the in-streams of the aerosols come from, the particles are regenerated after each MC step to maintain a constant input aerosol concentration Cin (the ratio of the number of particles to the total lattice cells on left sides of the filter). When output aerosol concentration Cout (the ratio of the number of particles to the total lattice cells on right sides of the filter) reaches equilibrium after certain MC steps, filtration efficiency of a fibrous filter is calculated as the ratio of Cout to Cin:

12.3 A 3-D Ising model for the filtration process.


It is suggested that the adhesive force on a particle less than 10 μm is much greater than other forces that a particle experience [65]. The sizes of the particles modeled in this work are well below 10 μm. Gravity effect in equation [12.1] can therefore be neglected.

The parameters needed for the simulation are listed in Table 12.1. This model applies to different fibers and particles by taking account of the property parameters for different materials. It can also be seen that interactions between neighboring cells (A and C) are in a much smaller scale than those within the same cell (B). This gap would be reduced in a finer lattice in cases of fibrous filters with more intricate structures, e.g. nanofiber filters.

Table 12.1

Parameters for fiber and aerosol particle at room temperature (20 °C)

Both simulation results (shown as continuous lines) and reported experimental data [83] (shown as discrete symbols) are shown in Fig. 12.4. They are in high accordance, indicating a good validity of the method.

12.4 Simulation and experimental results of filter efficiency vs. particle size; v represents the velocity of particles in simulated penetration, while ev is the velocity of particles in experiments.

Both the simulations and experiments show that, with the variation of particle size, the filtration behavior goes first through a diffusion regime, where filtration efficiency decreases with increase of particle size, as smaller particle size makes for better diffusion and thus better filtration efficiency. Then there is a regime of diffusion transiting to interception, and the efficiency goes down to a minimum, where the dominance of diffusion mechanism is taken over by interception, and then rises with the increase of particle size. Finally in an interception regime, filtration efficiency rises singularly with particle size. Combination of the above mechanisms in the simulation process is represented in the energy expression in equations (12.612.8). To be specific, when the gravity effect can be neglected (for particle size below 10 μm):

1. Increased particle diameter d means higher adhesion between particle and fiber and the particles have fewer chances to deviate from the airflow. This leads to a more prominent impaction/interception mechanism.

2. With decreasing particle diameter, on the one hand, adhesion between particle and fiber is weakened, and it becomes easier to remove a deposited particle from the fiber. On the other hand, the effect of airflow on the particles diminishes, and the particles have more chances to fluctuate around the streamline. Both of these two factors contribute to enhanced diffusion.

Hence there are certain advantages of the present approach. First, the Ising model is capable of describing such complicated systems as aerosol filtration in fibrous structures in a simple binary form, accounting for all the physical mechanisms involved, without using such indirect parameters as single fiber efficiency, as is the case with classical filtration approaches, yet generating robotically informative results. Second, the approach is obviously able to depict the intricate interface between aerosol and fibrous media. This approach can be especially useful for explaining the effect of the interactions that occur at the interface within heterogeneous materials. Further, this model can be adapted to deal with more complicated cases, such as poly-disperse particles filtration through multilayer fibrous filters.

However, since this work is intended to deal with a particle/fiber system where movement of fibers is neglected for the sake of simplicity, the model requires further modification if it is to be applied to study aerosol-fiber systems with considerable fiber movement, in which the parameter F for each cell has to change accordingly to reflect the fiber movement.

12.4 Future trends

Protective clothing provides essential barriers to environmental hazards of different kinds, so as to maintain human safety and health. The developments of clothing protection technology have been focused on the design and development of new materials, structures and/or treatments to enhance clothing protection and comfort. These two key issues, protection and comfort, will continue to be the focus of research in the future. Theoretical and simulation work will also be a future trend, because they offer important design tools when experimental tests are costly, difficult or dangerous.

In addition, nanotechnology and smart/intelligent textiles will be two important topics in the future development of clothing protection: micro-or nano-encapsulation provide highly effectively methods of carrying various active compounds such as antibacterial agents; the high surface-to-volume ratio of nanofibers makes them excellent barrier materials, while the high porosity of nanofibrous structures gives them excellent comfort; the incorporation of smart materials into protective clothing allows sensitive detection of hazards as well as programmable reactions to protect the end users of the protective clothing. As a result, these two highly interdisciplinary technologies are important for the developments in clothing protection technology in the future. A breakthrough in the clothing protection technology will likely depend on the extensive collaboration of researchers in a variety of areas, including material sciences, engineering, chemistry and biology.

12.5 References

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